October 2021 Volume 16 • Number 9 LabManager.com ROLE S ’ R E G MANA B A L D THE IT AGAIN E Z I N O IO OLUT BOUT TO D V E R ATA AI IS A BIG D Optimizing Lab Assets Scalable Lab Monitoring — TRF and Alpha lasers for speed and improved sensitivity Patented Hybrid Technology with independent filter and monochromatorbased optics for performance and flexibility Variable bandwidth selection for optimized fluorophore specificity and sensitivity Ultra-fast plate processing speeds with multiple PMT detectors Microplate incubation to 70 ° C and CO2/O2 gas control option There can only be one Highest-Performance reader... and it’s BioTek’s Synergy Neo2, the most advanced, high-performance, high-speed plate reader on the market today. Designed to meet the sophisticated needs of laboratories, the fully featured and flexible Synergy Neo2 offers uncompromising performance for cell-based and biochemical assays. To learn more about Neo2, visit www.biotek.com/neo2 www.biotek.com Optimize every lab. 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Sridhar Iyengar 14 18 The Data Science for Social Good Lab Strategic Teams and Lab Culture A lab’s culture has a strong influence over the success of an organization’s strategic agenda. Daniel Wolf and Lydia Werth business management lab design How to Effectively Communicate with Non-Scientists asset management 4 How key lessons from Monopoly can be applied to promote equity and limit hypercompetition in academia. Ane Metola Martinez, Claire Lyons, Katharina Herzog, Mathew Tata, Natalie von der Lehr, and Shruti Jain Researchers strive to improve the world through big data. Lauren Everett Learning the “languages” of other departments outside the lab is an important component of business success. Sherri L. Bassner 20 Creating an Inclusive Academic Research Culture 32 Designing for the Unknown 36 A Beacon for Life Sciences Optimizing the Utilization of Lab Assets Analyzing data to improve the availability and effectiveness of instruments and equipment in the lab. Scott D. Hanton Lab Manager October 2021 Flexible lab design plans accommodate current needs, future possibilities. Jeffrey Zynda and Adana Johns University of Michigan BSB wins Excellence in Innovation prize in 2021 Lab Design Excellence Awards. MaryBeth DiDonna health & safety 42 Building Habits through Safety Activities Participation in safety activities from staff and management improves safety culture. Tabi Thompson LabManager.com FLEXIBLE. SENSITIVE. DEPENDABLE. CLARIOstar® Plus The CLARIOstar® Plus multimode mic microplate reader streamlines assay development and validation by combining monochromator flexibility with best-in-class sensitivity. www.bmglabtech.com ©2021 All rights reserved. All logos and trademarks are the property of BMGLABTECH. · LVF MonochromatorsTM for highest sensitivity · EDR technology makes gain adjustment no longer required · Dedicated detectors for luminescence and red fluorescence · Best performance in TRF, TR-FRET, FP and AlphaScreen® · Atmospheric control with gas ramping function · Made-in-Germany dependability October 2021 laboratory product reports LabManager.com QUALITY & COMPLIANCE DIGITAL SUMMIT DEPARTMENTS manager minute Lab managers must protect the quality of their data, research, and projects by being familiar with the procedures and regulations under which they are governed. Lab managers can utilize different tools and ideas to make their jobs easier, and help them to meet or exceed their required standards. Join Lab Manager’s Quality and Compliance Digital Summit Oct. 20-21 as seasoned quality managers discuss the best resources lab managers need to achieve maximum compliance for their labs. 09 Three Keys to More Effective Project Planning in the Lab Learn more: summit.labmanager.com/qualityandcompliance 50 Ask the Expert Better project planning leads to better outcomes and results. Scott D. Hanton industry insights 46 A New Era of Protein Interaction Engineering New bioengineered protein devices allow near-instant response times, but highlight system needs. Rachel Brown ask the expert Computation predictions empower drug discovery. Tanuja Koppal product focus 52 Electronic Laboratory Notebooks Semantic enrichment is helping overcome issues associated with vast amounts of unusable ELN data. Lab Manager® (ISSN: 1931-3810) is published 11 times per year; monthly with combined issues in January/February, by LabX, 1000 N West Street, Suite 1200, Wilmington, Delaware, 19801. USPS 024-188 Periodical Postage Paid at Fulton, MO 65251 and at an additional mailing office. A requester publication, Lab Manager, is distributed to qualified subscribers. Non-qualified subscription rates in the U.S. and Canada: $120 per year. All other countries: $180 per year, payable in U.S. funds. Back issues may be purchased at a cost of $15 each in the U.S. and $20 elsewhere. While every attempt is made to ensure the accuracy of the information contained herein, the publisher and its employees cannot accept responsibility for the correctness of information supplied, advertisements or opinions expressed. ©2013 Lab Manager® by Geocalm Inc. All rights reserved. No part of this publication may be reproduced without permission from the publisher. WDS Canadian return: 1000 N West Street, Suite 1200, Wilmington, Delaware, 19801. POSTMASTER: Send address changes to Lab Manager®, PO Box 2015, Skokie, Il 60076. Aimee O’Driscoll 54 Lab Monitoring Systems Scalable laboratory monitoring systems can help minimize risks—but come with challenges. Aimee O’Driscoll 56 Next-Generation Sequencing Using NGS technologies to understand the impact of the microbiome on health. Andy Tay 58 PCR Leveraging digital PCR to improve detection of viral pathogens in wastewater. Brandoch Cook in every issue 29 Infographic Authenticating your cell lines. 49 The Big Picture Tackling the topics that matter most to lab managers. 60 Innovations In: Mass Spectrometry Important advances in mass spectrometry leading up to the 2021 ASMS Conference. 63 Lab Manager Online 6 Lab Manager October 2021 LabManager.com IF IT USES GAS, IT NEEDS HARRIS. ® + Full Spectrum of In-Stock and Customized Turnkey Gas Distribution Solutions + Gas Regulators, Flowmeters, Automatic Switchover Manifolds and More + + 24–48 Hour Shipping on Most Models Safe and Reliable FIND THE PERFECT PRODUCT NO MATTER THE INDUSTRY + PETROCHEMICAL + FORENSIC + AVIATION + EMISSIONS MONITORING + UNIVERSITIES/RESEARCH + PULP & PAPER + MEDICAL + FOOD, WINE, BREWERIES + BIOTECH & PHARMA CONTACT A HARRIS® SPEC GAS EXPERT 1.800.733.4043 ext. 2 harrisproductsgroup.com harrisspecgas@lincolnelectric.com HarrisSpecGas.com editor’s note How Does Data Influence Your Decision-Making? Data is the backbone of most scientific organizations. Every laboratory produces some form of data; lab managers rely on data to make important business decisions; and if used efficiently, data can offer insight into emerging trends and solutions. Our cover story for this issue, authored by Sridhar Iyengar, PhD, discusses the evolution of how data is being used by lab leaders, and how AI is playing a larger role in collecting, interpreting, and utilizing data produced in the lab. As the capabilities of big data continue to expand, so too, does the lab manager’s role in utilizing it. Today, managers need the technical expertise to maximize the value of the data being produced, and the ability to envision what the lab of the future looks like. As Iyengar states, “Outfitting a lab to collect data for today’s needs alone is shortsighted. It’s imperative that those seeking to leverage data in the lab consider not only the expanded data pipeline of today, but the colossal one of tomorrow.” Iyengar outlines the five stages of laboratory data maturity and sophistication, from elementary to transformative. Turn to page 10 to read the full article, and determine where your lab fits within the five stages. As mentioned, data is key for managers during many decisionmaking processes. This is especially true when evaluating the performance of your lab’s instruments. Our Asset Management piece (page 20) discusses the importance of using data to optimize lab equipment. “Lab asset optimization involves investigating and monitoring a variety of different data about the instruments and In addition to our data-focused pieces, I also wanted to highlight a new feature we are launching in this issue, “Innovations In.” Each issue, our editorial team will highlight some of the latest developments and applications of techniques or products in the lab. For this issue, we discuss innovations in mass spectrometry, detailing three main themes in mass spectrometry that are contributing to new developments in the field, and show promise for the future. Tur n to page 60 to see what those three trends are. Lauren Everett Managing Editor laboratory products group director editorial director art director Danielle Gibbons Robert G. Sweeney shanton@labmanager.com danielleg@labmanager.com creative services director graphic designer rsweeney@labx.com 203.530.3984 Scott Hanton Alisha Vroom Trevor Henderson thenderson@labmanager.com avroom@labmanager.com senior digital content editor managing editor Rachel Muenz Lauren Everett leverett@labmanager.com rmuenz@labmanager.com contributors scientific technical editor Sridhar Iyengar, PhD Sherri L. Bassner, PhD Ane Metola Martinez, PhD Claire Lyons, PhD Katharina Herzog, PhD Mathew Tata, PhD Natalie von der Lehr, PhD Shruti Jain, PhD Daniel Wolf Lydia Werth Jeffrey Zynda Adana Johns Tabi Thompson Tanuja Koppal, PhD Aimee O'Driscoll, BSc, MBA Andy Tay, PhD Brandoch Cook, PhD 8 equipment in the lab,” writes editorial director Scott Hanton, PhD. As Hanton highlights, a common challenge with data collection and investigation is that it is often done manually. Software and other tools are now available to assist lab managers with this process, and offer more meaningful interpretations of their laboratory asset usage. “By having standardized, meaningful definitions of utilization, deploying the right technology to capture the data that fits that definition across critical workflows, and visualizing the data in a way that can translate to lab insights, lab managers are on their way to understanding current usage of lab instruments,” explains Melissa Zeier, enterprise services product manager at Agilent Technologies. Lab Manager Michelle Dotzert mdotzert@labmanager.com creative services coordinator Sherri Fraser sfraser@labmanager.com sales manager Reece Alvarez ralvarez@labmanager.com 203.246.7598 senior account managers Alyssa Moore Mid-Atlantic, Southeast & International amoore@labmanager.com 610.321.2599 Melanie Dunlop rbrown@labmanager.com West Coast melanied@labmanager.com 888.781.0328 x231 business coordinator account manager scientific writer/coordinator Rachel Brown Andrea Cole andreac@labmanager.com eMarketing coordinator Laura Quevedo Ryan Bokor Northeast, Midwest rbokor@labmanager.com 724.462.8238 Published by LabX Media Group president Bob Kafato bobk@labmanager.com managing partner Mario Di Ubaldi mariod@labmanager.com executive vice president Ken Piech kenp@labmanager.com production manager Greg Brewer gregb@labmanager.com custom article reprints The YGS Group labmanager@theygsgroup.com 800.290.5460 717.505.9701 x100 subscription customer service labmanager@omeda.com lquevedo@labmanager.com circulation specialist Matthew Gale mgale@labx.com October 2021 1000 N West Street, Suite 1200 Wilmington, Delaware, 19801 888.781.0328 LabManager.com manager minute MANAGER MINUTE Three Keys to More Effective Project Planning in the Lab by Scott D. Hanton, PhD M any different things have to go right for large lab projects to be successfully executed. We need the right people, with the right training, using the right instruments. As lab managers, we are very aware of these priorities, and take significant time and effort to get them right. However, there are many other aspects of project planning that require a little forethought to ensure the delivery of large projects. It can be helpful to review some of these details with key team members, and ensure that someone is monitoring these details. Here are three tips that will help you and your staff develop a project planning system that will improve delivery and execution on your projects. #1 – Ensure consistent sourcing and supply plan for each of their critical assets. This can ensure the project continues on time, even if equipment problems occur along the way. #3 – Ensure milestone and compliance reporting Many big projects come with important milestones and regulatory oversight. Develop a clear understanding with customers and agencies about what needs to be reported, in what detail, and at what time points during the project. Build the infrastructure that is required to meet those expectations. It is very difficult to catch up on reporting during a large project. To ensure success, it is important to confirm the reporting tools are available and key staff are trained on their use before the project begins. One of the key impacts of the COVID-19 pandemic was the interruption of sourcing and supply. Even ubiquitous lab equipment and supplies had shortages and backlogs. As you prepare for a new project, build plans for consistent supply for the critical equipment, supplies, consumables, kits, and assays. Talk to your suppliers and negotiate delivery times. For especially critical components of the project, find alternate and emergency suppliers. Choose suppliers based on all the value they provide, not simply on one-time costs. Make sure project leaders in the lab have contingency plans for critical components. #2 – Ensure service support Having the right instruments in the lab is only half the battle. The next step to effective project planning is having a strategy to keep all of those instruments and pieces of equipment running consistently during the project. Work with your service providers to have repair and maintenance plans for the course of the project. Negotiate with them for rapid response for critical assets. It might even be worthwhile to build additional redundant capacity for vital systems for some projects. Make sure project leaders have a project continuity Thanks for reading. I hope you can use this information. I am very interested in hearing from you. If you have feedback or comments on this set of tips, or suggestions for future Manager Minutes, I’d love to hear from you. Please reach out to me at shanton@labmanager.com. I’m looking forward to our conversations. Thanks. October 2021 Lab Manager 9 Big data revolutionized the lab manager’s role—AI is about to do it again by Sridhar Iyengar, PhD the lab of the future: big data enables a big role for AI B uried in a working paper scribed in October 1980 by sociologist Charles Tilly was a consequential union—a marriage of two words forged out of necessity to describe a concept not yet named with repercussions not yet imagined. Such was the first recorded mention of “big data”—a phrase that would swiftly enter the common vernacular and become common practice across industries and geographies. To understand how data can and will be used to shape decisions in the lab, one must first understand what decisions lab managers need to make in the first place. That means maintaining frequent contact with techs and even the representatives of the machines themselves.” Luckily, Internet of Things (IoT) technology has enabled the collection of thousands of data points without human involvement. Today, sensors are embedded in new equipment, while legacy assets can be connected to the cloud via inconspicuous and easy-to-install sensors. Outfitting a lab to collect data for today’s needs alone is shortsighted. It’s imperative that those seeking to leverage data in the lab consider not only the expanded data pipeline of today, but the colossal one of tomorrow. A new era of science means new decisions for lab managers Artificial intelligence requires operational excellence Ten years ago, the titles of those who supported a lab’s operations were similar to today—technicians, lab managers, and IT managers. Yet, the responsibilities under their purview and the challenges associated with them have changed drastically in the decade since. Today’s scientists don’t just need their equipment to be operational; they need it to be transformational. Researchers now expect their tools to act as both collectors and reporters of data. To empower scientists with the data they require, operations professionals are now presumed to be experts in cloud infrastructure, data security, and encryption. As for the assets under their jurisdiction, many were manufactured before the internet was even established. The questions answered with data today will be asked by artificial intelligence (AI) tomorrow. Yesterday’s executive hypotheses are today’s data-driven plans and tomorrow’s fully automated discoveries. In the not-so-distant future, robotics will handle automation as AI evaluates protocols. Eventually, discovery will require little to no human involvement at all. But as Lily Huang, associate scientist at Pliant Therapeutics, explains, the initial impact of AI will be a welcomed one: “Many professionals might be worried about robots and AI leading to a high rate of unemployment for manpower-based jobs. I personally think that machines, especially smart machines, will take the boring tasks away from their human counterparts. AI technology has the potential to assist daily operations in the lab as well as facilitate the improvement in various processes. If well designed and executed, AI is able to identify process flaws and procedure redundancy, in addition to catching operational defects and optimization opportunities.” As the tidal wave of data crests, some researchers are still recording measurements on paper, manually transferring their notes to spreadsheets, and individually exporting spreadsheets into databases for processing and storage. If such habits are antiquated today, they’ll certainly be detrimental tomorrow. Any remaining “if it ain’t broke” devotion to paper notebooks will break under the weight of a data-hungry, AI-shaped future. But eventually, so will manual collection of any kind. To be truly transformative, AI requires input from mass quantities of data. Its collection must be copious, reliable, and automatic. Such widespread collection requires universal connection of every asset, every metric, and even the lab environment itself. IoT technology was born for such a time “Today’s scientists don’t just need their equipment to be operational; they need it to be transformational.” “I’ve definitely seen a paradigm shift,” says Russell Lund, facility manager at Zai Lab in Menlo Park, CA. “A lab manager needs to intricately understand every piece of equipment—what each does, why it does it, and what to do if it goes down.” Such growing responsibilities give lab managers a litany of new decisions. How can we draw new insights from old equipment? How is our data encrypted? How do we get data into the right hands with ease and out of the wrong hands with veracity? As Lund describes, today’s lab manager role is highly technical: “I have to ensure that the computer is talking to the machine and the data is being stored properly. October 2021 Lab Manager 11 the lab of the future: big data enables a big role for AI as this. “We were recording data by manually handwriting in a spreadsheet twice per day,” explains Joanna Schmidt, lab manager at Ionis Pharmaceuticals. “Since installing an online system, we can see all temperature changes of all freezers over time on one page. I’m moving users to underutilized freezers to help increase the lifespan of the units.” Some growing pains remain While most recent laboratory equipment on the market comes with cloud connectivity embedded, vendorspecific solutions solve one problem while creating another. Data is siloed into superfluous and clunky dashboards, rendering it all but useless to those who need it. Meanwhile, according to internal research by Elemental Machines, an estimated 300 million assets aren’t yet connected to anything. Most are fully operational and widely familiar (balances, centrifuges, freezers, etc). But thanks to turnkey IoT sensors and vendor-agnostic cloud solutions, the world’s unconnected assets will live on and live as one. Rather than being sidelined in favor of connected equipment, inconspicuous sensors enable seamless retrofitting in seconds. As such, tomorrow’s connectivity needs can be met while stewarding yesterday’s investments. “The organizations who will dominate market share tomorrow are those who prioritize data today.” In the