AI can make drug-testing more precise, relevant to human biology Premium

FDA proposes draft guidelines on AI use in drug development, addressing challenges and opportunities for improving safety and efficacy.

On January 6, the US Food and Drug Administration (FDA) proposed draft guidelines on the use of artificial intelligence (AI) to assess the safety and effectiveness of drugs.

The influential body has said that in the last decade, the number of submissions from drugmakers that include an AI or machine-learning component has seen an exponential rise. There was only one such submission per year in 2016 and 2017 but in the next two years it tripled; in 2021, the FDA reported a remarkable 10-fold increase on the previous year alone with 132 submissions including an AI and/or machine-learning component.

It takes nearly 10 years and over a billion dollars to develop a drug using conventional (animal-based) processes, which also have a success rate of only 14%. Emerging technologies like AI provide opportunities for us to catalyse and improve the human-relevant drug-development pipeline.

For example, rats can eliminate some drugs from their bodies much faster than humans can, which means that for the same dose level, humans would be exposed to the drug for a longer duration. As a result, the data for a compound obtained by testing with rats will have to be adjusted for this skew.

The responses of humans belonging to different populations around the world to drugs and diseases also vary according to age, sex, preexisting medical conditions, and genetic variabilities, among other factors. It’s often difficult to predict this range of responses from a homogenous, lab-bred animal population.

Researchers today use AI across the breadth of the drug development cycle.

In the discovery phase, researchers comb through databases with thousands of compounds to select a few hundred promising candidates for a particular use case. Then they test these compounds on animals during preclinical research. The data for compounds that produce encouraging results in animal models are submitted to drug regulators for permission to conduct human clinical trials.