AI Innovation in Life Sciences

We previously covered our expert discussion around how life sciences organisations can successfully adopt AI, hosted by Bradley Quinn, Managing Consultant at AND Digital, with Subroto Mukherjee, Chief Strategist at FutureGlobalTech, Lee Maw, Chief Digital and Information Officer at LGC, and Leena Pankhania, AI Strategy and Transformation Lead at AND Digital.

In this blog, we explore inspiring and effective use cases of successful AI adoption as shared by our experts, along with their tips for businesses to accelerate their own adoption.

Start small for successful AI use cases

Drug discovery and clinical trials are the pinnacle of innovation within life sciences. While this is where the glamour and publicity may lie, it’s the simpler AI use cases that are most successfully adopted.

For Lee Maw, some of LGC's work focuses on creating oligonucleotides - short single strands of RNA and DNA. A key challenge is the difficulty in predicting how hard or easy these are to manufacture. To tackle this, LGC uses machine learning to analyse new orders and predict the time and money needed for manufacturing. This innovative yet practical, AI application delivers immediate business benefits.

In Lee's view, starting with straightforward tasks—such as creating content or product descriptions—is the best approach for AI adoption. By building credibility and skills, teams can confidently progress to more complex AI innovations in the future.

Personalised and accessible healthcare

Subroto Mukherjee sees huge AI innovation in both personalised medication and vitamin recommendations. He acknowledges the impressive progress in AI-based drug discovery, especially for vaccines. But AI is also revolutionising diagnostics; helping patients receive faster diagnoses by combining AI with clinicians’ expertise. 

Subroto envisions AI as a clinical support system that promotes healthcare equity for everyone. For example, products like wearables can send valuable health data back to organisations for review. This can be used to predict health issues, safeguard the user's wellbeing and provide new health insights for the wider population.

Developing skills to accelerate AI innovation

For all of our experts, building the skills and knowledge to be able to confidently adopt AI into their business was a crucial step in innovation.

For Lee, LGC's workforce already boasts strong data science skills. The next step is launching an AI Academy to ensure that everyone shares a common vocabulary of what AI is and how to use it effectively. This training will build confidence in the teams and complement their core data skills to drive innovation even further.

Google is also developing a large-scale AI adoption programme, in partnership with AND Digital. Their goal is to help people in sectors such as life sciences grasp the challenges that come with AI and create training programmes that meet those specific needs. 

No ‘one-size fits all’ approach to upskilling

Leena Pankhania advises that meeting people at their individual skills level is crucial and a 'one-size fits all approach will be less effective. 

Understanding different learning styles and the relevant use cases is vital to helping people understand the importance of data and AI. Once they see the value of AI adoption, innovation becomes a natural part of the process, as people’s knowledge and skills increase.

Empowering teams to unlock AI's potential

In summary, AI has incredible potential in the life sciences sector, in both the exciting and more practical use cases. Fostering a culture of collaboration and innovation begins with educating the whole business on AI best practice, and developing skills to enable employees to confidently adopt AI into their work. 

As AI technology evolves, a focus on effective communication and tailored training programmes will be crucial for accelerating innovation and ensuring equitable healthcare solutions.

We partner with industry leaders in life sciences and healthcare to deliver cutting-edge AI solutions, and accelerate digital transformation and capabilities. See how we enabled AI-powered genetic sequencing for a leading biotechnology company here.

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