lab, data maturity advances in reverse In most categories, maturity is a quality that comes effortlessly to the aged and arduously to the young— not so for data maturity. When it comes to data, today’s startups spring to life already pushing the boundaries of its collection, harnessing its insights, and leaning on AI to make sense of its root causes. Despite their bound booklets titled “Digitization Strategy” and secured rooms labeled “Lab of the Future,” titans of industry are challenged with wriggling their way out of longstanding practices, breaking free of tired infrastructure, and asserting their way to modern data practices over the objections of sometimes thousands of internal stakeholders. Inertia is real. Despite the unequal hurdles presented to startups and industry leaders, the importance of achieving data 12 Lab Manager October 2021 maturity in the lab remains imperative to both. The organizations who will dominate market share tomorrow are those who prioritize data today. Amidst the myriad models and guidelines for data maturity in other sectors, practical handrails for leveraging data in the lab are few and far between. As such, the following offers an outline of the five stages of data sophistication in the lab. Evaluate your organization’s standing using the information below. The Five Stages of Laboratory Data Sophistication Stage 1: Elementary • Asset data is available but siloed • Equipment data populates single-asset interfaces • Some assets remain unconnected • Accuracy is questioned • Access is cumbersome Stage 2: Irregular • Organizational data strategy plans are forged but confusing • Sensors are deployed for complete lab connectivity • Data is trusted but siloed either by seniority or asset type • Progress is stunted as data strategy is not fully prioritized Stage 3: Championed • Data strategy and vision are formalized, adopted, and concise • Lab director champions the use of data and analytics • Algorithms detect and alert of anomalies • A single universal dashboard enables access to all data anytime, anywhere • Primary and secondary data are integrated • Humans remain integral to analysis Stage 4: Committed • Lab director and company executives fully buy in to organization-wide data and analytics strategies • Data informs business decisions and lab activity alike • Data and analytics are viewed as a key component in driving lab innovation • AI details the root causes of reactions, anomalies, and errors, and predicts those to come Stage 5: Transformative • Data and AI are central to discovery • Discoveries are fully automated without human involvement LabManager.com the lab of the future: big data enables a big role for AI • Robotics handle automation and AI evaluates protocols and results automatically • Utilization data informs all purchasing decisions in the lab and across the organization • A chief data officer maintains a seat on the board For now, achieving a “transformational” level of data maturity may sound like a lofty goal and a clear competitive advantage. But a day is coming where it will be essential for survival and thus become the status quo. Thanks to IoT, AI, and organizational prioritization of data maturity, the lab of the future is coming into focus. Charles Tilly likely had no idea in 1980 that his casual declaration of big data would eventually become sacrosanct. Lab managers had little indication of how quickly assets would measure themselves. But for anyone willing to listen, every indication is that AI will fulfill the promises enabled by big data. For legacy scientific and research enterprises, mature handling of data will determine whether their reign continues or ends. For emerging players, data maturity could be their ticket to disruption. The lab managers enacting the automation and optimization of data collection within each will maintain a place in history as the linchpins who enabled discoveries long elusive. The future of the lab is bright. Sridhar Iyengar, CEO and founder of Elemental Machines, is a serial entrepreneur in IoT, medical devices, and wearables. Iyengar was a founder of Misfit, makers of elegant wearable products acquired by Fossil in 2015. Prior to Misfit, he founded AgaMatrix based on his PhD research, a blood glucose monitoring company that made the world’s first iPhone-connected medical device. Iyengar holds more than 50 US and international patents and received his PhD from Cambridge University as a Marshall Scholar. We love to speed things up. Productive pipetting from 1 to 384 channels. We accelerate science together. To fulfill this mission, we develop the most precise and easy-to-use pipettes for labs all over the world. www.integra-biosciences.com labs less ordinary The Data Science for Social Good Lab RESEARCHERS STRIVE TO IMPROVE THE WORLD THROUGH BIG DATA by Lauren Everett A fter finishing his postdoc studies at the University of Washington, where he was the recipient of the Moore/Sloan Data Science Fellowship and the WRF Innovation Postdoctoral Fellow in Data Science, Michael Fire envisioned building a lab “dedicated to solving real-world problems using open data and data science tools across different domains, with an emphasis on making social good,” he explains. After becoming an assistant professor in the Software and Information Systems Engineering Department at Ben-Gurion University of the Negev (BGU), Fire “made good” on his vision, and founded the Data Science for Social Good Lab. “Since then, thanks to data science's growing popularity, our lab has rapidly grown. The lab currently has over 20 members that conduct active research encompassing a wide range of research domains,” says Fire. The team’s work indeed covers a variety of real-world issues and challenges, including inequality and diversity, public health, smart cities, and sustainability, to name a few. Specific projects range from investigating gender biases in clinical trials, to developing an approach to monitor palm 14 Lab Manager October 2021 trees for insect infestation, to analyzing global dietary habits and the linked economical effects—all of which are driven by collecting and analyzing big data. One of the team’s most recent endeavors, a collaboration with Dr. Talia Meital Schwartz-Tayri, of the university’s social work faculty, aims at helping at-risk youth “by utilizing historical data from documented records of governmental family services to identify factors that influence their life for the better or worse,” says Fire. “For example, historical records can be used to better predict the types of help services that are more likely to positively impact their lives.” Fire and fellow leaders of the lab, Galit Fuhrmann Alpert, PhD, and Dima Kagan, a PhD student, explain that the large amounts of data they collect for their projects can either be structured—meaning large tables with billions of records— or unstructured—texts, images, and sounds. “To analyze different data types, we use state-of-the-art data science tools to manipulate the data and extract information,” says Fire, Fuhrmann Alpert, and Kagan. “For example, in our recent work with the Palm Trees Infestation, we LabManager.com labs less ordinary used deep learning algorithms to automatically detect palm trees in Google Street View Images.” The team can carry out these data-intensive projects thanks to the lab’s numerous robust high-capacity servers. The lab also has access to university high-performance computing clusters. Amazon Web Services and Google Cloud are also used when needed. Free access for all The Data Science for Social Good Lab openly shares its data and codes on its website, in an effort to help other researchers across all types of disciplines with their studies. Examples of public large-scale datasets featured on the site include online social network datasets, such as Facebook, Google+, Academia.edu, and Reddit Communities, as well as time series datasets, and the largest public network evolution dataset, with more than 20,000 networks and a million-plus real-world graphs. To the layman, the concept of big data can sound overwhelming. So, in addition to sharing data and codes with fellow scientists, the lab team also makes it a priority to connect with the general public. “We do our best to communicate our research to the public by creating short videos, infographics, and publishing blog posts. By doing this, we hope to increase awareness of issues that we believe are important. Our tools and code are highly transferable to different fields, and we hope will be used by the broad community,” says the team. Sharing knowledge with the next generation While the lab’s capabilities to collect, analyze, and share massive amounts of data for social good is impressive enough, “the human capital is what makes our lab unique,” says Fire. “We have a fantastic group of researchers from very diverse backgrounds.” Fire brings his background in computer science and theoretical mathematics to the team, while CONCEPTION ■ INTERPRETATION ■ PRODUCTION ■ SATISFACTION The PLAS■LABS’ 840-Series “Powder Handling Isolator” is a completely sealed, double HEPA filtered, closed-loop containment isolator. It features a door inter-lock system for safety, anti-static ionizer, and front access door. Observed containment level: <1.0 nano gram / cubic meter. Anaerobic Chambers Powder Handing Isolator The PLAS■LABS’ advantages include: ■ Optically clear one-piece top with rounded corners and complete 360° visibility. ■ Complete customization is available. ■ Over 50 years of servicing the scientific community. ■ Completely sealed for lower gas consumption. ■ Bright white one-piece bottom with rounded corners for easier cleaning. Isolation & Containment Glove Boxes ■ PLAS■LABS partners with global research facilities and laboratories to develop the latest products in isolation and containment glove boxes. ■ 2-YEAR WARRANTY (not on consumables) PLAS■LABS® www.PLAS-LABS.com PLI@PLAS-LABS.com Now Shipping from Europe HEPA Filtered PCR Chambers labs less ordinary 1. 2. 3. 1. The Data Science for Social Good Lab is located in the Carole and Marcus Weinstein Software and Information Systems Engineering and Cybersecurity Building. Credit: Dani Machlis 2. The Data Science for Social Good Lab's founding team. Front (left to right): Dr. Michael Fire and Dima Kagan. Back: Aviad Elyashar and Dr. Galit Fuhrmann Alpert. 3. The Software and Information Systems Engineering Department's servers cluster. Left to right: Dima Kagan, Dr. Michael Fire, Dr. Galit Fuhrmann Alpert, and Aviad Elyashar. Credit: Shay Shmueli Fuhrmann Alpert comes from the field of computational neuroscience, and Kagan has a strong background in software engineering. The diversity of expertise enhances the lab’s skillset and contributes to innovative problem-solving. As the lab team keeps growing, their ability to reach and advise students also grows. The lab offers three avenues for student mentorship for those interested in big data and relevant fields. Senior-year undergraduate students can find mentorship among the team for their engineering and research projects, and PhD and MSc students can receive help with their data science-related research as well. Most recently, Fire and the team developed a course that educates students on how to use state-of-the-art data science tools. “One of the lab's most important goals is to train students in the field of applied data science. For this purpose, we designed and are teaching a unique course titled ‘The Art of Analyzing Big 16 Lab Manager October 2021 Data—The Data Scientist's Toolbox,’" explains Fire. Currently, about 100 students enroll in the course each year, but the team hopes to eventually make the course publicly available to reach thousands more. Fire, Fuhrmann Alpert, and Kagan are witnessing first-hand how the field of big data research is gaining momentum, and will continue to make a positive impact on society. “Big data and data science are currently changing the world,” says the team. “For example, the Large Hadron Collider generates petabytes of data. Another example, the Gaia project, stores a large amount of data to map our galaxy. In these enormous piles of data, there can be things that will change the world and make our lives better, if we ask and study the right questions.” Lauren Everett, managing editor for Lab Manager, can be reached at leverett@labmanager.com. LabManager.com Get Lab Manager on the go. Download a pdf at LabManager.com business management How to Effectively Communicate with Non-Scientists LEARNING THE “LANGUAGES” OF OTHER DEPARTMENTS OUTSIDE THE LAB IS AN IMPORTANT COMPONENT OF BUSINESS SUCCESS by Sherri L. Bassner, PhD T he lab manager has many responsibilities involving the optimization and effectiveness of the laboratory, and its contribution to the success of the business. This holds true for labs that are the focal point of a business, as well as for labs that support a business with a different primary offering. While it is tempting to spend all one’s energy on internal lab issues, lab managers must recognize the critical importance of developing effective communication techniques and working relationships with functions outside of the lab itself. This article will summarize the reasons these communications are important, provide some methodologies for building those skills and relationships, and point out a few pitfalls to avoid along the way. Understanding all the roles of the business “The success of the lab itself depends upon the flow of support and information from the other functions, as well as the ability of those functions to capitalize on the output of the lab.” It is human nature to place more importance on skills and activities you know well versus those that you don’t know quite as intimately. An extension of this mindset is the tendency of managers of various business functions, including the lab, to feel that their function is central to the success of the overall business. The reality, of course, is that all business functions need to work smoothly and cooperatively for any business to be most successful. The success of the lab itself depends upon the flow of support and information from 18 Lab Manager October 2021 the other functions, as well as the ability of those functions to capitalize on the output of the lab. For this to happen to greatest effect, lab managers must develop skills to effectively communicate with the managers of those other functions, many of whom are not scientists or are scientists who do not have intimate knowledge of how the lab functions. The first step to learning how to communicate well with those outside of the lab is to spend the time to learn as much as you can about the other functions in the business. How does sales work? Manufacturing operations? Finance? Business management? What are their goals and objectives? What headaches do those managers often have to contend with? What keeps them up at night? Learn the “language” that other functions use to describe their work. Either ask to spend time with those managers to truly understand their function, or look for mentors or friends who can educate you. If this seems like a waste of time to you, ask yourself this question: How frustrated do you get when a manager from another function minimizes the challenges of the lab or acts as if the lab output is less important to the business? If you expect other managers to understand how the lab works, then you should put in the effort to understand how their functions work. LabManager.com business management Once you’ve gained an understanding of the workings and challenges of other functions, map the functions and output of the lab with the goals of the other functions. How does the output of the lab help sales meet their goals? What does manufacturing require from the lab for them to be most successful? How does business management view the contributions of the lab toward meeting overall business objectives? Once you’ve gained the ability to “see” the lab through the eyes of the leaders of the other business functions, you are better positioned to not only prioritize lab activities that will most effectively drive the business, but also ensure that those other business leaders see the contributions of the lab as vital to meeting their own objectives. A cohesive approach Let’s take the example of seeking to gain approval for a large capital expenditure related to a new instrument. It may be the need to replace an aging tool or the purchase of an instrument that would provide a new capability. While it is usually the role of business management to sign off on these investments, often the input from other functions will be required. A typical approach to justify the purchase might be to discuss the technical capabilities of the instrument and how those capabilities fill a critical need within the lab. The technical aspects are often of most interest to the lab, but leaders of the other functions need to hear how the investment will help them meet their own goals, too. The sales manager wants to hear what market segments she might lose if that capability goes away, or what new customers she might gain with the new capability. The manufacturing manager wants to hear how this capability will lead to quicker answers to production problems, more robust products to begin with, or how loss of this capability would otherwise negatively impact production processes. The business and finance managers want to understand how this investment will return more in profitable sales than the cost of the investment itself or how loss of that capability would impact profit margin or overall revenue. To make these arguments effectively, the lab manager must have a deep enough understanding of the other functions to be able to make specific and quantitative statements that tie this investment to the objectives of the other functions and the business as a whole—and to make those arguments in the language of those other functions, not the language of the lab. Another example is the cyclic setting of objectives and the related budgeting process aimed at achieving those objectives. The lab manager aims to set objectives that contribute to the overall success of the business and then requests resources required to meet those objectives. However, if the lab manager expresses the objectives only in the terms of the lab (technical objectives, what skills and capabilities are required, and what do they cost), the path to approval is a steep one. The challenge for the lab manager is not to simply connect a lab objective to a business objective, but to specifically describe how the lab objective will lead to the achievement of the business objective. To achieve this, the lab manager needs to explain how the successful completion of the lab objective enables the successful completion of the objectives of other functions and the business as a whole. Key to this process is specificity and quantitation, which requires the deep understanding of how the other functions achieve their objectives. Achieving support and appreciation for the lab If this sounds like a lot of work, it is. It is easy for the lab manager to cut corners and not do sufficient homework. Don’t assume that the other managers understand how the lab works, and constantly challenge your own understanding of other functions. Ask questions. Spell out acronyms. Work hard to see the business through the eyes of your management peers and never stop expanding on that understanding. Be prepared to teach others as often as necessary so that they gain understanding of the lab. The investment in mutual education will pay rich dividends in continued support and appreciation of the lab. Finally, remember to stay humble. As noted above, it is easy to fall into the trap of seeing the lab as the critical function around which the business revolves. Certainly, it is important, but there would be no business if the other functions did not work just as hard. All the functions of the business are interdependent. The reality is that most managers, of all functions, don’t embrace this concept. Remember to keep the overall objectives of the business as your primary touchstone and always discuss the needs and accomplishments of the lab in the context of those business drivers. If you, as the lab manager, can do that, you will always be positioned to best support the lab. Sherri L. Bassner, PhD, is a retired chemist and manager who spent 30 years developing new products and services, and then leading others in those same efforts. She is a part-time leadership coach and blogs on personal and professional development (among other topics) at www.sherribassner.com. October 2021 Lab