Call for evidence: Why has the promise of personalised medicine failed to materialise on the ground?

We’re always hearing how personalised medicine is the future, thanks to advances in artificial intelligence and genomics. In fact many of those advances are already established science - so why haven’t they materialised in our day-to-day healthcare?

A new inquiry by the UK Parliament’s Science and Technology Committee seeks to answer just that question, with an investigation into why the NHS adoption of the UK’s cutting-edge life sciences innovations often fails - and what could be done to fix it.  And more importantly, members of Applied Microbiology International could be just the people to provide answers.

The new ’Innovation in the NHS: Personalised medicine and AI’ inquiry will examine the gap between early-stage research, clinical trials and NHS-wide delivery with a focus on personalised medicine and AI, considering the system blockages, procurement, clinical pathways, and organisational aspects of the question, such as the role of regulators and clinical/professional bodies.

”Recognising that many of AMI’s members are working in relevant areas of innovative research such as the application of bacteriophage as alternatives to antimicrobials or microbiome-based therapeutics, we wanted to highlight this opportunity to showcase the breadth of expertise within our community,” says AMI policy and diversity manager Daisy Neale.

”While this is a UK-based initiative, contributions from those working in other regions are equally valuable, as insights and lessons learned elsewhere can play a powerful role in shaping effective decision-making.”

Deploying innovation

The inquiry will examine the fragmentation of the overall NHS structure leading to uneven deployment of innovations in the NHS, questions around how the cost of personalised treatments can be reduced, as well as concerns about the clinical academics and clinical trials infrastructure needed to rapidly deploy innovations within the NHS.  

The deployment of personalised medicines and AI in the NHS and the development of these technologies more broadly, offers the opportunity to improve the health economics of the growth and support economic growth. The underlying question of how to create positive feedback between the UK’s medical research, its life sciences industry, and the NHS to unlock both growth and better health outcomes for patients will be explored in the inquiry.  

Key issues identified in adopting innovation in the NHS include fragmented budgets, overstretched workforce capacity, especially for clinical academics and clinical trials, risk-averse culture, slow procurement processes, and outdated digital infrastructure. Geographical inequalities in access and uneven deployment of new technologies, as well as unclear responsibility for who drives innovation in the NHS, have also been raised as problematic. 

The background

Personalised or precision medicines refer to tailoring medical treatment to the individual characteristics of each patient––for example, using genetic information to provide personalised preventative advice, diagnosis, and therapies. Recent advances in genomics, AI-driven data analytics and biotechnology are driving this evolution, enabling new therapies like CAR (Chimeric Antigen Receptor) T-cell therapy, which uses modified versions of the body’s own immune system cells to fight cancer, and other gene therapies that are highly customized to patients. These therapies offer life-saving potential, but the need to tailor them to the individual can make them expensive to deploy.  

Novel developments in AI, such as the development of Google’s AlphaGenome deep learning model, offer further hope that genomic medicine will advance as our ability to understand genetic effects on health improves and the data analysis for personalised medicines becomes possible to automate. There are broad ambitions to use AI more widely to advance medical science; for example, the Government’s AI for Science strategy has a target to “Use AI to accelerate drug discovery to develop trial-ready drugs within 100 days by 2030 and contribute to deploying new treatments faster.” 

Share your insights

More background on why the UK Government is exploring this topic can be found in the full call for evidence, but certain questions may be of more relevance for AMI members. 

”We have pulled out the questions we think are of most relevance to AMI’s members below - however please feel free to review the entire question list here and provide answers to any you wish to (there are >25!). Responses can be brief and bullet points are welcome,” Daisy Neale says.

”Please note that though this is a UK-based inquiry, we encourage international input – if you have any experience that could be translated to the UK setting we would love to hear from you. This is particularly the case for Question 1c.  

”We are particularly interested in evidence-based insights, examples, or your thoughts and experiences on any of the following.”  

1. What is the current state of the science underpinning personalised medicine – including genomics, AI-driven diagnostics, and advanced genomic therapies?  

a. What are the most significant near-term opportunities for patients to benefit (in the NHS)? 

b. Where are the major gaps in understanding that could be addressed through further investment in research and development, and which research projects would you prioritise? 

c. What possibilities exist for personalised medicine in the medium and long-term, and what is needed to unlock these opportunities? Are there examples of specific areas of UK practice, or practice overseas, which we should learn from to help deploy personalised medicine?   

2. What role could AI realistically play in accelerating the development and reducing the cost of personalised medicine? How close are we to understanding and realising its potential and what barriers need to be removed to fulfil it? 

3. Personalised medicine depends on large scale genomic and health data being accessible and linked together. What further research infrastructure, in terms of data accessibility, compute etc. – is needed to support the development of personalised medicine (and AI)? Where are the gaps in current provision? How should the Government help ensure that its health data infrastructure is fit to deliver on this promise? 

4. How effective is the UK at translating its strengths in life sciences research into clinically validated personalised medicine (and AI tools), and into its industrial base in the life sciences? 

a. What are the main barriers in moving personalised medicines (and AI) from the early-stage research to clinical trials and through to regulatory approval?  

5. Translating cutting-edge medical science (into routine NHS treatment) has long been recognised as a problem. Considering personalised medicine (and AI) as an example, what are the key systemic barriers, such as procurement processes, workforce, or IT infrastructure, that prevent or delay the deployment of proven innovations (across the NHS)? Which of these barriers are the most important in practice? 

a. Considering the patient perspective, what needs to be done in order to encourage uptake of personalised medicine (in the NHS) and provide a service that puts patient needs first?   

Call for evidence deadline: Monday 20 April (00:00 GMT+1)  - to have your say, email us HERE.