H E A L T H I N S I G H T S
When it comes to clinical development , saving time translates to saving lives , or at least improving them , through faster availability of treatments . It also translates into revenue opportunity – and a significant one at that . Some industry sources estimate that bringing new treatments to market ahead of schedule can be worth between £ 500,000 to £ 6.5 million per day . However , due to uncertain regulatory landscapes , coupled with the rapidly evolving nature of the technology , some companies are taking a wait-and-see approach to adopting Generative AI , delaying investments until the course forward is clearer . While this may seem a prudent approach , it will be one organisation ’ s regret in the long run as they miss out on the opportunities Generative AI holds , such as drug discovery and speed to market , and as competitors jump ahead and take the lead .
For life sciences companies looking to seize a competitive edge and supercharge their speed to market , there are a few key areas of the clinical development lifecycle they should focus on first .
Simplifying the research process
Research and development ( R & D ) is often the most time-consuming part of the drug development process , but AI can accelerate this process by up to 50 % as the technology has a multiplier effect wherever it is applied .
On average , it takes about seven years to develop a new drug and bring it to market . For ambitious life science businesses , Generative AI ’ s ability to generate insights and content in a fraction of the time of a human means wiping months , or even years , off that average . Bryan Hill , Chief Technology Officer , Life Sciences , Cognizant , focuses on how emerging tech can help clients increase innovation to bring new therapies to market faster .
Life sciences can implement Generative AI at the very beginning of the R & D cycle , to aid in searching and synthesising available literature on a specific potential drug . Instead of beginning with a manual keyword search and sifting through hundreds of articles across various sources , teams could prompt a Generative AI-enabled tool to rapidly search , gather and distil relevant articles – or even suggest unanticipated information pathways to explore .
Generative AI also has the potential to change how researchers find existing literature . Usually , researchers simply type keywords into the search box . But with a Generative AI tool , they could state their goal into the prompt , providing context and intent , for the technology to find reference materials to support that specific ask , saving significant time while broadening the research horizon .
Automating clinical trial protocol writing
Compiling a clinical trial protocol document is a lengthy process that can take anywhere from a few months to over a year . Generative AI technology ’ s
THE TRANSFORMATIVE IMPACT OF GENERATIVE AI ON LIFE SCIENCES
www . intelligenthealth . tech 17