Manager 19 asset management Optimizing the Utilization of Lab Assets ANALYZING DATA TO IMPROVE THE AVAILABILITY AND EFFECTIVENESS OF INSTRUMENTS AND EQUIPMENT IN THE LAB by Scott D. Hanton, PhD O ptimizing the usage of equipment and instruments in the lab is a key responsibility for lab managers. After people and space, ensuring working tools in the lab represents the next largest investment for most labs. Providing properly functioning instruments and equipment impacts both the capital budget— for new investments—and the operational budget—for repair, maintenance, and calibration. Optimizing the assets of the lab brings important benefits. Implementing a more efficient approach to optimizing asset management can help to reduce overall costs and generate greater productivity of the lab. “Optimized lab assets means you have the most productive mix of assets that are available, reliable, and performing the right tasks to meet your business goals,” says Melissa Zeier, enterprise services product manager at Agilent Technologies. “It is the responsibility of the lab manager to justify the cost of the laboratory asset life cycle to the business—from planning, acquiring, deploying, repairing, maintaining, and disposal of those assets while balancing risk to benefits.” Lab asset optimization involves investigating and monitoring a variety of different data about the instruments and equipment in the lab. Some of the data that is important to the optimization process includes repair history, maintenance schedules, calibration requirements, utilization history and expectations, operating costs, space requirements, asset life span, capital replacements, and disposal options. While labs track some or all of these data, most have a manual approach to recording the data, and few are really effective at analyzing these disparate data sets to optimize the availability, usage, and costs associated with their assets. “Manual methods 20 Lab Manager October 2021 of collecting data in spreadsheets or from logbooks can be time consuming and inconsistent,” says Zeier. “By having standardized, meaningful definitions of utilization, deploying the right technology to capture the data that fits that definition across critical workflows, and visualizing the data in a way that can translate to lab insights, lab managers are on their way to understanding current usage of lab instruments.” Having software designed to capture these data and help analyze it effectively can make a significant difference in the ability of lab managers to optimize the use of lab assets. There are options available now from several vendors that can enable more powerful tools to track and understand the usage and availability of lab assets. According to Jim Sweeney, senior product manager, PerkinElmer, “One approach is to have a software solution automatically capture utilization from the instrument, either through parsing of an instrument log file, or through a direct connection to the instrument through an application program interface.” Getting data about the lab instruments directly removes the need for staff to remember to gather these data during their already busy schedules, and provides an electronic record that is easy to share and document. When approaching a choice about the various tools now available to manage these kinds of data, it is important to understand the scope of the data that the tools measure and analyze. According to Joachim Lasoen, vice president of product BINOCS at Bluecrux, both visibility and optimization are critical for making the best use of lab assets. “Visibility helps lab managers understand instrument availability around maintenance and calibration schedules and the test demands on the instruments, and drives a LabManager.com asset management MINIATURE Solenoid-Operated Pinch & PTFE Isolation Valves capacity requirement profile for each instrument,” says Lasoen. Once lab managers have visibility on the data for their lab, they can begin to optimize the usage of the lab tools. Lasoen continues, “Two aspects determine the success of instrument utilization—maximize the white space between test runs, and maximize the test campaign fill rate.” Lasoen also adds that some of these tools are now using optimizers based on business rules and artificial intelligence to address more sophisticated workflows. Before implementing a tool to optimize asset utilization, it is important to understand the metrics that drive lab performance. “There are concrete steps that lab managers can take to optimize the usage of lab instruments,” says Zeier. “Start by prioritizing meaningful, standardized operational data for lab instruments across critical workflows.” Doing the hard work of standardizing the lab work process will enable the asset optimization tool to align the collected and analyzed data with the key metrics of the lab. “To help optimize lab asset management, managers should establish key performance indicators (KPIs) and assess them on an ongoing basis. These KPIs need to reinforce the important metrics for the lab,” says Carola Schmidt, global director of automated solutions at PerkinElmer. Using an asset utilization tool will help lab managers correlate the use of the lab instruments with the lab metrics. “By keeping a watchful eye on established KPIs, lab managers can pinpoint areas for improvement or prevent small issues from becoming bigger problems,” adds Schmidt. The use of asset management software tools makes this process much more efficient and useful. Another part of optimizing lab assets is to figure out which instruments and pieces of equipment are needed in the lab. Most labs tend to hang on to old or rarely used instruments because of the challenges in obtaining capital to purchase new ones. “Users of the lab assets often have an emotional attachment to some of the instruments,” says Sweeney. However, applying effective metrics and KPIs can overcome those emotional ties, especially when that data can demonstrate that the space, time, and effort to keep those instruments operating is not helping the lab deliver on its mission. An asset optimization tool can help lab managers perform a key function of lab management—making good decisions about the effective use of time, money, and effort to deliver on the lab’s mission. Zeier reminds us that, “Asset management optimization is central to maximizing the return on the investments that a lab manager makes in their operations.” Scott D. Hanton, editorial director for Lab Manager, can be reached at shanton@labmanager.com. 1 1 Pinch nch & Media Isolation Valves 2 Pneumatic P eumatic Pinch Valves 2 3 NEW! EW! “Cordis” Electronic Pressure Controls ontrols 4 NEW! EW! “Eclipse” Proportional Isolation Valves 5 NEW! “DR-2” Miniature Precision Regulators 3 6 Electronic Valves Ideal for Oxygen Applications Introdu cing More Precision Flow Controls 4 5 bility of Repeata ! ±0.15 psi 6 CINCINNATI • BRUSSELS • SHANGHAI 877-245-6247 • clippard.com leadership & staffing Creating an Inclusive Academic Research Culture HOW KEY LESSONS FROM MONOPOLY CAN BE APPLIED TO PROMOTE EQUITY AND LIMIT HYPERCOMPETITION IN ACADEMIA by Drs. Ane Metola Martinez, Claire Lyons, Katharina Herzog, Mathew Tata, Natalie von der Lehr, and Shruti Jain T he classic game Monopoly is often dictated by a set of highly variable “house” rules that can lead to heated words over the consequences of landing on “free parking.” These discrepancies inevitably favor some players over others, yet future games are doomed for failure as the rulebook remains unexplored, poorly understood, or simply does not provide regulations for a specific situation. Unfortunately, many careers in the academic sector share this predicament. Researchers are trained to perform science, but few are taught a strategy for a successful academic career. Much like the infamous Monopoly game, the academic career path follows an equally ambiguous set of rules and requires more than just rolling the dice. During its workshop series, “Improving Research Culture–Proposals & Discussions from the Science Community”, the National Junior Faculty (NJF) of Sweden discussed how to instill a more sustainable, creative, and inclusive environment for early career researchers (ECRs). Though discussed in the context of Swedish research conditions and politics, young researchers around the world face similar challenges and seek similar solutions. Just like in Monopoly, the problems that can arise from poorly defined house rules are universal. Time to rewrite the rulebook More and more researchers are seeking the opportunity to rewrite academia’s ailing rulebook. The sun needs to set on a research assessment system based primarily on journal metrics, where “bad winners” survive by targeting a portfolio of papers, rather than mentoring and supporting people. Researchers are implicitly encouraged to be 22 Lab Manager October 2021 individualistic, yet the length of academic careers is rapidly falling even amongst those who publish research articles as the lead author. Both international and national movements are raising the idea that embracing a different approach to research careers can foster a sense of inclusion that provides a place at the table for all of academia’s players. A more inclusive environment begins with a proper examination of the rulebook, so that researchers can eliminate discrimination against different individuals (such as women and minorities) by endorsing alternative measures of success, and reevaluating career step time limits. Valuation practices based on bibliometric measures and so-called research excellence, combined with greater competition for funding, have consistently replaced other considerations like novelty, reproducibility, interdisciplinarity, cooperation, and the societal impact of research. The hypercompetitive environment exacerbates the leaky pipeline of academia because it fails to provide support and training to valuable individuals who enter the game from a disadvantaged position. To ensure equity, educating ECRs on career expectations and forthcoming challenges needs to become a requirement for institutions—so that all players have the same chance of success. Mentorship and counseling can be important elements of this education; by recognizing their value, these activities are elevated from altruistic kindness to criteria for promotion. This helps to limit elusive house rules from excluding aspiring researchers, and diminish equity and inclusion. Another positive change would be to flatten research group hierarchy by including intermediate career positions that bring welcome stability and allow scientists to be creative. LabManager.com leadership & staffing Competing or playing together? Many have experienced a long, contentious Monopoly game that turned bitter and left us feeling like quitting. Unfortunately, this description accurately portrays how an increasing number of ECRs perceive an academic career. In any competitive game where obtaining resources and victories leads to further resources and victories, failing to score early makes recovery difficult. The snowball effect—where a successful player starts setting up hotels while others are still squabbling over railroads—is more apparent as the number of players in the game increases. In the present academic system, where resources and tenured positions are limited and not correlated to the increasing supply of PhDs, those who aren’t effectively educated around the rules from the start are quickly excluded. Additionally, in the research game, grant applicants are often disadvantaged by the Matthew effect, when funding is distributed disproportionately toward established scientists. Discussions during the NJF workshops gave rise to a number of possible solutions. Equitable rules for career development would encourage playing as teams (cooperation), rather than as individuals (competition), starting with improving the way credit is given The laboratory is patient care Your organization strives to provide high quality patient care CSMLS can help. With CSMLS certification, you know laboratory assistants and technologists have proven their competence to practice within the nationally set standards. Maintain the high standard so your institute and the public are guaranteed effective and accurate laboratory services. certifcationmatters.csmls.org leadership & staffing for contributing to publishing scientific data or conducting projects. ECRs were strongly in favor of separating funding pools and setting caps on what a single group leader can receive. For effective funding pools, inclusive considerations need to be made to avoid replacing one set of inequitable house rules with another, such as biological or academic age as eligibility criteria. Funding through more stable, institutional, or state funds could help shift away from a precarious and project-based funding culture, and randomizing funds at late stages of project evaluation can help counter bias and diversify the reach of public money. Constructive feedback from funding agencies and senior researchers would help those who fail to attract funds and make the process more pedagogical. The game should provide enough incentives for players to feel motivated to continue and enjoy the struggle of research, even if there are few winners. Not everyone will win the research grant or academic position of their dreams, but the joy of playing needs to be enhanced. It may mean the extension of “winning” to embrace and promote other scientific careers and pathways outside of academia, where ECRs can apply their knowledge and experience. Gaining knowledge by losing In Monopoly, the winner may not have acquired the most properties or executed the best strategy. Luck is simply part of the game. In academic research, winning is represented by gathering groundbreaking data, which leads to publications and funding. But what happens when your findings are considered negative, do not show any effect from an intervention, or go against the current accepted paradigm? These studies are difficult to report and are rarely published, leading to both a publication and citation bias toward positive data. This problem is compounded when fraudulent results are actively published and cited. The advantages gained from losing a game or obtaining negative data are increasing knowledge; for example, through publishing datasets or saving time and resources by teaching other researchers to avoid the same investigations. If used appropriately, negative results can demonstrate a lack of reproducibility and provide tactical value for future experiments. Sharing data and methods represents a core principle in science. Negative data needs to be fully understood, more widely accepted, and published. Journals dedicated solely to negative data are rarely successful—much like playing a game where nobody wins. The NJF workshop proposed calling all findings ‘data’, whether they are positive or negative, whilst recognizing 24 Lab Manager October 2021 that initial results shape a theory which needs to be tested over time. ECRs can benefit from the reminder that not every experiment leads to spectacular findings, much like Monopoly newcomers won’t win every round. “The game should provide enough incentives for players to feel motivated to continue and enjoy the struggle of research, even if there are few winners.” Alternatively, publications could be reviewed and approved at the planning stage, before data collection. PLoS has adopted this method in a preregistration stage where a research study is assessed based on its rationale and proposed methods. Upon journal acceptance, authors can rest assured that their results will be published regardless of the outcome of the study, thus increasing their willingness to publish data of any kind. More journals can adopt a similar approach to ensure that any findings are the result of robust methodology and statistical analysis. Like knowing how to play the game, one will feel a sense of inclusion while playing without knowing the outcome before starting. A different way to play During the workshop series, attendees were unanimous in calling for a change in attitude across academia: all stakeholders need to be more mindful of how research is performed, what results are sought, and which professional factors drive the contemporary scientist. This transformation must also begin with those in positions of power welcoming the perspectives and ideas of ECRs into academic governance. Only then can we end the monopolies of hypercompetition and discrimination on the research system, and set the board equitably for the current and future generation of players. Drs. Ane Metola Martinez, Claire Lyons, Katharina Herzog, Mathew Tata, Natalie von der Lehr, and Shruti Jain are all members of the National Junior Faculty of Sweden. LabManager.com REGISTRATION NOW OPEN SUMMIT.LABMANAGER.COM/QUALITYANDCOMPLIANCE Compliance Standards and regulations Laboratory operations Accreditation of ISO quality systems Validation MORE Lab Manager’s Quality/Regulatory Digital Summit on October 20-21 will feature expert speakers from various professional agencies, as well as seasoned quality OCTOBER 20-21, 2021 LEARN MORE managers, who will discuss important standards ranging from GxP and ISO and what they mean to lab managers and staff. The sessions featured in this virtual conference will provide lab managers with the resources they need in order to achieve maximum compliance for their labs, and SUMMIT.LABMANAGER.COM/QUALITYANDCOMPLIANCE will follow up with an audience Q&A after each session. UNLOCKING THE LAB OF THE FUTURE Universal data platforms empower laboratory operations and bring the lab of the future into focus L aboratory organizations that prioritize data reap short-term benefits and set the foundation for future success. The laboratory environment contains a potential wealth of data—including a variety of environmental parameters, as well as instrument and equipment metrics. While the evolution of the Internet of Things (IoT) has made it easier to collect this data, it must be transformed into actionable insights to benefit laboratory operations. The Elemental Machines ecosystem collects environmental, instrument, and equipment data, transforms it into usable data, and makes it accessible to laboratory managers. This powerful platform can improve productivity and reproducibility, optimize laboratory operations, and support the process of data sophistication—bringing the laboratory of the future into focus. HARNESS DATA TO DRIVE LABORATORY OPERATIONS Each laboratory organization consists of a variety of different roles, and individuals in every role face a unique set of challenges. The laboratory manager often has a diverse range of responsibilities and must balance planning, budgeting, problem-solving, and quality control, among a myriad of other tasks. Often, laboratory managers act as firefighters—springing into action to address problems as they arise. This is an inefficient approach to laboratory operations. A robust platform can transform a wealth of data into actionable insights, making it easier to shape strategy, reduce operational efficiencies, and maximize ROI. Solutions designed specifically to support laboratory managers combine alerting and monitoring with asset management, asset utilization, and quality assurance/quality control functions to improve laboratory operations. Asset management functionality supports the entire team by maximizing uptime, and decreasing costly delays and lost productivity. Real-time monitoring and alert functions improve visibility and provide invaluable peace of mind. Further, from a quality assurance/quality control perspective, deploying and monitoring autonomous quality checkpoints at consequential steps in manufacturing or research processes reduces waste and regulatory burden. Joanna Schmidt, lab manager at Ionis Pharmaceuticals Inc. shares how the Elemental Machines platform benefitted her laboratory. Using the monitoring functionality to continuously monitor the temperature of her laboratory’s ULT freezers, she was able to identify a problem and intervene before valuable samples were lost. “Without the long-term data, we would not have noticed the freezer’s bottom freeze point had shifted by almost 10°C over several months,” she explains. With the platform’s asset utilization functionality, she was also able to identify overutilized assets, and is “in the process of moving users to underutilized freezers to help increase the lifespan of the units.” in focus | Elemental Machines ACHIEVE DATA MATURITY TO ENSURE FUTURE SUCCESS By taking immediate action to break free of old