Embracing AI Technology Will Be Key to the Future of UK Life Sciences

AI technology

ChatGPT’s explosive rise and Microsoft’s consequent investment stoked the flames under a life sciences industry that was already set to blossom. From programmers to pilots, seemingly all industries are being forced to consider how AI might revolutionise their work.

Currently, the tech presents itself in the form of generalised tools, which, while incredibly effective, may be potentially overstated. While these tools can certainly impress audiences, they may not always stand up to intellectual scrutiny.

Our sector will, in all likelihood, be revolutionised by highly specialised AI systems which are designed to solve a limited set of specific problems, such as drug discovery, handling and making sense of ‘big data’, and improving workflow efficiencies in an R&D setting, amongst others.

Microsoft’s BioGPT, trained on millions of published biomedical research articles, could be the first step towards repurposing these generalised AI to enhance great work or improve inefficiencies in the industry. Ultimately, this will massively reduce time consuming activities and freeing up time for brilliant clinicians and researchers to do what they do best.

Revolutionising patient experiences

Already, there are a number of pioneering AI tools changing and enhancing the clinician-patient relationship. Closed loop medicine, for example, is using AI to optimise dosing for patients and guide behaviours to enable better outcomes. Blueskeye, a small company based out of the Midlands, is using behavioural analysis to personalise the delivery of mental health and wellbeing care. Kinomica is a developing AI that identifies treatments that are likely to be more effective for patients, and avoid treatments that are less likely to work.

All of these great companies have one thing in common: they are using AI to collate existing information and optimise delivery to provide better patient outcomes. They provide a complimentary service to improve patient outcomes, building on existing work in the life sciences sector.

In a broader sense, it is clear that AI could quickly revolutionise the patient-clinician dynamic, helping to optimise interactions and improve efficiencies across the board. It does not take a giant leap in assumptions to see how generalised AI could help organise feedback reports, radically speed up data organisation, and act as a digital assistant to clinicians across the industry.

Research, development, and distribution

Through my years working in labs, I know first-hand the immense amount of time, effort, and crucial investment R&D consumes. Moving towards the next generation of life sciences does not come cheap or easy, so any way AI can assist in speeding up this process, or make it less resource intensive, will be welcomed by the scientific community at large.

AI has already given innovative firms such as Recursion Pharmaceuticals the ability to rethink the way we conduct traditional research. By creating biological ‘maps’, they hope to turn drug discovery away from simple trial-and-error and towards a better understanding of biological pathways. This will allow Recursion to actively search for new drugs and solutions by developing a deeper understanding of the relationships between genes and proteins.

Over and above the research and development of new treatment paradigms, AI is expected to have wider applications within the life sciences industry that will help to make the delivery of better or more advanced treatments to patients. One such application being explored and which may soon be available is the use of AI to manage highly automated, flexible supply chains, enabling the development and delivery of increasingly complex therapies and treatments.

Furthermore, this could also enable complex treatments, such as personalised cell therapies, to be deployed at-scale in a way that previously would have been largely impossible. In turn, this could then lead to significant reductions to the high costs that are generally associated with such treatments, which is a barrier to wider adoption, making them far more appealing to potential investors.

ChatGPT is already demonstrating easily transferable capabilities that would change the way patients are recruited and enrolled into trials, helping to improve patient outcomes, but also the efficiency of the trials themselves. AI can quite easily be implemented to eliminate time consuming admin that only serves to increase overheads and tighten what are generally already tight margins. Alongside this, much faster and more effective diagnostic tools will free businesses in a way that hasn’t been seen before.

For the UK to remain at the forefront of innovation and new technologies, especially within life sciences, AI needs to be embraced as a vital tool for tackling the increasingly complex future of clinical trials.

Better horizons

The adoption of sophisticated AI within the UK’s Life Sciences sector will undoubtedly optimise costs and improve patient outcomes, making the industry a far more attractive investment opportunity for those who may not have traditionally considered the sector.

There are certainly valid concerns around patient safety and confidentiality, due to the premature nature of AI in its current state, meaning that a blind commitment to the technology would not be appropriate. The dominant form of AI technologies that exist do so on the basis of machine learning, with existing data being constantly fed into the technology to improve its function. This comes with problems regarding patient safety and confidentiality, however, many of these problems can be mitigated by robust regulation and ensuring that all personal data is anonymised.

Despite these concerns, the opportunities that are present in the not-so-distant future, combined with the increasingly rapid development of the AI tools, mean that it is realistic to expect AI to play a significant role in the life science sector.

For the UK to remain a hotspot for long term innovation and high growth companies, it is paramount that we do not miss the potential opportunities that sophisticated AI presents.

Mark Andrews
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Mark Andrews
2 June, 2023