Biopharma Use of AI in Drug Discovery and Development - Current Biopharma Leadership Perspectives

DeciBio interviewed 10 biopharma leaders from the U.S. and EMEA to delve into the current usage, key applications, ROI, and unmet needs of AI/ML approaches in biopharma R&D, while also gathering insights on vendors used in the field. Several stakeholders were involved in directly implementing AI / ML approaches in their organizations and had extensive experience with key vendors offering AI solutions. All stakeholders were able to provide feedback on key use cases, perspectives on the drivers for partnerships with third parties vs. building internal solutions, and main unmet needs that persist on the market.

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This report is organized around the responses to 9 key study questions‍

• How is AI defined in your organization and what are the key R&D use cases for which you currently leverage AI?
• How do the drug development AI use cases differ by therapeutic modality?
• How do you decide what AI capabilities you will develop internally or partner with a solutions provider externally?
• What are the main barriers and unmet needs to using AI in your organization?
• How is the use of AI currently organized in your company?
• What return on investment (ROI) do you think AI has had / will have for your organization?
• What is your level of agreement with each of the following hypotheses over the next 3 years?
• Who are the key AI solution providers and where do they fit across the value chain?

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Companies Discussed

• Atomwise
• InSilico Medicine
• Schrodinger
• Exscientia
• BenevolentAI
• Recursion
• Isomorphic Labs
• Insitro

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This advisory board is meant to be a qualitative, limited scope study, and the intent is to highlight the unbiased and unfiltered feedback just from the stakeholders interviewed, not provide a comprehensive market assessment.DeciBio also has a suite of comprehensive market reports (Link Here) if broader industry level insights are of interest. 

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