infrastructure, longstanding practices that may no longer be effective, and addressing concerns from staff, laboratories will be better positioned to achieve data maturity. Working toward achieving the transformational stage of data maturity—as a new startup or established organization— will help to ensure a successful laboratory into the future. Discovery thrives in the transformational stage. At this point, data and artificial intelligence are central to new discoveries, many of which are fully automated. Robotics are used to automate manual tasks, and artificial intelligence is used to evaluate protocols and results automatically. It is also in this stage that utilization data can be used to inform better purchasing decisions. However, for artificial intelligence to enable these outcomes, it requires input from mass quantities of data pertaining to every asset, metric, and environmental parameter. IoT technology is essential for this purpose. A POWERFUL PLATFORM FOR A CHANGING LANDSCAPE The Elemental Machines platform drives laboratory operations and supports data maturity by capturing large quantities of data and making it usable and accessible to the right personnel. The platform combines a variety of sensors, powerful software, a cloud-connected dashboard, and reliable support. All data is consolidated into a single dashboard that provides monitoring, alerting, and asset utilization insights. It also facilitates asset management, data management, calibration and maintenance management, quality assurance, and quality control. A variety of turnkey IoT sensors and cloud solutions can be combined to create a complete monitoring solution for the laboratory. Temperature sensors enable monitoring inside ovens, incubators, freezers, and liquid nitrogen tanks; ambient sensors can be deployed to monitor humidity, air pressure, and light in the laboratory or micro-environments like vivariums; and equipment sensors are available for nearly every asset and metric, from blood gas analyzers to mass spectrometers and everything in between. All sensors are easily implemented without hardwiring or cables, connect nearly every asset regardless of manufacturer or era, and integrate with existing third-party electronic laboratory notebooks, enterprise resource planning, and laboratory information management systems. The IoT is changing the laboratory environment, and requires a powerful platform to transform large amounts of data into valuable insights. Not only can the right platform yield immediate benefits for laboratory operations, it can also support the ever-expanding data pipeline to ensure long-term success. The Elemental Machines ecosystem is designed to monitor the moment and inform the future. To learn more, visit: https://elementalmachines.com/ leadership & staffing we’re headed” in the lab. They define the why, what, and how of the lab’s work, and the focus of people across and beyond the network of stakeholders. Talented individuals and teams serve as active agents for the lab’s strategic agenda, as integrators and executors, makers and shakers, scouts and support crews, process wizards and progress teachers. People assume different roles, functions, and goals in strategic teams with assignments that are based on specific “talent blocks and beams” that connect a range of skills sets, surrounded by a series of experiences, behaviors, and perspectives. These weave together to influence culture and build strategy. Everyone in the lab feels the culture, and it prepares people to engage in the work to be done at every level. Culture shapes the casting of people in key roles across the lab, and the cultural agenda advances two practical elements that connect people and strategy in action: foundations—readiness, competence, and expressions—intentions and exchanges. Foundations The foundations of the cultural agenda are like DNA. They drive purpose, meaning, and scope and define what matters most. Foundations derive from core themes in strategic focus, value propositions, and value-based statements of standards and principles. Aspirations are driven by foundations. They provide touchpoints that reflect the lab’s purpose, vision, and mission. They are the grounding of the lab, the blueprint for the lab’s offering. Expressions Expressions of the cultural agenda are like conversations that convey what really matters, what effort and impact looks like. They define, inform, and persuade how people should think about their work and their relationships. Expressions are driven by the morning announcements, planning discussions, and feedback exchanges that communicate the cultural agenda. Culture provides the backdrop of attention. Managers use the cultural agenda to bring attention to key issues, behaviors, and efforts. They build on themes that support team engagement, learning, and advancement, with clear links to the lab’s cultural foundations. They reinforce values with examples and narratives that move people in their everyday thought and behavior. Culture is active and dynamic; managers work on and work through the foundations and expressions of culture. The culture conversation Many organizations today have “culture decks” that provide summary references on values, principles, and 30 Lab Manager October 2021 norms. These are often supported by graphics and images that contribute to the intended picture of culture and climate. Culture decks frame expectations and behaviors. They provide a general look at the aspirations of the lab, and they enable a more specific view of the language that the managers and strategic teams use to discuss the work to be done, working together, and the nature of the road ahead. These serve as statements that drive everyday conversations, reinforcing the foundations and expressions, supporting the strategic agenda for growth, performance, and change. Culture conversations are sparked by questions like: • Would you recommend your lab to others for employment, and why? • Would you share what success means to different people across the lab setting, and why? • Would you share how people work together to achieve strategic goals of the lab, and why that really matters? • Would you say that managers, staff, and teams follow the best intentions of the lab’s cultural agenda on a consistent basis? • Would you say that management is walking the talk—so to speak? • Does your view of the present and future look different than management’s?” Questions like these open conversations that connect staff to the strategy and culture. In the process, individuals and teams gain permission to engage in constructive debate about what matters most, and how to address strategic intentions through teamwork. Management connections Building the climate for lab excellence is an essential task of management. That task percolates, matures, and integrates through the work of strategic teams. The efforts of people serving on strategic teams drive the collective impact that managers promise to stakeholders. Culture is the intersection for people in motion, making things happen. Culture and strategy together, blended in the work of strategic teams, is the formula for excellence. Daniel Wolf is president of Dewar Sloan, a strategy and development group with extensive ties in lab and technical markets. He can be reached at dwolf@dewarsloan.com. Lydia Werth is a research consultant with Dewar Sloan, focusing on strategic teams and communication models. LabManager.com ask the expert Data Management for the Entire Product Lifecycle THE RIGHT LIMS CAN HELP ORGANIZATIONS IMPROVE THE QUALITY AND SAFETY OF PRODUCTS, FROM CONCEPT TO CONSUMER Jacqueline Barberena is the senior director, Global Marketing and Product Management at STARLIMS. Q: How does a LIMS (laboratory information management system) improve day-to-day operations across an entire enterprise? A: A LIMS typically extends beyond laboratory data management. It is a comprehensive solution that manages data and helps with quality, regulatory compliance, and safety throughout the entire product life cycle. LIMS solutions can integrate with existing systems, and identify opportunities to improve processes so organizations can bring safe, high-quality products to market faster. Q: What are barriers associated with implementing a LIMS and how can they be overcome? A: The success of a LIMS project requires the creation of accurate laboratory workflows within the LIMS, and staff involvement to ensure everyone understands the benefits and will work with the system. Overcoming barriers and successfully implementing and deploying a LIMS requires: • A clear understanding of the business and user requirements. • LIMS workflows that match or improve existing workflows to enhance productivity. • A clear understanding of how proper data management contributes to organizational success, to name a few. Q: What type of infrastructure is needed to ensure the success of a data management solution such as a LIMS within an organization? A: I don’t believe a specific type of infrastructure needs to be in place for a LIMS to help an organization. Our customers range from completely paper-based start-ups, to large global enterprises that are fairly automated but lacking the latest informatics innovations. They can all benefit from a LIMS if it is properly implemented with the correct functionality and requirements to address the needs of the business. Q: How does “technical debt” occur, and how does STARLIMS address this problem? A: “Technical debt” essentially means that as a laboratory’s instruments, platforms, and software are updated and replaced, outdated systems are retired from use and may still need to be maintained—at a significant cost— to access data held in proprietary formats. New technologies may support digital transformation in the short term, but may result in technical debt five to 10 years later. STARLIMS has taken an evolutionary approach to technological development, so it can grow in parallel with the data requirements, formats, and requirements of laboratories taking on new analytical technologies and workflows. Q: What is on the horizon for STARLIMS? A: Looking ahead, to support customers on their journey, futuristic technologies are essential, including IoT, AI/AR, etc. For STARLIMS, an example of this is the Digital Assistant. This technology provides the ability to interact with the STARLIMS HTML5 solution using user voice. Customers can utter commands using the microphone, launch applications and KPIs, conduct hands-free workflows while away from desk, and build their own skills to meet individual business needs. The tool leverages advancements in AI and NLP (natural language processing), allowing the user to interact with the system using only voice. With continual and consistent product releases and innovations, STARLIMS will stay ahead of the technology curve. sponsored by October 2021 Lab Manager 31 lab design Designing for the Unknown FLEXIBLE LAB DESIGN PLANS ACCOMMODATE CURRENT NEEDS, FUTURE POSSIBILITIES by Jeffrey Zynda and Adana Johns W hat type of research environment is needed to support the development of technologies that will not exist for another decade? This was the exact challenge faced by the project team that designed the Integrated Engineering Research Center (IERC) at Fermi National Accelerator Lab in Batavia, Illinois. In the world of particle physics, advanced devices, hardware, software, and technology development for multinational projects such as the Deep Underground Neutrino Experiment (DUNE), laboratory planners and designers don’t have the luxury of asking researchers, “What do you need?” Often, there are not definitive answers. Researchers may only be able to share a concept for an experiment that will be funded and designed years down the road— perhaps as many as 20 years in the future. “Laboratory planners and designers don’t have the luxury of asking researchers, ‘What do you need?’” Physics and engineering laboratories like IERC often have unique needs, highly specific to equipment requirements and functional capabilities. With these kinds of ever-evolving constraints, the design of successful next-generation facilities demands a change in perspective and approach, starting with a robust and adaptable framework that can be augmented to meet the specific needs of today and the speculative needs of the future. 32 Lab Manager October 2021 A view into the laboratory space of the Fermilab facility. Credit Perkins&Will; Julian Roman and Thang Nguyen In contrast to life sciences laboratories—where the range of activities and needs can be reasonably predicted, and the type of flexibility can be anticipated—projectbased physics and engineering laboratory environments must speculate based on the trajectory of the science. To deliver a facility that will meet the needs of today’s known programs and provide future flexibility, one must first dive into the drivers of science and engineering. A modular approach At IERC, this process was based on programming around the “scientific use-cases” of project types that were planned on a 20-year horizon. The IERC is the first building at Fermilab that intentionally brings together multiple departments and capabilities to foster a cross-departmental and cross-divisional collaboration platform. From this perspective, a broad look at current needs and future potential created a strong set of guiding principles for the design of this unique facility. Rather than embracing the idea of flexibility—attempting to anticipate every future need and incorporating features that meet these speculative needs—the IERC takes a markedly different approach in providing an adaptable framework that removes obstacles to future augmentation as new research and development needs emerge. During the course of reviewing more than 400 use-cases and determining the types of spatial support that projects might need—such as clean-class requirements, assembly capabilities, fabrication, equipment, and services—the LabManager.com lab design design team began to analyze the data to identify commonalities and distinct differences in capabilities. Based on the spectrum of use-case potential needs, the team developed a modular approach to space allocation and building systems. The outcome was a program that included clean-class fabrication space or project labs, core instrumentation and tool laboratories, and function-specific electronic fabrication laboratories, as well as adaptable dry-bench lab space for small electronic design and fabrication. The project labs were conceptualized as large workshops for the development and testing of novel technologies in support of Fermilab’s initiatives. Individual project labs are anchored by a central support “spine” that delivers critical service needs such as power, laboratory gas (nitrogen, CO2, compressed air), fiber-optic data, and exhaust capabilities for specialty needs. Flanking either side of the support spine, individual project labs were designed with three generations of project support taken into account. Each project lab was designed to be ISO clean-class capable. Rather than installing expensive building infrastructure that may never be used, space was set aside to add air-handling units, ductwork, and HEPA or ULPA filtration units. This ability to construct for the known needs of today and in the immediate future controls cost while providing the means to adapt the facility to future requirements. The ground level of the IERC has been designed to facilitate fabrication for large-scale project needs, expressed in a series of project laboratories. Overhead cranes were provided to utilize these spaces for the fabrication, assembly, and movement of large-scale detectors and vessels, such as dilution refrigerators. Each project laboratory is designed with utility service panels in the perimeter walls providing power, data, compressed air, nitrogen, and system-process chilled water on an 11-ft. module. Service distribution trenches are provided lab design The Liquid-Argon Cube Laboratory will test detectors that are destined for the “far-site” in Sanford, North Dakota as part of the Long-Baseline Neutrino Facility. Credit: Perkins&Will; Julian Roman and Thang Nguyen in each laboratory to enhance delivery to equipment, instrumentation, and workbenches, all while eliminating tripping hazards and allowing the end-users to readily access services on an as-needed basis. First signs of success While the true test of this level of adaptable design and planning will come when the IERC opens in 2022, its approach to adaptability has already been tested during the design process. After the preliminary design phase of the project, the project team learned of significant programmatic changes to accommodate new DUNE-related initiatives and emerging technology developments—which required little to no re-design of the building. Some simple re-configuration of utility requirements and specific instrumentation accommodation met the new program needs, underscoring the value of this adaptable approach and its potential to support generations of unknown research needs. The project team developed a toolset of “core capabilities” to support the development of future projects and eliminate needless duplication of resources. Programmatically, this was aptly named Shared Core Lab and provides the ability to support common needs across the spectrum of 34 Lab Manager October 2021 project labs, such as coordinate measuring machines, wafer fabrication tools, and similar commonly shared equipment assets. To support the widest range of known requirements today, these tools are housed in an ISO 7 clean-class environment that is future upgradable to ISO 5. “Researchers may only be able to share a concept for an experiment that will be funded and designed years down the road—perhaps as many as 20 years in the future.” Today’s researchers, including those at Fermilab, are working to deepen humankind’s understanding of the universe so that scientific discovery can advance our global society. Buildings like IERC have the potential to set an example for how architecture—and specifically, the thoughtful design of physical spaces for scientific inquiry—might support and advance these altruistic goals. Jeffrey Zynda is principal, Northeast regional practice leader, science and technology; and Adana Johns is associate principal, practice leader, science and technology; both with Perkins&Will. LabManager.com product in action INTEGRA MINI 96 PORTABLE, PRECISE, AND AFFORDABLE PIPETTING OF 96- AND 384-WELL PLATES The INTEGRA MINI 96 is an ultra-compact, lightweight, and portable 96-channel pipette, offering high throughput and reproducibility for virtually any microplate based liquid handling tasks around your lab. LIGHTWEIGHT AND PORTABLE DESIGN TOUCH WHEEL-CONTROLLED GRAPHICAL INTERFACE The built-in carry handle makes it easy to move anywhere Large, easy-to-use touch wheel-controlled graphical in the lab, including inside laminar flow cabinets. The interface offers a selection of predefined pipetting tasks, pipette’s small size makes it easy to have two instruments or allows users to develop custom workflows. 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Discover the most affordable 96-channel pipette on the market at www.integra-biosciences.com To learn more, visit www.integra-biosciences.com |22 Friars Drive Hudson, NH03051 USA October 2021 Lab Manager 35 lab design WINNER 2021 A Beacon for Life Sciences UNIVERSITY OF MICHIGAN BSB WINS EXCELLENCE IN INNOVATION PRIZE IN 2021 LAB DESIGN EXCELLENCE AWARDS by MaryBeth DiDonna T he University of Michigan has hosted a biological sciences program since the hiring of its first botany and zoology professor in 1884. The Kraus Natural Sciences Building was later built in 1915, followed by the Ruthven Museums Building in 1928. By the early twentyfirst century, however, the university realized that it would be better served by a modern biological sciences building that could accommodate fast-paced research, as well as an up-to-date museum facility able to house a collection that is surpassed in size only by the Smithsonian Institution. “We wanted to create a facility that would attract talented researchers and students, and allow worldclass investigation to occur.” The resulting building—the Biological Sciences Building & Museum of Natural History—unites the University of Michigan’s biology departments under one roof, promoting interdepartmental collaboration and opportunities for researchers and the public to interact. The project broke ground in September 2015, and achieved occupancy in April 2019. At a cost of $261 million, it offers a highly visible, spacious home for the school’s natural history museum, earmarked by a magnificent mastodon display in the building’s soaring atrium. 