Goldman Sachs 45th Annual Global Healthcare Conference
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Exscientia (EXAI) Goldman Sachs 45th Annual Global Healthcare Conference summary

Event summary combining transcript, slides, and related documents.

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Goldman Sachs 45th Annual Global Healthcare Conference summary

2 Feb, 2026

Industry context and platform strategy

  • Biopharma faces high failure rates in clinical trials, with a need for better data and models to improve outcomes.

  • The focus is on using AI-driven drug design to address statistical causes of trial failure, not just biological mechanisms.

  • The platform is therapeutic area agnostic but internal expertise is concentrated in oncology; partnerships extend reach to other areas.

  • Proprietary data generation and automation are central to rapid, efficient learning cycles in drug development.

  • Automation facility has improved productivity by 75–90% in cost and time, enabling faster and more targeted experimentation.

Proprietary pipeline and clinical progress

  • Three main assets advancing: CDK7 inhibitor (617), LSD1 inhibitor (EXS539), and MALT1 inhibitor (565), all targeting oncology indications.

  • CDK7 inhibitor designed for reversible action and improved absorption, aiming to minimize toxicity and maximize efficacy in breast and potentially lung cancer.

  • LSD1 inhibitor is brain-penetrant, addressing both AML and small cell lung cancer, with design focused on reducing hematological toxicity.

  • MALT1 inhibitor optimized to avoid liver toxicity, targeting B-cell malignancies with a focus on CLL in combination with BTK inhibitors.

  • Clinical trials are adaptive, with global footprints in the US and Europe, and initial data readouts expected later this year.

Partnerships and business model

  • Major partnerships with Sanofi, Merck KGaA, and BMS provide significant non-dilutive funding and leverage platform capacity.

  • Partnership economics include up to $343 million per program with Sanofi, with $193 million pre-commercial and double-digit royalties.

  • The model allows internal focus on select oncology programs while external partners advance other assets, maximizing platform output.

  • Automation and proprietary data generation are expected to further enhance partnership productivity and enable new business models.

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