BREAKTHROUGH IN DRUG DEVELOPMENT: AI TO REVOLUTIONIZE THE PROCESS?
We’ve all heard the saying “the cure is worse than the disease,” but what if that was actually true? Drug development has not been the smooth, quick process we all hope for it to be. With a staggering 90% failure rate, drug development takes 14 long years on average and costs a mind-blowing $2 billion to bring a new drug to market. Enter the cutting-edge technology of artificial intelligence (AI) and machine learning (ML), providing a glimmer of hope in this arduous process.
Computational approaches have long been focused on the discovery phase, with the emphasis on targeting and optimizing drugs. These methods have led to some promising results, but the challenge remains that these approaches are largely correlative and not causal. AI is making strides in clinical trial design and patient enrollment, but the big question still remains: Can AI be the game-changer in drug development?
One of the primary challenges lies in the proper diagnosis and stratification of diseases. With an estimated 50-100 million misdiagnoses annually, disease progression and phenotyping are critical factors that affect root cause analysis of the high failure rate. Real-world evidence and data, claims data, as well as data interoperability are crucial, yet complex, components of this process.
So, will AI be the ultimate savior in drug development, reducing the failure rate and producing more effective drugs? Or are there still too many variables and unknowns to make that call just yet? Share your thoughts and let’s get the conversation started!
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