36 Lab Manager October 2021 Views into the open labs from the atrium and bridge. Credit: Aislinn Weidele In recognition of their success in developing a building that combines science, research, and community-building, Lab Manager has awarded SmithGroup and Ennead Architects—the architect of record and the design architect, respectively, for the Biological Sciences Building & Museum of Natural History—with the Excellence in Innovation prize in the 2021 Lab Design Excellence Awards. SmithGroup additionally served as the laboratory planner, MEP engineer, structural engineer, civil engineer, and landscape architect for the project, and Ennead also acted as the interior designer. Science showcase The purpose of the Biological Sciences Building (BSB) was to transform the way science is conducted and communicated in the twenty-first century. Susan Monroe, capital projects manager for the University of Michigan’s College of Literature, Science, and the Arts, says that the main goal of this project was to unite the school’s Molecular, Cellular, and Developmental Biology (MCDB) and Ecology and Evolutionary Biology (EEB) departments. “We wanted to bring them together with neuroscience research and with the paleontology researchers. We wanted to create a facility that would attract talented researchers and students, and allow world-class investigation to occur,” says Monroe. “We wanted a facility that would foster collaboration and interaction. And we wanted a building that would engage the broader campus and public community to showcase LabManager.com lab design science and the exhibit collections in the form of a new Museum of Natural History.” The BSB is located on the University of Michigan’s central campus in Ann Arbor, on the site where North Hall and the Museum Annex Building once stood. The BSB serves as a “beacon” for the surrounding Life Sciences Neighborhood, where it acts as a liaison between the historic academic campus core and the developing life sciences core, and then continues on to the medical center campus to the north. The ground level of the BSB contains a main entrance to the atrium, along with striking exhibits and a café, to draw in the school community. The plaza-level Science Lawn connects the surrounding Life Sciences Institute and Undergraduate Science Building, and forms an outdoor gathering area. The project team decided to avoid the traditional design of insular blocks that appear in many other research buildings. Instead, they developed a plan that includes three articulated towers, joined by large atriums, to form a collection of research neighborhoods. These neighborhoods share certain collaborative spaces such as break rooms, conference rooms, and lounge spaces. The research neighborhoods also share open labs, flexible work spaces, lab support spaces, and core facilities such as imaging, aquatics, and plant growth. However, other amenities are spread across the three towers, encouraging research groups to travel to other neighborhoods and interact. The elevators are strategically placed in the center tower, to create an active zone of circulation. PI office space was reduced by about a third, in an effort to increase square footage for open lab and collaboration spaces. Promoting collaboration The project team utilized a social network mapping survey to document existing research collaboration, as well as desired future research collaboration, to Detect pesticide residue at trace levels (<10 ppb) while improving overall throughput Triple Quad GC-MS/MS (978) 535-5900 | salesinfo@jeol.com | go.jeolusa.com/TQ4000_LM lab design 1. 2. 3. 4. 1. The Biological Sciences Building at dusk is a beacon for scientific discovery. Credit: Bruce Damonte 2. Biodiversity Lab with transparency to atrium. Credit: Aislinn Weidele 3. The museum atrium houses remarkable mastodon skeletons, witnessed when you first enter the museum. Credit: Aislinn Weidele 4. Two-way communication with the Paleontology researchers. Credit: Aislinn Weidele 38 Lab Manager October 2021 LabManager.com lab design understand the depth of connection between building users and develop the best possible collaborative infrastructure. The planning team identified 21 themes/ sciences that could be co-located in areas by neighborhood. This included 19 wet lab neighborhoods and two computational neighborhoods, based upon compatible sciences but not necessarily different departments. “I think one of the fantastic formal recognitions that the team came to...is that this program could not be represented monolithically; that it would not lend itself to the superblock notion of the laboratory. The analysis showed some fairly discrete neighborhoods that could be developed, and really begin to organize into research neighborhoods,” says David Johnson, design and lab liaison, SmithGroup. “[It allows] people to recognize how engaging and charismatic science is, in that laboratories like fossil prep really become inside-out opportunities to engage the user community and to engage the public in the mission of science at the University of Michigan.” The university’s Museum of Natural History was previously housed in the Ruthven Building, but was “relatively unknown,” says Jarrett Pelletier, project designer, Ennead. “You'd have to know it was there; you didn't walk by it and see the museum, you had to sort of uncover it. While it was beloved, in its previous location it was hard to spot. The museum wanted to turn that around on its head and really make it a centerpiece for the design of the biological buildings and really celebrate those two interactions,” he says. The museum is co-located on three floors of the BSB alongside research programs, “so there's a sort of overlap. We chose to maximize all of the contact areas as much as we could in the design of the museum space, to encourage collaboration and chance encounters and really leverage the proximity of those two programs,” says Pelletier. According to SmithGroup and Ennead, museum memberships have tripled since the museum was relocated to the BSB. Inspired by the sciences The university’s natural sciences program was an influence on the design of the BSB, as well as its energyefficient strategy. Natural systems, native landscape, and stormwater management strategies are utilized to form an immersive environment surrounding the building. The labs embrace natural light to overcome the stereotype of the lab as a dark, dingy place. The labs are also designed to be free of barriers, to promote the well-being of the occupants, and to develop a sense of community via shared bench space. Holistic ventilation has resulted in lower energy costs, and also means increased occupant ventilation and enhanced indoor air quality. The BSB has received LEED Gold Certification. “We did a lot of things to reduce energy usage while supporting the health and safety of everyone in the building. The systems design really takes advantage of transferring and utilizing energy efficiently at every stage of the building operation through some key design decisions and strategies,” says Jeff Hausman, principal in charge, SmithGroup. “First, makeup areas are pre-heated with waste heat from the process cooling water loop, then the amount of air needed is reduced by the use of low-velocity chilled beams. Then, outside air is used to cool the highly utilized spaces, such as classrooms, offices, and the graduate student spaces, and then transferred to the labs as makeup air. Finally, the non-exhausted air is used to ventilate the linear equipment rooms. We are wringing every bit of energy out of the airside system to make the overall building as efficient as possible for an intensely used lab building. The energy use intensity for the building is actually below 100 kBTU per square foot, which is 70 percent better than a benchmark lab building from 2003, and met the AIA 2030 challenge when the building opened. The building is 30 percent more efficient than any code building is today.” Safety initiatives in the BSB include shared yet separate storage areas for chemicals and biologicals jointly used among research neighborhoods; fume hoods (including shared radioisotope fume hoods) that are housed in alcoves apart from human circulation; and the location of biosafety cabinets in lab support spaces, apart from general circulation areas. Each neighborhood in the BSB is outfitted with lab sinks, eye wash stations, and emergency showers. Desks are located away from open labs to reduce exposure. Passenger elevators and circulation areas are situated near faculty offices to avoid the laboratories, and separate service elevators accommodate the transport of chemicals, biologicals, and research specimens from the loading docks to the labs. “We think the building is really poised to help elevate science education in the future, and future generations,” says Pelletier. “And we think that's a great aspect about bringing all these programs together.” MaryBeth DiDonna, lab design editor for Lab Manager, can be reached at mdidonna@labmanager.com. October 2021 Lab Manager 39 IMPLEMENTING A DOCUMENT MANAGEMENT SYSTEM Working with a vendor to create a laboratory document control system D ata integrity requires vigorous adherence to protocols and meticulous record-keeping. Hand-typed dates and times no longer satisfy regulators and accreditation bodies. Digital options have dramatically evolved into sophisticated software platforms that track users, dates, procedures, and more. This means the platform itself does the record-keeping. Using such software now allows laboratories to meet and exceed regulatory standards. The current document management landscape is divided into two separate types of systems. Older systems have data fields for information entry, such as when files were reviewed or approved. Manual entry in these older systems puts your lab at risk of human error, because they rely on the word of the person who typed in the information. More modern systems directly track when those files are reviewed and approved. These newer, more sophisticated systems don’t even give users the option to manually enter data, which ensures built-in data integrity. Modern systems also allow teams to collaborate directly, automatically keeping track of versions. Although most documents required for accreditation and validation don’t change from year to year, it still feels like starting from scratch when paperwork is due. Document management software creates checklists to help identify what can be reused to prove compliance. Such platforms can also assign tasks to individual users, so everyone understands their responsibilities. These features will save you time and money. in focus | Softtech Health DEVELOPING A LAB DOCUMENT CONTROL SYSTEM Build a team First, identify stakeholders. Define all the users and assign them roles. Quality management software provider SoftTech Health suggests labels such as beneficiaries, drivers, supporters, or champions. Once the list of stakeholders is complete, choose the key players. These team members will brainstorm the requirements of the software and evaluate its delivery. Completing the project After deployment, evaluate the project. Ensure the acceptance criteria list is complete and the deliverables satisfied. Sign off on all contracts, and back up the documents and the system. Finally, announce the launch and send thank you messages. BEST FEATURES IN A DOCUMENT CONTROL SYSTEM A key deliverable is to understand the functionality you’re looking for, as well as the minimum functionality required. Define the scope of work First, define the purpose of the project—include why the software is needed. Your vendor must understand what your needs are—time management, cost savings, or regulatory compliance. Your entire team needs to understand the “why” for the new system now, not when they are trying to learn it later. Use the defined purpose to develop a list of desired functions and features, but also make a clear list of project exclusions. A wish list is great, but remove unrealistic items to avoid disappointment on both sides of the contract. Finally, create a list of acceptance criteria. Use questions with yes/no answers paired to items in the scope of work. This makes the project clear for both you and your vendor. Ultimately, it provides you with backup in case those criteria are not met upon delivery. Once this work-scope document is complete, circulate it to all team members. Getting buy-in early smooths the way later and helps your team look forward to the new system. Today’s sophisticated software systems help labs guarantee data integrity, while ensuring maximum user uptake with a user-friendly interface. For lab managers, it’s key to recognize which systems will safeguard their data integrity by providing automatic tracking rather than manual record-keeping on a computer. By following the simple best practices listed here, your lab can take proactive steps toward a successful software rollout. Managing the project As mentioned above, get a clear list of the vendor’s deliverables. If your software deployment falls behind schedule, you can keep the team and management updated. Software installations rarely happen overnight. Tweaks and updates are inevitable. If changes come up, discuss them with the team and ask for input. Meet the issues head-on and keep senior management informed. Training is a huge part of the management of the project. Deployment day is exciting, but also full of anxiety. Having excellent training helps ease deployment. Training should include real-world examples. Ask if the vendor has a train-the-trainer option—one or two team members receive in-depth training to provide on-site support to the rest of the team. To learn more, visit: https://softtechhealth.com/ For minimum functionality: • Vendor must migrate all your files into the system • Vendor to migrate your users into the system • A clear list of what the vendor requires before the launch Questions your vendor must answer in writing: • What training is included, how is it delivered, and for how long • What support is available and what are the response time guarantees health & safety PARTICIPATION IN SAFETY ACTIVITIES FROM STAFF AND MANAGEMENT IMPROVES SAFETY CULTURE by Tabi Thompson C onsistent safety activities have the potential to create a stronger safety culture. When lab management fully embraces these tools, the benefits can include decreased injuries, increased morale and productivity, and improved cost savings. How can safety activities contribute to a stronger safety culture? Consider this: Major League Baseball players practice similar drills as Little Leaguers. By turning the fundamentals into habits, professionals and amateurs alike can focus on more complex tasks. This lesson applies to all aspects of life, including a safe laboratory environment. The following safety activities are options for companies to consider implementing. These activities should be completed consistently with intention and recorded for the sake of accountability. Lab inspections Lab inspections help provide a baseline for lab cleanliness and serve to ensure that labs are safe for employees. By regularly inspecting a lab, the staff are encouraged to keep their space tidy and safe. Most workplaces already perform lab inspections, but how they are done can be just as important as simply doing them. Lab cleanliness requires time. Through inspections, lab managers can see first-hand that their employees require more time to attend to cleaning activities. An inspection checklist and inspector diversity can further improve lab inspections. It’s easy to only catch the most obvious offenses and miss smaller problems, which have the potential to become larger over time. Prepared checklists allow inspectors to inspect labs with greater consistency. Including a diverse range of employees on the inspection team (i.e., employees from all levels of the organization) can ensure that 42 Lab Manager October 2021 inspections don’t become routine, and regularly rotating the members of an inspection team can help spot problems other inspection teams overlook. Incident prevention tasks Incident prevention tasks (IPTs) are performed when an employee observes an unsafe behavior or condition and addresses or corrects the issue. For example, a common unsafe condition is water on the floor. If an employee observes this condition, they should immediately correct the condition by removing the water from the floor to prevent someone else from slipping and falling, which is “among the leading [cause] of serious work-related injuries and deaths,” according to OSHA.1 The key to preventing common—and sometimes more complex—incidents is to act immediately when unsafe behaviors or conditions are seen. Incidents cannot be prevented if employees assume issues will be corrected by someone else. All employees have the responsibility to speak up about, and get involved in, the site’s safety. Eventually, employees will observe and habitually correct risks when they routinely perform IPTs. IPTs should be performed by all employees within an organization to be effective. Involvement throughout the organization shows employees that safety is a priority, and it fosters a cooperative environment. Moreover, employees exposed to greater and more various risks should perform more IPTs than those with less exposure risks. Consequently, IPTs may offer a certain level of preemptive action when enough information is recorded. For instance, if there is a persistence of IPTs concerning ergonomic issues, the organization can be proactive in LabManager.com health & safety health & safety addressing future ergonomic issues by strengthening their existing practices, policies, or trainings. Also, if there appears to be a preponderance of issues recorded within IPTs over a shorter time period, lab managers may choose to focus discussions with their employees on specific hazard categories. Activity drift checks Over time, lab workers can, often unintentionally, start to perform an activity differently than the written procedure details. This “drift” from the procedure can introduce hazards when left unchecked. Activity drift checks (ADCs) provide an opportunity for lab managers to check in with their employees on activities with documented procedures they regularly perform. Regular review of how tasks are performed allows good things to happen. First, quickly catching unsafe drifts from the written procedure can prevent injuries from occurring. Second, drifts that result in increased safety or efficiency of the task may be added to the procedure to document and share best practices. Finally, the review process presents an opportunity to improve the lab safety equipment. ADCs work best when a lab manager observes an employee physically performing the task. The lab manager should simply observe the employee’s actions while comparing to the written procedure and make note of any differences, both safe and unsafe. Once the activity is complete, both lab manager and employee can discuss potential improvements. ADCs aren’t about assigning blame or getting anyone in trouble; they’re a learning opportunity and a chance to improve the safety of the lab. Organizational accountability Organizations can implement many safety activities, but they’re meaningless if no one performs them. Enacting a safer work culture to prevent common mistakes or injuries requires lab managers and site leadership to see the value in a stronger safety culture. Participation of everyone—at all levels within the organization—is required. Organizations that recognize and advocate for a work culture where nothing is more important than the safety of its employees and the communities to which health & safety they belong empowers its employees to act, support, and challenge one another to work safely. Frequency of safety activities How often do safety activities need to be done to form positive workplace habits? Habits are defined as “actions that are triggered automatically in response to contextual cues that have been associated with their performance.”2 For example, automatically addressing or correcting an unsafe situation (action) after seeing the unsafe situation (contextual cue). “Decades of psychological research”2 shows that repetition of an action in response to a consistent contextual cue leads to habit formation. Organizations can’t survive on safety alone, though. Consistency of activities is key, so setting a weekly or monthly goal for every employee can build slow, but steady, progression of safety habits. In a jaded world where employees frequently feel expendable, organizations can boost morale by prioritizing their safety. But improving the safety culture doesn’t just benefit employees. By effectively implementing safety activities designed to build positive workplace habits, organizations can decrease and prevent injuries and increase productivity, giving way to greater cost savings; a rare win-win scenario. Natural Instincts Supervision Self Team DuPont Bradley Curve In the 1990s, DuPont devised and implemented a model known as the DuPont Bradley Curve,3 which describes stages an organization’s safety culture must go through to progress toward a goal of zero injuries. These stages are: • Reactive: People don’t take responsibility and believe accidents will happen. • Dependent: People view safety as following rules. Accident rates decrease. • Independent: People take responsibility and believe they can make a difference with actions. Accidents reduce further. • Interdependent: Teams feel ownership and responsibility for safety culture. They believe zero injuries is an attainable goal. When applied in tandem with safety activities designed to build positive workplace habits, this system provides a guideline for organizations to follow to develop a stronger safety culture. A strengthened safety culture saves organizations money by avoiding and preventing injuries; and when organizations focus on safety, employees feel valued, leading to lower turnover rates from higher morale and productivity. However, organizations hoping to achieve the interdependence stage should make a critical distinction. Believing that zero injuries is attainable through a strong safety culture is not the same as attaining zero injuries by underreporting or changing what qualifies as an injury. A culture born from sweeping incidents “under the rug” harms employee morale, and will not prevent injuries or more serious incidents from occurring. 