Despite the value of AI to the pharmaceutical industry in the drug discovery space, significant barriers to its adoption remain. One of the major barriers lies in developing the relevant AI capabilities to tackle questions around novel target identification, lead identification and optimization, safety, and bioavailability and metabolic stability, to name a few. Big pharma has, for the most part, looked at investing heavily in these capabilities internally, launching open innovation programs or acquiring promising drug discovery startups. However, smaller pharmaceuticals and clinical-stage biotechnology companies are more resource-scarce, especially if there is no internal AI expertise within the core team.
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