Artificial intelligence (AI) has found itself being utilized with increased frequency within the biopharma industry, with companies often collaborating with AI platform providers for a myriad of reasons and mutual benefits. In this article, find out about the growing role that AI is currently playing within a sector that is constantly evolving.
Searching for Drug Candidates
AI plays an important part when it comes to streamlining the process of discovering new drug candidates. This can include predicting the properties of a potential compound where only the molecules that possess the relevant properties are selected for synthesis, saving both time and money by preventing work on compounds that have a high chance of being ineffective. AI can also be used to create ideas for entirely new novel compounds, where the molecule at hand is predicted to have the relevant properties that are needed for a successful clinical trial process, accelerating the rate at which new effective medicines are discovered while also saving large amounts of time that would be needed for manual human intervention.
Finding Clinical Trial Participants
Matching the correct trial with the right participant is a challenging and time-consuming process for both researchers and the patients themselves. With the importance of clinical trials in the R&D process, this is a vital step. Despite this, organizations repeatedly face challenges relating to recruiting participants. Based on an analysis done by Clinical Trials Arena, almost 80% of trials do not meet enrollment timelines, while being unable to recruit suitable patients serves as the most common reason for clinical trial termination, making up 55% of cases. This can be a major threat to the industry as it causes delays in drugs being made available to the market.
With this at stake, AI processes can help improve patient selection by identifying and selecting cohorts through data sources like medical health records to determine eligible populations to participate in studies. Subsequent analysis can further hone in on suitable subjects whilst also reducing any unnecessary screening required.
Improving the Manufacturing Process
The manufacturing stage is a crucial point in the timeline of a pharmaceutical asset, with manufacturers needing to meet stringent regulatory requirements as well as customer expectations by providing a consistent product. Here, AI can also play an integral role in providing insights and reducing the requirement for human intervention, such as in quality assurance by identifying defects in raw materials before they enter the production line. AI can also be implemented by spotting faulty products or packaging in real time, maintaining customer satisfaction.
Industry Applications
Many companies have implemented the use of AI in their business operations. French drugmaker Sanofi has previously expressed its desire to be the first pharma company powered by AI, participating in a host of AI collaborations. A notable example of this was in May 2024, when they entered a partnership with Formation Bio and OpenAI to design software to accelerate the drug development process and bring medicines to patients more efficiently. Another case is Eli Lilly and Company collaborating with XtalPi in a combination of AI and robotics. Here, Lilly utilize XtalPi’s technologies to pinpoint small-molecule compounds that can then be brought through clinical and commercial development.