44 Lab Manager October 2021 REACTIVE DEPENDENT INDEPENDENT INTERDEPENDENT The DuPont Bradley Curve shows the four stages an organization’s safety culture should go through to progress: Reactive, Dependent, Independent, and Interdependent. As the relative safety culture improves the injury rate decreases. Credit: DuPont Sustainable Solutions The writer acknowledges Air Products & Chemicals and Evonik Industries as sources of inspiration for some of the best practices outlined in this article. Tabi Thompson is a former bench chemist with a BS in chemistry from Wittenberg University, who spent more than 15 years working in a variety of roles in chemical and pharmaceutical industries. Most recently, she apprenticed as a safety training coordinator at Evonik in Allentown, PA. There, she influenced the implementation of the Safety at Evonik program aimed at bolstering the safety culture as well as managing updates to the safety training program. Currently, she is a freelance writer, proofreader, and copyeditor in Bethlehem, PA. References: 1. https://www.osha.gov/walking-working-surfaces 2. Gardner, B., Lally, P., & Wardle, J. (2012). Making health habitual: the psychology of 'habit-formation' and general practice. The British Journal of General Practice : The Journal of the Royal College of General Practitioners, 62(605), 664–666. https://doi.org/10.3399/bjgp12X659466 3. https://www.consultdss.com/bradley-curve/#:~:text=The%20 DSS%20Bradley%20Curve%20identifies,and%20believe%20 accidents%20will%20happen.&text=Accidents%20reduce%20 further.,and%20responsibility%20for%20safety%20culture. LabManager.com 5-9 Boston Convention and Exhibition FEBRUARY Center | MA GET HYPED to connect • Nine scientific tracks: • Submit an abstract to present! • More than 250 exhibitors + • Innovation AveNEW for startups • Two keynotes: Carolyn Bertozzi • and David Walt • Early registration discounts • Special programming Learn more at SLAS.ORG/2022 SLAS.ORG/2022 | #SLAS2022 industry insights: synthetic bio A New Era of Protein Interaction Engineering NEW BIOENGINEERED PROTEIN DEVICES ALLOW NEAR-INSTANT RESPONSE TIMES, BUT HIGHLIGHT SYSTEM NEEDS by Rachel Brown, MSc I magine detecting and instantly counteracting an overdose through a micro in vivo device. Or an early detection system that warns of an impending heart attack based on trace biomarkers. Or a pill that can diagnose disease. New synthetic biology research out of MIT paints these seemingly science fiction scenarios as realistic in the not-toodistant future with a new approach to protein switches. The burgeoning field of synthetic biology has already gifted us with the incredible. Active applications of design advances in biocatalysts, protein switches, gene switches, and genome engineering tools include intracellular biosensor devices. Proof of concept exists for micro 46 Lab Manager October 2021 engineered biosensors that can be swallowed and wirelessly relay real-time detection of internal bleeding. To date, the field has primarily relied on lengthy and resource-taxing transcription and translation processes that take minutes, hours, or even days to respond to inputs. Applications requiring faster, near-instantaneous responses—like those relating to cell signaling or metabolism—require engineering fast protein-protein circuits with an eye to systems behaviors. This approach faces challenges relating to biological complexity and the unknown. How the field of synthetic biology advances from here depends on how these challenges are addressed. LabManager.com industry insights: synthetic bio ENGINEERING A PATH THROUGH BIOLOGICAL COMPLEXITY Biological complexity is a tricky beast—one that stymies progress in synthetic biology. Synthetic biology is a collision of biology, chemistry, and engineering that aims to engineer new biological functions and inform systems biology research. Fundamental to an engineering approach to programming biological functions and cell behaviors is introducing modularity—breaking down complex processes into manageable units that can be assembled, reorganized, and connected to existing endogenous functions. Engineering relies on predefined materials with predictable behavior, on-demand procurement, and foundational rules or models dictating how materials can be combined1. Establishing this baseline within biological systems is fraught with challenges. “The issue of biological complexity is frequently raised when assessing reproducibility of research.” Starting from nucleic acid design and regulation has resulted in impressive strides in the field. Genetic engineering was in full swing during synthetic biology’s formation and forms the base of early established abstraction levels: “DNA” manipulation, biological “parts” like proteins, “devices” assembled from parts, and “systems” from patterns of devices1. It is—to an extent— modular in form and allows engineered functions to be considered separately from endogenous functions. The wealth of knowledge of regulation networks that has built up over the decades has allowed for the engineering of sophisticated networks. However, starting a function with DNA transcription and translation slows down any programmed biological response, in part due to competition for shared cellular resources, which limits the applications of the technology. Establishing networks composed solely of protein-protein interactions speeds biological response time, but is difficult, according to Ron Weiss, MIT professor of biological engineering, electrical engineering, and computer science. Understanding how to design appropriate chimeric proteins and reliably predict the upstream and downstream interactions is still developing and will prove a major challenge to the field moving forward. It highlights the need for thinking of engineered networks as part of a whole. Weiss describes a current perspective shift, “I think a lot of our [early] thinking in synthetic biology, certainly mine, [was] ‘let's build a circuit and then put it into the cell, but without [fully considering] endogenous pathways.’” According to Weiss, improved understanding of the systems context around embedded engineered networks is critical to success in the field. While conversations on this need are as old as the field, Weiss draws a distinction between talking about it and investigating it deeply. Once synthetic biology and systems biology are better integrated, he believes that both areas will provide valuable insights into the other, “ultimately [paying] huge dividends.” While greater insights into systems biology will aid synthetic biology in managing complexity as research expands in scope, it’s possible that improved standardization will reduce it. The issue of biological complexity is frequently raised when assessing reproducibility of research2–4. But how much variability in results is due to inadequate standardization of methods, protocols, and measurements? While in-depth conversations around the need for improved measurements and standardization in biology—and across the sciences—have been ongoing for years3,5, correction in the research community has lagged2,6,7. Measurements of biological activity, for example, are often relative. This increases ambiguity in results across the field but becomes more urgent when involving engineering efforts. Jacob Beal, a senior scientist at Raytheon BBN Technologies, is part of the wave of researchers pushing for improved consistency. He believes that a considerable portion of the variability and unpredictability in results would be eliminated with improved standardization. “There's a huge amount of time and energy wasted just trying to recreate missing information about units, protocols, and designs,” he explains. He’s observed researchers waste “months or even years debugging tricky biological issues” that turn out to be instrument or protocol related that—once fixed—demonstrates “more systematic and predictable” biology than previously believed. Beal expects that once enough labs commit to a particular minimum information quality, reduced time and effort costs will instigate “a vast acceleration of the field.” A NEW APPROACH A new paper in Science describes an engineered protein circuit that uses reversible protein phosphorylation-driven interactions8. As Deepak Mishra, lead author and MIT October 2021 Lab Manager 47 industry insights: synthetic bio research associate in biological engineering, notes in a press release, this provides “a methodology for designing protein interactions that occur at a very fast timescale, which no one has been able to develop systematically.” The authors used a combination of endogenous and exogenous proteins to build complexity in a novel, reversible bistable toggle switch. Taking it a step further, they demonstrated its ability to control basic cell processes by tying the switch to cell division, successfully flipping on and off a yeast cell’s ability to bud by alternately exposing the yeast to two different chemical signals. Using endogenous proteins in the network, the authors created a more complex toggle than most others to date, with more dependencies. Weiss, senior author, hopes this demonstration of incorporating existing biological systems in device design will contribute to pushing the boundaries of synthetic biology, particularly when it comes to building complexity and drawing inspiration from existing sophisticated networks. The added layers and complexity in their toggle circuit prompted the authors to search the study organism for similar endogenous toggle circuits. So far, according to Weiss, regulatory network discovery has been limited by the streetlight effect, searching familiar areas for familiar topologies. The authors instead searched for a diverse array of—less optimal but potentially more evolutionarily probable—topologies that would achieve the same result. They found six. “We wouldn’t think to look for those because they’re not intuitive… This is a new, engineered-inspired approach to discovering regulatory networks in biological systems,” says Weiss. This marks a considerable step forward in designing protein circuit devices. The authors see immediate use in developing biosensors for environmental pollutants, particularly given high sensitivity to triggers. Future development of similar custom protein networks opens the door to a wide range of diagnostic capabilities. Similar networks can add complexity to the type of micro engineered biosensor mentioned earlier, suggest the authors. This could allow for detection of multiple biomarkers, such as those associated with cancer, neurodegenerative disease, inflammation, or infection, and changes in concentration over time9,10. There’s even a potential for immediate intervention. “You could have a situation where the cell reports that information to an electronic device that would alert the patient or the doctor, and the electronic device could also have reservoirs of chemicals that could counteract a shock to the system,” Weiss notes in the press release. 48 Lab Manager October 2021 There is more work to be done before realizing these potentials, both regarding the findings and within the field. Understanding the modularity of fusion proteins and signal strength for this sensor is key, says Beal. He also notes the work that remains to build consistent systematic libraries. And, of course, a better understanding of circuitry integration is needed to drive smart designs. Still, in a field with immense progress year over year, it seems that when standardization leads to reliable reproducibility, anything’s possible. REFERENCES: 1. Endy, D. 2005. Foundations for engineering biology. Nature 438, 449–453. DOI: 10.1038/nature04342. https://www. nature.com/articles/nature04342. 2. Coxon, C. H., Longstaff, C. & Burns, C. 2019. Applying the science of measurement to biology: Why bother? PLoS Biol. 17, e3000338. DOI: 10.1371/journal.pbio.3000338. https://www. ncbi.nlm.nih.gov/pmc/articles/PMC6605671/. 3. Vilanova, C. et al. 2015. Standards not that standard. J. Biol. Eng. 9, 15–18. DOI: 10.1186/s13036-015-0017-9. https://jbioleng.biomedcentral.com/articles/10.1186/s13036-015-0017-9. 4. Sené, M., Gilmore, I. & Janssen, J. T. 2017. Metrology is key to reproducing results. Nature 547, 397–399. DOI: 10.1038/547397a. https://www.nature.com/articles/547397a. 5. Plant, A. L. et al. 2018. How measurement science can improve confidence in research results. PLoS Biol. 16, e2004299. DOI: 10.1371/journal.pbio.2004299. https://journals.plos.org/ plosbiology/article?id=10.1371/journal.pbio.2004299. 6. Stark, P. B. 2018. No reproducibility without preproducibility. Nature 557, 613. DOI: 10.1038/d41586-018-05256-0. https:// pubmed.ncbi.nlm.nih.gov/29795524/. 7. Beal, J. et al. 2020. The long journey towards standards for engineering biosystems. EMBO Rep. 21, e50521. DOI: 10.15252/ embr.202050521. 8. Mishra, D. et al. 2021. An engineered protein-phosphorylation toggle network with implications for endogenous network discovery. Science 373, eaav0780. DOI: 10.1126/science.aav0780. https://science.sciencemag.org/content/373/6550/eaav0780. 9. Gibson, D. G. et al. 2010. Creation of a bacterial cell controlled by a chemically synthesized genome. Science 329, 52– 56. DOI: 10.1126/science.1190719. https://science.sciencemag. org/content/329/5987/52. 10. Duhkinova, M., Crina, C., Weiss, R. & Siciliano, V. 2020. Engineering intracellular protein sensors in mammalian cells. J. Vis. Exp. 185, e60878. DOI: 10.3791/60878. https://pubmed. ncbi.nlm.nih.gov/32420982/. Rachel Brown, MSc, science writer/coordinator for Lab Manager, can be reached at rbrown@labmanager.com. LabManager.com the big picture The BIG Picture TACKLING THE TOPICS THAT MATTER MOST TO LAB MANAGERS W hether creating a new lab facility from scratch or moving your existing lab to a new space, the process of setting up a working laboratory is a complex process. Depending on the equipment and other needs of your lab, it can take weeks after the initial move-in day to get fully operational. In this web series, we offer tips and solutions to some of the main hurdles of leading a new lab setup. To see this and other Big Picture series, please go to Lab Manager’s website: LabManager.com/ big-picture. The Big Picture is a digital series produced by the Lab Manager editorial team. Each month, the series features a collection of in-depth articles, expert insight, and helpful resources, covering a specific industry, trend, or challenge. To see the setting up a new lab and other Big Picture series, please go to Lab Manager’s website at www.labmanager.com/big-picture. October 2021 Lab Manager 49 ask the expert ASK THE EXPERT COMPUTATIONAL PREDICTIONS EMPOWER DRUG DISCOVERY by Tanuja Koppal, PhD Michelle Arkin, PhD Q: Can you share with us the goals of the ATOM consortium? A: The vision of the ATOM research initiative is to use ML and AI to bring together data from public databases and from pharmaceutical partners to perform multiparameter optimization on a drug target. Another aspect of the ATOM pipeline is to do automated experimentation. Nearly five years ago, the pharmaceutical company GlaxoSmithKline (GSK) and the national laboratories (Lawrence Livermore, Oak Ridge, Argonne, and Brookhaven) started re-envisioning drug discovery as a computationally driven approach. They realized that if we are going to do personalized medicine for a patient, we need to do it much faster, with fewer resources and a higher success rate. That’s where the idea of ATOM and using computational tools along with rapid experimental drug discovery came from. Our goal is to start with a drug target and a set of molecules that impinge on that target, along with a set of design criteria for the drug. The AL/ML models use that information to design new molecules in silico and virtually assess whether they meet 50 Lab Manager October 2021 Michelle Arkin, PhD, professor and chair of the Department of Pharmaceutical Chemistry and co-director of the Small Molecule Discovery Center at the University of California, San Francisco, talks to contributing editor Tanuja Koppal, PhD, about the growing applications of artificial intelligence (AI) and machine learning (ML) for automating chemistry, drug target optimization, systems-level modeling, and eventually for predicting if a drug is going to work in the patient. She discusses the vision of ATOM (Accelerating Therapeutics for Opportunities in Medicine), a public-private endeavor that she is working with, to transform drug discovery using computational tools. those design criteria. This is done iteratively until you get a set of compounds that fits the criteria well. Laboratory automation then enables automated synthesis and purification of those compounds and testing in biological assays of interest. The goal was to go from an identified target to a drug worth testing in animals in about a year. People used to say that’s crazy, but now they are asking, “what is it that you are doing differently from what everyone else is trying to do?” which shows how fast the field is moving. Q: How do the experimental and computational components work together? A: There are two kinds of computational models. Parameter-level models measure and predict experimental endpoints such as hERG channel activity, MDCK permeability, and more. There is a lot of data around those parameters that can be used to develop AI/ML models. The longterm goal, however, is to use systems level computation, where models can predict a “therapeutic index,” i.e., how safe and effective a drug is based on its on-target activity and toxicity, at predicted in vivo concentrations of the drug. What we can do right now is parameter level modeling and some amount of systems level modeling for pharmacokinetics. However, in the future we are looking to do mostly systems level modeling. We are also using transfer learning or matrix learning approaches to see how little data you need to understand a target based on what you already know about a related target. There are two reasons why we do experiments alongside computation. One is to make and test compounds to validate predictions and then use the compounds in “real” biology. The other goal is to make and test compounds in a chemical space where none exists. Data obtained from the new molecules that are designed, made, and tested, is fed back into the model, which continually updates itself and is self-correcting. We can do this intense computational work because we are working in collaboration with the national laboratories who have the biggest computers in the country. Human biology is very complex and drug discovery is a hard problem to tackle. If we crack biological problems using computational