An AI lesson from history

This time last year DDW was reflecting upon the drug discovery and development sector’s push towards artificial intelligence (AI), in particular generative AI and how it could inform research. Within that article included the news of BenevolentAI’s disappointing results of its Phase II clinical trial of its atopic dermatitis drug – a significant blow to a company that had spoken in length about how AI could improve drug discovery and development timelines. Unfortunately, BenevolentAI’s woes have continued, with the company announcing in December a major restructuring that will see it pivot back to its status of a techbio, rather than a pipeline-driven biotech. Consequences of this restructuring will largely be felt by current employees at BenevolentAI. As the company begins plans to streamline and reduce operating costs, redundancies will be inevitable. It's important to understand whether BenevolentAI’s struggles are due to limitations of current AI use or are yet another example of a biotech skyrocketing in both expectations and funding, and then failing to meet the lofty targets it had set itself. Though drug candidates discovered using these systems have yet to reach the market, both the interest and application of AI within the sector are still growing. Research by The Pistoia Alliance last year showed an increase in the use of AI and ML within research work and the technology was also touted as a top tech investment over the next two years. The fact that accessing data / data being unstructured are some of the biggest challenges drug developers face when utilising AI for research purposes shows that the disparate nature of the sector may not be best suited to this technology or that reliable and consistent data will still act as a teething problem in regard to AI for some time. Don’t expect AI-driven biotech to disappear however. Though BenevolentAI is now changing its approach to support – rather than enact– early-stage drug discovery efforts, the industry is still inundated with companies striving for breakthroughs in this area. You only need to look at last year’s Nobel Laureates in Physics, John Hopfield and Geoffrey Hinton, both of whom used tools from physics to develop methods that have advanced machine learning techniques, to understand why these technologies offer major opportunities for life sciences. And though 2024 might have seen the rise of GLP-1 agonists attracting interest across the sector, AI still made a major impact, particularly with Xaira Therapeutics’ launch that included over $1 billion of capital from investors. Xaira is developing a generative AI platform for drug discovery and development that it hopes will help advance treatments to market faster. It’s a familiar story but the biotech has been quietly developing its team throughout 2024 and managed to land a spot on the Fortune 50 AI Innovators list as well. Though the funding is a major boost for Xaira, the biotech would do well to remember that BenevolentAI also started with large investments and lofty goals. Hopefully history doesn’t repeat itself and the AI revolution can truly take off. From DDW Volume 26 – Issue 1, Winter 2024/25 Read the digital issue About the author Reece Armstrong is Editor of DDW. He has worked in life sciences and pharmaceutical B2B publishing for seven years and was previously Editor of European Pharmaceutical Manufacturer. He has a master’s degree in Journalism from Newcastle University.