Can AI really transform drug development?

The use of AI in drug development is generating both excitement and scepticism. While it shows promise in speeding up processes, experts warn it’s not a guaranteed game-changer.
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The growing use of AI in drug development is dividing opinions among researchers and industry experts. Some believe AI can significantly reduce the time and cost of bringing new medicines to market, while others argue that it has yet to solve the high failure rates seen in clinical trials.

AI-driven tools have already helped identify potential drug candidates more quickly, with some companies reducing the preclinical testing period from several years to just 30 months. However, experts point out that these early successes don’t always translate to breakthroughs in human trials, where most drug failures occur.

Unlike fields such as image recognition, AI in pharmaceuticals faces unique challenges due to limited high-quality data. Experts say AI’s impact could improve if it focuses on understanding why drugs fail in trials, such as problems with dosage, safety, and efficacy. They also recommend new trial designs that incorporate AI to better predict which drugs will succeed in later stages.

While AI won’t revolutionise drug development overnight, researchers agree it can help tackle persistent problems and streamline the process. But achieving lasting results will require better collaboration between AI specialists and drug developers to avoid repeating past mistakes.