approaches, we can push our computational capabilities forward. LabManager.com ask the expert Q: What has been your biggest challenge so far? A: We ran into two main challenges with our first project. When we started with data that was collected a long time ago or over a long period of time, we found that the new molecules that we designed were consistent with the old dataset, but the data itself could not always be reproduced. Thus, we need ways to demonstrate that the data sets are robust and experimentally reproducible. Secondly, it can take several months to source and synthesize compounds to test. With computational design, you can have several different scaffolds that are not related to each other and making those compounds can take time. Hence, we needed flexible, robust, automated chemistry to support the computational chemistry efforts. These are both active areas of research. Q: How is ATOM different from other public-private partnerships? A: There are a few things that make ATOM different. One is the integration of computational and experimental data, and the other is the systems-based modeling. Most companies are working only on parts of the puzzle, such as finding hits against a particular target or improving the pharmacokinetics or therapeutic index of a molecule. Big companies do most of the work internally and small companies take on focused aspects with a vision of doing more. What it’s going to take is people sharing data and models, and groups becoming comfortable with finding ways to do that. One basic approach is data sharing with an honest broker who maintains that data and creates a model using all the data. Alternatively, each organization can make models based on its own data, and the models themselves can be shared and “federated.” Another differentiation is that ATOM products are all open science. The goal is to put all the models and data in public domain so people can use the models and continuously improve them. We intend to publish all the datasets, and be open about describing what we are learning, what works and what doesn’t, and developing best practices. We have more of an educational and sharing approach. Q: What are some of the trends that will likely help improve AIdriven drug discovery? A: People are developing automated ways to design chemical synthetic routes and optimize chemical reactions. Then there is parallel, automated chemistry; the slow step in automated chemistry is always the purification. We are also interested in selecting the initial inputs to the chemical optimization. DNA encoded libraries could be an amazing way to seed our initial design loop. These libraries include billions of molecules, and compounds are screened for binding to the target of interest. Machine learning can use a lot of the screening data that was previously thrown out due to its size and noisiness. We can use this data to design and predict better molecules that can then be tested. DNA encoded library technology is rapidly changing because of opensource collaboration with companies. Crowdsourcing the information helps advance the field. So, in a way, you are democratizing DNA encoded library screening and drug discovery using computational approaches. I am excited about AI for academic drug discovery and chemical biology (that is, using the compounds as tools to explore biology). Drug discovery usually requires lengthy and costly cycles of making compounds and testing them. If computational models in the ATOM pipeline can give us compounds with much better properties with less chemistry, we can learn much more biology and get closer to discovering new drugs. “Human biology is very complex and drug discovery is a hard problem to tackle.” Michelle Arkin is professor and chair of Pharmaceutical Chemistry at the University of California, San Francisco, and member of the Joint Research Committee for the ATOM Research Initiative. Her lab develops chemical probes and drug leads for novel targets, with a particular interest in protein-protein interactions and protein-degradation networks. Michelle is co-director of the UCSF Small Molecule Discovery Center, president of the board of directors (BOD) of the Academic Drug Discovery Consortium, member of the BOD of the Society for Laboratory Automation and Screening (SLAS), and co-founder of Ambagon Therapeutics and Elgia Therapeutics. Prior to UCSF, Michelle was the associate director of Cell Biology at Sunesis Pharmaceuticals, where she helped discover protein-protein interaction inhibitors for IL-2 and LFA-1 (lifitegrast, marketed by Novartis). Tanuja Koppal, PhD, is a freelance science writer and consultant based in New Jersey. She can be reached at tkoppal@gmail.com October 2021 Lab Manager 51 ELECTRONIC LABORATORY NOTEBOOKS product focus | electronic laboratory notebooks 52 Lab Manager SEMANTIC ENRICHMENT IS HELPING OVERCOME ISSUES ASSOCIATED WITH VAST AMOUNTS OF UNUSABLE ELN DATA by Aimee O’Driscoll P rior to the age of digitization, the norm in the lab was to scribble information in a notebook before storing said book along with hundreds or even thousands of others in stacks of boxes. With this traditional method of recording, there were obvious issues. Even if the correct notebook could be located among a sea of boxes, there’s no guarantee that the recordings would be legible. Plus, there was no practical way to compile similar or related data from multiple books. Enter electronic laboratory notebooks (ELNs). These make the lives of lab personnel infinitely easier by providing a tool to record, store, and analyze vast amounts of data. While ELNs have obvious advantages, they don’t offer the whole solution. As Gabrielle Whittick, project leader and consultant, The Pistoia Alliance, explains: “In theory, ELNs are easy to search and archive, and users can link samples, experiments, and results. In reality, this isn’t always the case.” Whittick goes on to say that because of how individual researchers work, the range of nomenclature used, and the variance of structured and unstructured data, search and retrieval doesn’t always deliver the most accurate results. But there are solutions to these problems underway. Here, we examine the pros and cons of ELNs more closely and reveal how semantic enrichment is helping bridge the gap between a slew of disorganized information and valuable, usable data. ELNs and their advantages and drawbacks ELNs have revolutionized the way in which laboratories operate. They allow users to input all data associated with their work, including material information, experiment equipment and conditions, and, of course, results. As Whittick notes, “ELNs are vital to how researchers work today, as a October 2021 digital solution to record and store data safely and securely.” They are also increasingly useful as collaborative tools, enabling researchers to share knowledge across organizations and with partners. Whittick reveals that the early focus of ELNs was to improve data capture by facilitating the transition from paper-based notes to digital inputs. Even with this component, there have been some issues. “Bespoke ELNs tailored to lab workflows are most useful, but ‘out of the box’ ELNs may not fit how a researcher works, which limits the benefits,” says Whittick. She also notes that if an ELN is not platform-agnostic, a researcher needs to be based in a lab to use it, and can’t utilize it from home or on the move. “ELNs are vital to how researchers work today, as a digital solution to record and store data safely and securely.” To overcome these issues and facilitate the changing way in which personnel are working, remote and mobile access to ELNs is necessary. Indeed, Whittick notes that digital-native researchers entering the lab in the early days of their career expect digital solutions to be accessible. While most of these challenges are readily solved, recording, storing, and accessing data is only part of the solution. There is also the issue of the usability of the data being accessed. With vast amounts of data input into ELNs, there can be challenges in compiling and sorting information such that researchers can easily locate and retrieve the data points they require. “Some captured experimental data are therefore locked in ELNs, and rendered unusable and unsearchable. This results in LabManager.com product focus | electronic laboratory notebooks duplicated experiments and time spent tracking down and wrangling data,” explains Whittick. Another problem arises with non-compatible ELNs. For example, partner organizations may use different ELN systems, which can actually end up creating more work for both parties. A large potential benefit of ELNs is the ability to collaborate, but this is stifled by issues of inefficient data extraction and system incompatibility. How semantic enrichment of ELN data can help The Pistoia Alliance is currently working on a large-scale initiative that is set to overcome many of the challenges faced by ELN users, dubbed the Semantic Enrichment of ELN Data (SEED) project. Whittick reveals that semantic enrichment of data includes enriching free text in ELNs with metadata for every relevant term from agreed ontologies. “It also uses dedicated ontologies for improved data management, incorporating additional data like attributes, mappings, and annotations,” she explains. “This creates relationships between ontology classes to help to describe and define them.” The alliance brings together more than a dozen large pharma organizations to contribute to the project. These include AstraZeneca, Bayer, Biogen, Bristol Myers Squibb, CDD, Elsevier, GSK, Linguamatics, Merck, Pfizer, Sanofi, SciBite, University of Southampton, and Takeda. The first phase of the project involved the development of new standard assay ontologies for ADME (absorption, distribution, metabolism, and excretion), PD (Pharmacodynamic), and drug safety, because there was a gap in existing ontologies. “These have now been added to BioAssay Ontology (BAO) and are freely available,” Whittick notes. “As a cross-pharma project team, we built new standards and added them to the key ontology BAO, and then used this in the semantic enrichment process.” The next phase of the SEED project is underway and aims to continue to make ELN data more searchable and usable. With metadata assigned to each relevant term, data can become readily accessible for future analysis. The aim is to develop a set of standards for ELN data structure across the pharma and life science industries. Among these, there is advocacy for the alignment with FAIR principles (findability, accessibility, interoperability, and reusability) as published in Scientific Data in 2016. ELNs are incredibly useful tools in today’s laboratories, but there are barriers to utilizing them to their full potential. Semantic enrichment is paving the way for users to be able to more efficiently extract data and enhance collaboration opportunities. As Whittick puts it: “In short, semantic enrichment unlocks the value of scientific data currently ‘trapped’ in ELNs.” Aimee O’Driscoll, BSc, MBA, has a decade of experience as a development chemist and is a seasoned science writer. She can be reached at aimee@aimeeodriscoll.com. FOR ADDITIONAL RESOURCES ON ELECTRONIC LABORATORY NOTEBOOKS, INCLUDING USEFUL ARTICLES AND A LIST OF MANUFACTURERS, VISIT WWW.LABMANAGER.COM/ELN October 2021 Lab Manager 53 LAB MONITORING SYSTEMS product focus | lab monitoring systems SCALABLE LABORATORY MONITORING SYSTEMS CAN HELP MINIMIZE RISKS—BUT COME WITH CHALLENGES by Aimee O’Driscoll I n the past, laboratory personnel had to simply trust that everything would run smoothly in their absence. Inevitably, things would go wrong, and detectable issues would be dealt with upon arrival at the lab. This could result in lost time and wasted resources. There was also the element of the unknown, as without monitoring you wouldn’t know, for example, how temperatures or humidity levels may have fluctuated overnight. Such changes could lead to sample degradation and unreliable results. Thankfully, modern laboratories have a wealth of options when it comes to monitoring systems. Scientists can remotely monitor experiments, receive real-time notifications, monitor the performance of instruments and equipment, and more. As Salvatore Savo, PhD, co-founder, TetraScience, notes, “The ultimate goal of a lab monitoring system is to provide peace of mind to lab operators who need them to keep samples safe and improve operational efficiency.” Monitoring has now become the norm and helps with not only ensuring the integrity of samples and products, but also with remaining compliant with industry standards and regulations. With huge corporations utilizing laboratory monitoring systems, this begs the question of how scalable these processes are. We look at the importance of lab monitoring systems and the challenges faced in implementing scalable systems. Scalable lab monitoring systems have many benefits to offer Laboratory monitoring systems can have a large impact on the integrity of work completed and often represent huge cost savings for organizations. For example, Savo explains, “By using a remote monitoring system, life science organizations can prevent significant material and financial losses that can have a serious impact on their ability to take a drug to market.” Joe LaPorte, director of Cold Chain, Projects, and Regulatory, PHC Corporation, notes that “the largest value comes from being able to determine when your critical products fall outside their measured parameters when nobody is around to witness it.” There is also the compliance component. Lab monitoring systems are often vital to proving the integrity of research, development, and production processes. “The best systems have audit trail capability to meet compliance requirements and provide a method for analysis to help implement best practices,” says LaPorte. Implementation of scalable systems presents challenges While small-scale systems are broadly implemented, as an increasing number of parameters are measured across facilities, there is demand for organizations to implement large-scale solutions. Aside from enabling comprehensive monitoring, they need to deliver other features such as synchronization of data, customizable alerts, and maintenance tracking. These systems are available, but there are some roadblocks. One of the biggest issues is the large amount of data that must be transferred and stored. Savo notes that larger systems must support a nearly unlimited number of data streams. There’s also the issue of compatibility as so many different types of equipment and systems must be integrated. To overcome these challenges, providers offer cloud-based systems that are instrument agnostic and have superior integration capabilities. LaPorte discusses reliability issues inherent in some systems, including dropped signals due to electrical interference or loss of internet connection, as well as human error problems such as failure to change or charge batteries in Wi-Fi systems. These issues are trickier to fix, but there is an understanding that while no system is infallible, the benefits certainly outweigh the risks. Aimee O’Driscoll, BSc, MBA, has a decade of experience as a development chemist and is a seasoned science writer. She can be reached at aimee@aimeeodriscoll.com. FOR ADDITIONAL RESOURCES ON LAB MONITORING SYSTEMS, INCLUDING USEFUL ARTICLES AND A LIST OF MANUFACTURERS,VISIT WWW.LABMANAGER.COM/LAB-MONITORING 54 Lab Manager October 2021 LabManager.com product in action Labconco Axiom Type C1 Biosafety Cabinet SAFE, FLEXIBLE, INTELLIGENT. THE MODERN BSC. The Axiom Type C1 BSC opens the door of possibilities for all biosafety containment needs you expect from a modern BSC. Inherent to the Axiom's design is Omni-Flex™, a convertible design with two exhaust modes. The recirculating Type A mode or fully exhausted Type B mode will address your changing needs and reduce the cost of operation in the process. The Chem-Zone™ worksurface clearly delineates a total exhaust area for safe chemical handling within the BSC. Powered by MyLogic™ OS with Constant Airflow Profile™ Technology, the intelligent Axiom keeps you safe and informed so you can focus on your work. SAFETY FIRST FLEXIBILITY LIKE NO OTHER The innovative features of the Axiom C1 The unique design of the Axiom C1 were designed with safety in mind. In allows for conversion between two fact, the Axiom C1 is safer than other different modes of operation—something BSCs—and with its unique features typically requiring two completely you can be assured that personnel and separate BSCs. This one-of-a-kind product protection remain the number- biosafety cabinet can operate in A mode one priority. HEPA supply and exhaust with recirculating airflow, then switch to B filters are at least 99.99 percent efficient mode for 100 percent venting when your (at 0.3 microns in size), providing a laboratory requirements change. The safe environment for both you and your easy conversion negates the need for precious samples. another BSC when your work changes. INTELLIGENT CONTROLS A bright LCD screen displays MyLogic OS, an easy-to-use interface that displays filter life, alerts, and alarms right at eye-level within the cabinet. Behind the scenes, the Axiom’s control system utilizes CAP™ Technology to continuously monitor and adjust enclosure airflow to keep users safe as conditions change. To learn more, visit: www.labconco.com/axiom October 2021 Lab Manager 55 NEXT-GENERATION SEQUENCING product focus | next-generation sequencing USING NGS TECHNOLOGIES TO UNDERSTAND THE IMPACT OF THE MICROBIOME ON HEALTH by Andy Tay, PhD T echnologies for DNA and RNA sequencing are crucial to unlock secrets held within our genome and transcripts that can be used to better understand biology and impact medicine. Sanger sequencing is traditionally being used to sequence oligonucleotide strands one at a time by capillary electrophoresis. While this method is still considered the gold standard for analyzing small numbers of gene targets and samples, next-generation sequencing (NGS) is quickly overtaking it. NGS, also known as massively-parallel sequencing, enables the interrogation of larger numbers of genes with high throughput and low cost per run. Continual improvements have also enabled NGS to capture a broader spectrum of mutations and be more accurate in detecting variants at low allele frequencies without bias. NGS workflow There are a few main companies providing instruments for NGS, but their workflow is similar. The first step is library construction where DNA or complementary(c) DNA generated from RNA is fragmented and bound to adaptors that have a unique molecular “barcode.” With this barcode, each fragment is uniquely labeled, and multiple samples can be pooled together to save time during sequencing. The second step is clonal amplification, where more copies of each DNA fragment are amplified via polymerase chain reaction. The third step is sequencing, where most instruments use optical signals to assess nucleotide incorporation during DNA synthesis. The final step is analysis. NGS to boost microbiome research The microbiome describes the interactions of microorganisms including bacteria, fungi, and viruses with their ecological environment, such as a human body. Such interactions can be further broken down into commensal, symbiotic, and pathogenic. A variety of bacteria resides in our guts and influence our health, such as through adsorption and secretion of metabolites. NGS has been useful for taxonomical identification and classification of the microbiome in different parts of our bodies, including the intestinal and respiratory tracts. Kasai and colleagues studied the composition of gut microbiota in Japanese subjects using NGS technology and found that there were significant differences in the bacterial species. For instance, there was higher bacterial species diversity in obese individuals. NGS technologies have also facilitated an extension of such research to evaluate the effects of probiotics to modulate perturbed microbiota. Suez and coworkers found that probiotics supplementation might be ineffective as resident gut bacteria can resist the mucosal presence of probiotics strains. Probiotics supplementation was only useful in a subset of individuals, suggesting that this is likely not a universal approach to influence gut microbiota composition and that personalized probiotics development should be further studied. Antibiotics can also significantly alter the microbiome and play a role in disease onset and progression. Using NGS technologies, scientists have experimentally identified