Turbine, a leading company specializing in virtualizing biological experiments with AI, today announced a collaboration with AstraZeneca LSE/STO/Nasdaq: AZN to test the ability of Turbines platform to rationalize antibody-drug conjugate ADC discovery by predicting response mechanisms, informing ADC positioning, and reducing the need for large-scale cell line screens. This collaboration will apply Turbines platform, which virtualizes biological experiments at scale, to not only improve the efficiency and speed of ADC discovery but also deliver mechanistic insights that current experimental screening approaches may typically lack.
ADCs are targeted cancer therapies that deliver potent drug payloads directly to tumor cells, but discovery can be slowed by the need to identify effective payloads across diverse tumor types and patient populations through costly, large-scale screening of hundreds of cell lines and patient-derived xenografts PDXs. Through this collaboration, Turbine and AstraZeneca will address the in vitro challenge by implementing a lab-in-the-loop approach where Turbines platform recommends a strategically chosen subset of cell lines for testing, then predicts outcomes across thousands of in silico models using AstraZenecas ADC datasets, including both single-agent and combination studies. This brings discovery closer to outcomes, with the long-term aim of extending the same approach to patient derived models and ultimately clinical care. Beyond reducing experimental burden, the platform also provides mechanistic insights that enhance clinical translatability, modeling not only cell survival but also changes in gene expression, to understand why cells respond or resist treatment.
By implementing a lab-in-the-loop approach, we can move beyond broad experimental screening toward a more efficient, targeted strategy that selects the ADC combinations most likely to succeed in patients, said Daniel Veres, MD, PhD, CSO and Co-Founder of Turbine. This also lays the groundwork for deeper integration of our Virtual Lab into discovery workflows, helping ensure that the right experiments are run to generate the greatest impact for patients.