AI is transforming clinical development in pharma services but faces challenges in drug discovery due to fragmented data. Dr. Henning Steinhagen highlighted this during Inflexion’s Pharma Services dinner, discussing AI’s impact across three key phases: target identification, drug discovery, and drug development. While AI aids clinical trials, patient stratification, and biomarker discovery, its full potential remains constrained by a lack of accessible high-quality discovery data. Upstream, AI technologies like AlphaFold3 enhance experimental science by interpreting complex protein structures, revolutionizing structural biology. Conversely, downstream applications refine clinical trial designs, improving efficiency and cost, emphasizing the importance of curated data. However, drug R&D remains a lengthy process with high costs, underscoring that AI, though valuable, cannot yet substitute human expertise in medicinal chemistry. The integration of AI will evolve, but it won’t eliminate the need for skilled professionals in the foreseeable future.
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