bacteria species that are affected by antibiotics and how their absence correlates with changes in immunity and disease susceptibility. Specifically, researchers have found that the use of antibiotics can have negative impact on gut microbiota by reducing species diversity (causing loss of bacterial ligands recognized by host immune cells), changing metabolic activities and selection of antibiotic-resistant organisms that can cause recurrent Clostridioides difficile infections. Andy Tay, PhD, is a freelance science writer based in Singapore. FOR ADDITIONAL RESOURCES ON NEXT-GENERATION SEQUENCING, INCLUDING USEFUL ARTICLES AND A LIST OF MANUFACTURERS, VISIT WWW.LABMANAGER.COM/NGS 56 Lab Manager October 2021 LabManager.com how it works Cryogenic Preservation without Liquid Nitrogen AIR PHASE CRYOGENIC STORAGE CAN ELIMINATE THE NEED FOR COSTLY, HAZARDOUS LIQUID NITROGEN Q A Cryogenic preservation of samples and cells can be costly, dangerous, and cumbersome. The handling of LN2 tanks can be challenging and bog down laboratory workflow. Ensuring that your inventory has appropriate temperature preservation at the cryogenic level can be critical. While it does indeed offer excellent long-term storage capability, liquid nitrogen can be dangerous to work with and requires additional investment. Safe and economical air phase cryogenic storage without liquid nitrogen Consider the benefits of mechanical cryopreservation. The PHCbi brand MDF-C2156VANCPA offers tight temperature uniformity at -150°C, +/- 5°C, and can eliminate consumption of LN2. This small footprint cryopreservation model can accommodate up to 165 two-inch boxes and leverages standard 220V power requirements. Using this air phase storage system lowers total costs of ownership through reduced energy usage, lowered reliance upon LN2, and decreased safety concerns. To learn more, visit: https://www.phchd.com/us/biomedical/preservation/ultra-low-freezers/mdf-c2156vanc October 2021 Lab Manager 57 PCR product focus | pcr LEVERAGING DIGITAL PCR TO IMPROVE DETECTION OF VIRAL PATHOGENS IN WASTEWATER by Brandoch Cook, PhD A lthough qPCR sounds quantitative when you say it (it’s in the name!) and looks quantitative when you analyze the results, its potential for accuracy, sensitivity, and dynamic range lags well behind that of digital PCR (dPCR). There are several limitations to any traditional PCR platform, either in endpoint or real-time assays. One example is that exponential amplification always produces copy numbers in multiples of two. Another is that target gene expression must be derived by comparison to a standard curve generated by amplifying a reference gene. Twofold measurements offer a disconnect from reality, and normalizations to housekeeping reference points can assume incorrect kinetics of amplification. Therefore, qPCR is an inadequate technique to achieve some highsensitivity objectives, such as measuring copy number variants of disease biomarkers, or identifying rare point mutations against an overwhelming background of wild type allelic expression. Alternatively, dPCR provides a substantial upgrade by detecting single molecules, quantifying their abundance, and obviating the need for generation of standard curves, which can consume excess time and reagents and introduce amplification biases. With increased sensitivity and accuracy, dPCR can additionally be applied to cataloguing water-borne microbial pathogens refractory to traditional methods, and therefore accelerate and validate crucial use and recycling decisions. Digital PCR: Enhanced sensitivity and accuracy through partitioning Work by investigators, including Kary Mullis at Cetus Corporation, in the early days of PCR enabled detection and amplification of a single copy of the λ-globin gene. Their approach was enhanced by Pamela Sykes and colleagues to allow copy number quantification, in a procedure first referred to as digital PCR by Bert Vogelstein and Kenneth Kinzler. The critical step Vogelstein and Kinzler contributed was using oil emulsion to maximize separation of individual PCRs into minimized volumes. By partitioning identical reactions into thousands of tiny individual microreactors, one can treat them simultaneously as a population, with a demographic distribution of on/off (or digital) signals corresponding to starting material with one or zero target molecules. Signals in this case consist of emitted fluorescence via accumulation of a TaqMan-style probe. Although each individual readout is analogous to what emerges from a larger single-well qPCR, dPCR has an endpoint readout, instead of a contemporaneous threshold cycle that varies between samples. To generate quantitative data, dPCR employs several assumptions and statistical conditions: 1) each partition begins with an equivalent, random probability of containing target molecules; 2) all partitions have the same volume; and 3) one can therefore use binomial probability and Poisson distribution to extrapolate absolute numbers of independent “events” occurring at a constant rate during a fixed period. Because of these relationships, there is an optimal partition occupancy rate, λ, 58 Lab Manager October 2021 LabManager.com product focus | pcr that drives considerations, including partition number and volume that can impact the dynamic range and accuracy of dPCR. For example, the Wilson method of direct calculation incorporates the probability that a partition is empty, the total number of partitions, and a confidence interval of 95 percent. In this algorithm, a λ of 1.6 is optimal for an assay with 10,000 partitions and corresponds to about 20 percent vacancy. Optimized thusly, dPCR can detect variations within a linear range of less than 30 percent, an obvious improvement over the classic two-fold limitation. However, deviations toward much lower or higher occupancy can skew accuracy, and bracketing an assay’s median intrinsic dynamic range promotes the highest fidelity. One way to ensure this is to develop dPCR partitioning strategies that allow for different volumetric ranges across subsets of partitions, with larger volumes promoting sensitivity, smaller ones enabling optimal detection limits, and medium volumes for precision. Finally, the incorporation of microfluidic devices into dPCR workflows adds an aspect of massively parallel throughput that can diversify analytic potential and improve accuracy by reducing pressures on expense and reagent use to allow unfettered reiteration of technical replicates. “While bacterial pathogens grab many of the headlines, waterborne viruses can be silent killers because they often occupy wastewater at levels below facilitative thresholds of detection.” Leveraging dPCR to characterize and solve wastewater problems In developing nations, there is often economic pressure to mitigate water waste through reuse. There are analogous pressures in historically privileged areas newly plagued by drought or population influx to conserve household, commercial, and municipal waters downstream of their initial use. In both cases, there is a quandary over whether these waters can be recycled safely, particularly for agricultural purposes. However, policy makers have already implemented many such programs, with active procedures and regulations taking place well ahead of a detailed understanding of what’s in the water before reusing it. While bacterial pathogens grab many of the headlines, waterborne viruses can be silent killers because they often occupy wastewater at levels below facilitative thresholds of detection. Moreover, small populations are often infected in a localized manner, with houses, neighborhoods, and cruise ships all serving as highly variable foci. However, the ubiquity of enteric viral pathogens is almost prosaic in nature. Norovirus is the most common source of viral acute gastroenteritis. Human adenoviruses are omnipresent, non-seasonal, UV-resistant, and can cause fatal infections in immunocompromised people, but also respiratory, mucosal, and gastric issues in otherwise healthy people. Because qPCR is an insufficient platform to assess enteric pathogens in wastewater, investigators have developed robust epidemiological models to derive the statistical likelihood of and quantity of their presence from overall infection rates, and to predict whether ultrafiltration, membrane bioreactors, and other treatments are sufficient before downstream reuse (the developing consensus: they are not). Recently, dPCR has begun to serve as empirical validation for these methods, and subsequently to extend its own legitimacy in ever-improving waves of sensitivity and accuracy. The incorporation of array- and microfluidic-based droplets (ddPCR) has allowed researchers to assess log removal values in ground water downstream of agricultural runoff, graywater, blackwater, and mixed wastewater for genogroup I and II noroviruses, and for various adenoviruses including HAdV41, a common diarrheal agent and bellwether for water treatment safety. Commercial manufacture of plate-based dPCR instruments continues to improve throughput, which will facilitate making decisive and accurately informed policy changes that can broadly impact human health. Brandoch Cook, PhD, is a freelance scientific writer. He can be reached at: brandoch.cook@gmail.com. FOR ADDITIONAL RESOURCES ON PCR, INCLUDING USEFUL ARTICLES AND A LIST OF MANUFACTURERS, VISIT WWW.LABMANAGER.COM/PCR October 2021 Lab Manager 59 innovations in: mass spectrometry Innovations in Mass Spectrometry IMPORTANT ADVANCES IN MASS SPECTROMETRY LEADING UP TO THE 2021 ASMS CONFERENCE by Damon Anderson, PhD, Scott D. Hanton, PhD, and Rachel Muenz A s the 69th annual conference of the American Society for Mass Spectrometry (ASMS) quickly approaches, we examine recent key developments and some of the most interesting applications poised to impact the future of mass spectrometry. RECENT ADVANCES Many recent advancements in mass spectrometry (MS) have centered on the study of proteomics. One such example comes from the Max Planck Institute of Biochemistry, where research group leader Jürgen Cox and his team released a new version of the pioneering and widely used MaxQuant software platform for analyzing and interpreting data produced from MSbased proteomics research. MaxQuant 2.0. includes “an improved computational workflow for data-independent acquisition (DIA) proteomics, called MaxDIA,” states a recent press release. The MaxDIA software enables researchers “to apply algorithms to DDA [data-dependent acquisition] and DIA data in the same way,” according to the institute. 60 Lab Manager October 2021 The software accomplishes this by combining the use of spectral libraries with machine learning algorithms. By predicting peptide fragmentation and spectral intensities, more precise spectral libraries are created in silico, which can then be applied to the data. Spectral libraries are one of the limiting factors in the application of MS to proteomics, so this innovation is helping to expand the scale and scope of how MS can continue to contribute. Use of this technology will enable researchers to compare data from DDA and DIA more easily, and harness the power of both techniques to measure and analyze thousands of proteins with greater breadth than before. The Max Planck team is already working on further enhancements for the new software. A paper on MaxDIA was published in July in Nature Biotechnology. Another technology gaining significant momentum, primarily in industry but also in academic circles, is MS-based multiple attribute monitoring (MAM). The MAM concept was born from the need to monitor protein production and purification, and limit the inherent heterogeneity of biologics, such as therapeutic antibodies, LabManager.com innovations in: mass spectrometry and their impact on quality control. Although MAM is not a new concept, advancements in MS instrumentation and data analysis solutions have made MS-based MAM the preferred platform in biologics drug quality control. Immediate applications include biopharmaceutical discovery and development, although the technique is gaining popularity in research groups studying post-translational modifications and other potential modifications of proteins. “With ENABLE, we are starting with a successful commercial design capable of conducting diagnostics from atmospheric pressure down to ultra-high vacuum.” MS instrument providers such as Thermo Fisher Scientific, SCIEX, Waters, and others now offer complete MAM workflows that are built around their MS technology platforms. The solutions are intended to provide comprehensive characterization of proteins and therapeutics by matching reagents and protocols with instrument output and software analysis. Another new area for MS development centers on the concept of trapped ion mobility MS. The ion mobility mass spectrometry (IM-MS) method combines the separation of ionized molecules based on their mobility in a carrier buffer gas, with the high-accuracy resolving power of mass spectrometry. This enables separation of both mass and size/shape, which provides even greater specificity for analyzing and understanding the complex suite of proteins present in living cells. When combined with chromatography and powerful analytical software, the IM-MS technique offers a multi-dimensional approach toward resolving complex samples such as those in proteomics studies. Trapped ion mobility spectrometry is a modification that essentially traps the ions during ion mobility separation, which allows for sequential fragmentation over a series of timed millisecond scans. Combining trapped ion mobility with a method termed parallel accumulation-serial fragmentation (PASEF), these trapped ions can accumulate in parallel, and be released sequentially. Rather than a quadrupole selecting a single precursor ion for fragmentation, such as that of a typical MS/MS experiment, sub-millisecond switching enables the selection and fragmentation of multiple precursors in a single 50 ms run. Such performance can result in thousands of protein identifications over a short run time using nanogram amounts of material. These technological developments have led to significant gains in sequencing speed without a decrease in sensitivity, ideally suited for complex, high-throughput proteomics. Significant advancements have been made recently in trapped ion mobility MS. For instance, at the beginning of June, Bruker Daltonics launched new MS technology that combines time-of-flight and trapped ion mobility MS (timsTOF) with liquid chromatography and improved automation software. That combination will allow for big steps forward in the efficiency of epiproteomic and proteomic analyses in labs—along with enabling the rapidly growing field of single-cell proteomics. An additional advancement impacting both the proteomics and metabolomics spaces is spatially resolved MS. Development of multimodal imaging mass spectrometry is helping researchers reveal more about the workings of biological systems. Yet another area of growth is high-throughput planar solid-phase extraction coupled to high-resolution mass spectrometry, which is helping streamline screening for antibiotics in foods, among other applications. APPLICATIONS Researchers have recently been applying established mass spectrometry techniques in many interesting ways. In a study published in the journal Antiquity in August, researchers used accelerator mass spectrometry to analyze 26 human tooth and bone samples from Machu Picchu, Peru, determining that the site is at least two decades older than what textual sources indicate, demonstrating the ability of MS innovations to impact a very wide range of important studies. In another recent development, MS will have an impact a little farther from Earth in the Southwest Research Institute’s (SwRI’s) Environmental Analysis of the Bounded Lunar Exosphere (ENABLE) project, a three-year $2.18 million program funded by NASA that was announced in July. The program aims to bring mass October 2021 Lab Manager 61 innovations in: mass spectrometry Through the ENABLE project, SwRI is adapting a mass spectrometer to return the technology to useful operations on the lunar surface for the first time in half a century. This image of the Lunar Atmospheric Composition Experiment, deployed by Apollo 17 in 1972, was photographed from the lunar surface by astronaut Harrison Schmitt. Image Courtesy of NASA/Schmitt/AS17-134-20499 spectrometry back to the moon, adapting a commercially-available mass spectrometer to identify the composition of the lunar surface. “The last mass spectrometer deployed to the lunar surface was the Lunar Atmospheric Composition Experiment in December 1972 during the Apollo 17 mission,” says SwRI’s Edward Patrick, ENABLE principal investigator, in a press release. “With ENABLE, we are starting with a successful commercial design capable of conducting diagnostics from atmospheric pressure down to ultra-high vacuum.” This work demonstrates continued innovation to adapt existing technology to solve new problems. MS has also been an important tool in studies of SARS-CoV-2, the virus responsible for the current COVID-19 pandemic. Recently, in three studies explored in a Science research article in August, MS helped reveal how the B.1.427/B.1.429 variant of concern evades the human immune system. Another study published in Sustainability in July shows how MS could be combined with machine learning to provide surveillance of airborne pathogens during the current COVID-19 pandemic and future ones. “Widespread deployment of such an MS-based contagion surveillance could help identify hot 62 Lab Manager October 2021 zones, create containment perimeters around them, and assist in preventing the endemic-to-pandemic progression of contagious diseases,” the researchers write. While these studies used more established MS techniques, there are a number of new technologies emerging around MS-based SARS-CoV-2 and virus testing. As reported in December 2020, there are two MS-based SARS-CoV-2 diagnostic tests that have received Emergency Use Authorization from the US Food and Drug Administration. The MassARRAY SARS-CoV-2 Panel commercialized by Agena Bioscience and the SARSCoV-2 MALDI-TOF Assay from Ethos Laboratories pair RT-PCR with MALDI-TOF MS to detect the COVID-19-causing virus in samples collected at home or at a point-of-care location. Many other MS techniques for virus testing are being developed and used at the research level—certain to be an area of increasing value moving forward. “MS could be combined with machine learning to provide surveillance of airborne pathogens.” TRENDS Three general themes in MS that continue rapid and important ongoing developments and offer promise for the future involve MS imaging, single-cell proteomics, and remote monitoring. Further progress in these areas will continue to bring new insights and technologies into the hands of researchers to benefit the general population. With that thought in mind, we look forward to seeing more of the latest cutting-edge developments impacting the MS industry at the ASMS conference this year. Damon Anderson, PhD, is the technology editor at LabX.com. He can be reached at danderson@labx.com. Scott D. Hanton, editorial director for Lab Manager, can be reached at shanton@labmanager.com. Rachel Muenz, senior digital content editor for Lab Manager, can be reached at rmuenz@labmanager.com. LabManager.com lab manager online LM ONLINE What’s new at LabManager.com? Managing Laboratory Complexity and Data-Driven Operations The ability of scientific organizations to react swiftly to changing scientific, financial, and business conditions is of paramount importance in today’s rapidly evolving scientific landscape. The global pandemic exemplified how rapidly and explosively conditions can change. The ability to adapt quickly to such monumental shifts is necessary and achievable by optimizing lab performance using new digital technologies and expert analysis to enhance the visibility and utilization of assets. This piece highlights a few key steps to achieve operational agility. To read the full article, visit: www.LabManager.com/data-driven-operations Check out what else LabManager.com has to offer—from the latest research and industry news, to product resource guides, educational webinars, exclusive online content, and much more. LabManager.com October 2021 Lab Manager 63 More space for your ideas. Our innovations help simplify medical progress so that better therapies will reach patients faster. What will happen to your ideas? 1,000+ open positions worldwide. Join our team and elevate your creativity. www.sartorius.com/morespace
