It’s not just data driving the Lab of Future!

 in blog  tagged data / lab / LotF by

Four other important factors driving the Lab of the Future evolution.

What will the scientific lab look like in 5, 10 or 20 years time?  This fundamental question around the “Lab of the Future”, or LotF, particularly what that lab will look like in a highly digital and data-driven world, has been a major topic of interest, discussion and publication throughout industry and academia for the last decade and more.  Indeed there are entire websites, conferences and global initiatives given over to the area.1,2  Recently, Curlew Research scientists and consultants have been able to make their own contribution to the LotF conversation through a chapter3 in a new book published by Wiley on the digital transformation of the laboratory4.  In line with much of the current focus on “data and digital” we do highlight many of the data-centric drivers steering the LotF development, but we also concentrate on some of the other non-data factors that we believe contribute just as importantly to the LotF evolution.  In our view there are four other critical drivers that people should not overlook when considering how their labs might need to be re-imagined in the years and decades to come.  These four additional, non-data/non-digital drivers of the lab of the future are:-

  1. People and Culture
  2. Process Developments and Optimisation
  3. Lab Environment and Design
  4. New Technology and New Science

We were recently able to go into these four areas in more detail during a webinar hosted by the editors of the Wiley book and a recording of that webinar is now available.5  In this blog we would like to summarise a few of the key areas within each non-data driver, which we believe could constitute a useful “aide memoire” for the additional factors to consider when you are thinking about how your lab(s) may evolve over the coming years.

  1. In the People & Culture dimension, we believe this will be dominated by more global working, increased hybrid location working (a mixture of site-based and home-based), more collaboration and a more open working, open science culture. These changes will put a high emphasis on good networks and communications in the LotF. At a more hands-on, practical level, the explosion of robotics & increased lab automation will result in a lower density of people in the lab.  This will have a knock-on effect on safety and the risks of lone working as well as requiring a rethink in the lab scientist “user experience”.
  2. In the Process Optimisation dimension, we believe all lab processes will have to consider sustainability much more than previously. This will be helped by increasing miniaturisation and a consequent lower use of climate-impacting solvents and chemicals, and by more in silico, virtual processes being performed leading to fewer actual, tangible experiments. This move from real to virtual is already being seen in some R&D organisations, especially in the pharmaceutical industry, where virtual “Design-Make-Test-Analyse” (vDMTA) is the primary part of the process and is starting even now to surpass classical, real DMTA (rDMTA) in occurrence.  This is despite increased robotics and automation, which enable higher physical experiment throughputs:-

At a more fundamental level, with less rDMTA and more vDMTA, we also believe there will be a shift towards more of a cloud-based “Lab-as-a-Service”6 (LaaS) model for those real, tangible experiments.  This would put the classical iterative discovery cycle epitomised by Design-Make-Test-Analyse towards a more protocol-driven fee-for-service model which we refer to as REAF – “Request-Experiment-Analyse-Feedback”, which has customers requesting a scientific experiment or procedure to be performed by the service lab staff, who then run the procedure against a defined protocol, work up the results and transfer the products (tangible &/or intangible) to the customer:-

  1. In the physical Lab Environment and Design dimension, the biggest single driver will be that of a much greater emphasis on robotics and automation (R&A). Whilst these technologies have been gaining increasing importance over the last 1-2 decades, the combination of R&A, LaaS and the need for greater flexibility in the use of the lab space will make these the primary drivers for Lab Design in the years to come. Finally on lab design we have mentioned that there will be fewer people in the labs doing more open, collaborative work.  This will lead to more openness in the service lab itself with experiments from multiple customers co-occurring. All of this will impact the data privacy and security needs for LotFs, and we will cover those aspects in future blogs.
  2. Finally, two of the biggest drivers for how labs will operate and be configured in the future are New Technologies and New Science. Indeed in the Scinote-hosted webinar5 where we presented these four factors, when the audience was asked which was the most important driver for change after data/digital in the LotF, 41% identified new technologies and new science as the most important. Whilst it is not our place to crystal-ball which new technologies and new science will have the biggest impacts on the LotF, there are a few standout areas which we believe will be of critical importance in the years ahead.  Without going into very much more detail here, some of the new technologies we believe will be most influential include:-
  • Artificial Intelligence (AI) and Machine Learning (ML)
  • Quantum Computing
  • Aids to R&A integration and interoperability
    • Examples here include: digital twin technology7; improved network connectivity and the associated need for better security; Internet of Things (IoT)8 and the associated Internet of Laboratory Things (IoLT); improving the lab scientist’s experience by way of such technologies as Artificial Reality (AR)/Virtual Reality (VR)9 and voice-activated equipment (to name but two).

