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Data management
Generative AI: can it be trusted?
In the era of precision medicine, generative AI is poised to revolutionise clinical trials as a formidable tool. As healthcare becomes more data-driven, integrating advanced technologies
such as artifi cial intelligence (AI) into clinical trials promises to deliver faster, more effi cient medical research and expedite the development of new treatments. Clinical Trials Insight discusses
the transformative potential and ethical implications of this technology with Jonathan Crowther, PhD, head, predictive analytics Pfi zer Research & Development, OARS.
O 12
ver the past few decades, the pharmaceutical industry has experienced a concerning trend: the approval rate for new drugs has halved approximately every nine years. This phenomenon, known as Eroom’s law (the reverse of Moore’s law, where the number of components on a circuit doubles every two years) highlights the growing difficulties in bringing new medications to market. Unlike the technological advances predicted by Moore’s Law, Eroom’s Law reflects a stark reality where the innovation rate in drug development is dwindling.
The process for bringing a single new drug to market now requires billions of dollars and decades of effort. A significant portion of these resources is allocated to increasingly complicated clinical trials, which are critical to ensuring the safety and efficacy of new drugs but are also a major bottleneck in drug development. Currently, roughly only one in seven drugs that enter phase I make it through to approval. “It’s a very interesting paradigm that we have because we have so much data that we shouldn’t be seeing that inverse,” says Jonathan Crowther, PhD,
Clinical Trials Insight /
www.worldpharmaceuticals.net
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