Artificial Intelligence (AI), including both deep learning and machine learning, will become increasingly important within the life science sector in the coming years. This will effect lab demand due to the potential for downscaling lab space and upscaling space for computers, power and cooling requirements as well as the need for flexibility.
The life science industry is affected by tech and AI on a day-to-day basis. This is because of the breadth of application that AI has on the ability to cover the drug development process, from discovery to manufacturing that is significant:
Impact of AI:
Discovery: Scientists in laboratories across the world are executing numerous complex experiments every day generating huge amounts of data. The challenge is in finding useful information in the flow of data and to make meaningful insights which could ultimately lead to getting a product to market faster. AI allows the researchers to predict the potential benefits of a new compound.
Clinical Trials: A significant cost in validating a drug is in clinical trials and this is also where many drugs fail, leading to pharma often having to write off their investment. AI offers the potential to support trial design, better choice of subject and improved data analysis.
Manufacturing: The manufacturing of a drug especially biologicals is an extremely complex process. The use of AI has the potential to improve quality control, reduce materials wastage and potentially lead to faster production.
Science has been based on developing a hypothesis and proving or disproving, by gathering the evidence and looking for relationships in the data. As data sets are getting bigger and more disparate, identifying the relationships with standard statistical model is getting progressively more challenging. The introduction of AI provides scientists with analytical tools that are able analyse data in a completely different way and offers the potential to provide more powerful insights from protein folding to chemical interaction. This is truly revolutionary and the possibility, in terms of drug discovery and the speed of bringing solutions to disease and ill health, could be truly impactful.
Impact on real estate:
Tech and life sciences are coming together, in the future, it is feasible, with the laboratory automation, we will see pharma companies and clinical research organisations establishing contractual wet labs that operate autonomously. This could mean that laboratory services become more efficient with a higher throughput leading to a scaling down of global lab space and the scaling up of computational lab space, with real estate focusing more on power, cooling requirements and data provision.
The practice of outsourcing chemistry work is already prevalent and taking this automated approach further could lead to an acceleration of innovation and ideas coming through with spinouts and academics no longer facing costly barriers to entry which including both real estate and expensive laboratory equipment.
Clearly, for property owners and developers looking at trying to future-proof their buildings for the life science sector, flexibility in design remains key in order to be able to accommodate the changes that are going to be seen in the way that science is undertaken in the future.
Here is a link to the full blog post: https://www.bidwells.co.uk/what-we-think/how-will-the-application-of-ai-in-the-life-science-sector-impact-on-the-demand-for-labs/