The first two in this list will likely play more of a role in the Design and Analyse stages of DMTA and REAF, and the final one falls clearly in the hands-on Make, Test and Experiment stages.

When it comes to new science, the crystal-ball gazing becomes even more difficult.  In healthcare, such developments as CRISPR/Cas-9,10 CAR-T,11 improved vaccines, gene therapy and microbiome-focused therapies12 will, we believe, assume increasing importance.  These will undoubtedly impact what happens in the LotF and will consequently affect how that lab is configured, structured, organised and populated.  In life sciences more broadly, techniques such as scanning tunnelling microscopy (STM)13 and cryo electron microscopy (Cryo-EM)14 will allow us to understand the world at the nano-scale even better.  Finally, in other science areas, the global drivers of sustainability and climate change will lead to major advances in CO2 sequestration and fixation;15 and the search for improved battery technology, preferably not using heavy metals,16 will drive the LotF evolution.

We go into more detail on all of these topics as well as the challenges of data management in the LotF in our book chapter, but we feel it is important to highlight the factors other than data and digital which will impact how the lab of the future develops.  We accept that these factors are not independent of each other – they cross over in many ways.  For example: AI/ML, being highly dependent on good quality data, is both data and new technology driven; robotics and automation feature in all the key drivers.  But we do believe firmly that anyone within an R&D or service organisation who is looking to commission or redesign a new lab in the years to come must consider all of these drivers alongside data & digital when thinking about and planning their new lab.

References

  1. All internet links were confirmed at time of writing (early July 2021).
  2. https://www.lab-of-the-future.com/; https://labsofthefuture.com/; https://www.terrapinn.com/conference/future-labs-live/conference.stm; https://www.pistoiaalliance.org/projects/current-projects/lab-of-the-future/
  3. Shute, R & Lynch, N., 2021, The Next Big Developments – The Lab of the Future, pp3-31. https://media.wiley.com/product_data/excerpt/94/35273471/3527347194-24.pdf
  4. Digital Transformation of the Laboratory: A Practical Guide to the Connected Lab, 2021, Klemen Zupancic (Editor), Tea Pavlek (Editor), Jana Erjavec (Editor), Wiley Inc., ISBN: 978-3-527-82506-6. https://www.wiley.com/en-gb/Digital+Transformation+of+the+Laboratory%3A+A+Practical+Guide+to+the+Connected+Lab-p-9783527825066
  5. https://www.scinote.net/webinar-defining-rd-labs-strategic-directions/
  6. Tawfik, M., Salzmann, C., Gillet, D., et al. (2014). Laboratory as a service (LaaS): a model for developing and implementing remote laboratories as modular components. 11th International Conference on Remote Engineering and Virtual Instrumentation. IEEE. https://doi.org/10.1109/REV.2014.6784238.
  7. Rasheed, A., San, O., and Kvamsdal, T. (2020). Digital twin: values, challenges and enablers from a modelling perspective. IEEE Access 8: 21980–22012. https://doi.org/10.1109/ACCESS.2020.2970143.
  8. Farooq, M.U. (2015). A review on internet of things (IoT). International Journal of Computer Applications 113 (1): 1–7. https://doi.org/10.5120/19787-1571.
  9. See for example: https://www.fit.fraunhofer.de/de/geschaeftsfelder/kooperationssysteme/mixed-reality.html
  10. Vidyasagar, A. (2018). What is CRISPR? https://www.livescience.com/58790-crispr-explained.html
  11. https://www.cancer.gov/about-cancer/treatment/research/car-t-cells
  12. Eloe-Fadrosh, E.A. and Rasko, D.A. (2013). The human microbiome: from symbiosis to pathogenesis. Annual Review of Medicine 64: 145–163. https://doi.org/10.1146/annurev-med-010312-133513.
  13. Voigtländer, B. (2015). Scanning Probe Microscopy. NanoScience and Technology. London, UK: Springer-Verlag. https://doi.org/10.1007/978-3-662-45240-0.
  14. Milne, J.L., Borgnia, M.J., Bartesaghi, A. et al. (2012). Cryo-electron microscopy–a primer for the non-microscopist. The FEBS Journal 280 (1):28–45. https://doi.org/10.1111/febs.12078.
  15. Aminu, M.D., Nabavi, S.A., Rochelle, C.A., and Manovic, V. (2017). A review of developments in carbon dioxide storage. Applied Energy 208: 1389–1419. https://doi.org/10.1016/j.apenergy.2017.09.015.
  16. Heiska, J., Nisula, M., and Karppinen, M. (2019). Organic electrode materials with solid-state battery technology. Journal of Materials Chemistry A 7:18735–18758. https://doi.org/10.1039/C9TA04328D.

Leave a comment

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.