Digitally enabled lab environments, driven by AI, can help accelerate innovation, reduce lab errors and ultimately save lives, argue Andrew Garrood, James Roden and Colin Terry.
In a world where we can carry every book, film and song that has been published in our pockets and the increasing use of artificial intelligence assists our day-to-day lives, many laboratories still seem decades behind with sticky notes and paper still adorning walls and workspaces. Credit: University Hospitals Plymouth NHS Trust However, for those who depend on the outputs of laboratories, patients and customers, expect more. They are eager for faster, betterquality results that accelerate timelines, reduce errors and improve patient care.
A multitude of labs are involved in every stage of healthcare, from research and development to the doctors’ surgery, yet they all have similar challenges of disconnected systems, siloed data sources and pressure to apply AI for more rapid insights into the results collected.
Fortunately, there is a solution to all of this – the digital enablement of lab environments, maximising the use of the latest technological advances to empower organisations and scientists rising to the myriads challenges they face.
One laboratory segment, biopharma organisations, has seen that investments in Lab of the Future initiatives deliver tangible results. They are turning to digitisation to meet the pressure of accelerating scientific discovery and shore up their pipelines.
This will affect organisations of all sizes, whether an acquiring big pharma or the new start-up, as their labs will be required to digitally collaborate at speed to head off the US$236 billion [1] in drug sales at risk from loss of exclusivity.
Deloitte recently conducted a survey of 104 R&D executives [2] to build a picture of where they are investing and the benefits they are seeing. According to the results, modernisation initiatives are yielding tangible benefits for biopharma R&D. The study found that 53% of respondents experienced enhanced laboratory productivity. Nearly half (45%) also reported a decrease in human error, with 30% achieving improved cost efficiencies and 27% noting quicker therapy discovery.
Looking to the future, almost 60% of the R&D executives surveyed anticipate that their current investments will accelerate the pace of drug discovery within the next two to three years. Despite this optimism, there remains significant scope for advancement. Around one in ten (11%) of those surveyed have successfully implemented a fully predictive laboratory environment, characterised by the integration of AI, automation, digital twins and cohesive data to guide research decisions.
Biopharma organisations are turning to digitisation to meet the pressure of accelerating scientific discovery and shore up their pipelines
So where are those investments being made? The survey findings indicate that organisations are strategically investing in key areas such as laboratory automation, advanced analytics platforms, AI technologies, robotics, and smart lab instruments. These investments are aimed at fostering agile, digitally driven scientific workflows.
To unlock these investments its critical that a strategic approach is taken, without buzzwords and shiny tools being thrown at the problem. The Deloitte study found that there are four key strategies to consider for R&D organisations undergoing a modernisation effort:
Establish a comprehensive lab modernisation roadmap aligned with R&D strategy. Starting with that modernisation roadmap, a clear vision for the lab transformation needs to be created that is aligned with broader business objectives of the organisation. This must then be turned into a vision with clearly defined capabilities, strategic investments and a detailed roadmap for implementation. A blend of short-term wins to gain momentum, coupled with longterm transformation, is required to deliver success. Seventy per cent of those surveyed – who reported reduced late-stage failure rates and increased IND approvals – attributed these outcomes to lab-of-the-future investments being guided by a clear strategic roadmap.
Enhance R&D data utility through a ‘research data product’ focus. Critical to any lab but especially an R&D one is the ability to organise, integrate and optimise value from multiple types of data. Four out of five (84%) respondents believe that new technologies and analytical methods need to be built on solid data foundations. To achieve this, organisations should consider linking all laboratory instruments so they can seamlessly transfer data to centralised Cloud-based systems without manual intervention [3].
They need to build scalable data foundations that can support all the structured, unstructured and image data they generate. Lastly, they need to build data products to turn raw data into FAIR (findable, accessible, interoperable and reusable) data that can be used by all teams.
Focus on operational excellence and data governance. Scientists complain about how operational inefficiencies get in the way of delivering results. Organisations need to better manage lab equipment and see it as strategic assets to be shared across the whole company, using modern approaches to track utilisation and optimise workflows. To exploit the potential of AI and digital twins, strong data governance is key to maximise the investments made in modernising the labs.
Champion cultural change to support digital transformation. Ultimately lab transformation requires a shift in people, culture and processes. The best technologies will not succeed if nobody knows how to get the best from them. A third (33%) of survey respondents identified scaling new technologies and processes as a major challenge, while a similar number (32%) cited scientists’ hesitancy to adopt new ways of working as an obstacle.
These findings highlight the importance of engaging teams early. Communicating the rationale for transformation and empowering scientists with digital skills and ongoing support are essential for fostering trust and enabling sustained adoption of new technologies.
Seventy per cent of those surveyed – who reported reduced late-stage failure rates and increased IND approvals – attributed these outcomes to lab-of-the-future investments being guided by a clear strategic roadmap
Deloitte’s survey and analysis of industry trends showed there is a new generation of technologies available through Cloud, AI and data analytics that can enable the next level of lab modernisation. Lab-of-the-future initiatives are no longer experimental; they deliver measurable results and potentially could set new industry standards.
Creating the digital foundations for AI driven drug discovery could lead to a deeper understanding of patients and the biological drivers of disease. Furthermore, these labs will likely enable R&D organisations to create feedback loops that retrain AI models on actual wet-lab outcomes, speeding up drug discovery and supporting sustainable pipeline replenishment.
Of course, sticky notes will likely never disappear from labs, they may well just revert to their primary purpose – preventing people borrowing milk from the communal fridge!
References:
1 Bernice Lottering. Pharma faces $236 Billion patent cliff by 2030: Key drugs and companies at Risk, GeneOnline, 7 March 2025. https://www.geneonline.com/pharma-faces-236-billion-patent-cliff-by-2030-key-drugs-and-companies-at-risk/
2 Deloitte. Pharma’s R&D lab of the future: Building a long-lasting innovation engine. https://www.deloitte.com/us/en/insights/industry/health-care/future-proofing-pharma-rnd-labs.html
3 Sharma, Raveen, Van Dam, Joris. Lab of the Future Activating the Lab of the Future through an open, modular, and cloud native approach. https://pages.awscloud.com/rs/112-TZM-766/images/ Deloitte_Lab%20of%20the%20Future.pdf
Andrew Garrood and James Roden are, respectively, associate director and director Deloitte UK Life Sciences Engineering, AI and Data. Colin Terry is partner, Deloitte UK Life Sciences
