McKinsey estimates AI use cases could generate $60 billion to $120 billion a year in economic value for pharma and medical-product industries by boosting efficiency and innovation throughout the sector’s value chain. This trend aligns with an increase in pharma firms experimenting with AI use cases in their R&D processes.
Over the next three to five years, experts predict that AI-enabled efficiencies could halve early-stage development timelines and costs.
But that is not to say AI is without its challenges. Ultimately, any LLM or other AI-based technology is only as good as the quality, completeness and context of the information on which it is trained and applied. In pharma, where decisions are expensive to reverse, inputs are everything.
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