Turbine To Simulate Hard-to-treat Cancer Populations With Ai For Identification Of Novel Dependencies Through Collaboration With Msd

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turbine to simulate hardtotreat cancer populations with ai for identification of novel dependencies

Turbine, a leading developer of cell simulations with AI, today announced a research collaboration with MSD the tradename of Merck Co., Inc., Rahway NJ USA to create simulations of cancer patient populations that remain difficult to treat and study in laboratory settings.

To develop novel treatments for patients, scientists must first understand the biological mechanisms driving their cancer in wet lab experiments. Laboratory models of many solid tumors fail to reflect the molecular diversity and biological complexity observed in patients. Many of these cancers depend on biological pathways and microenvironmental conditions that cannot be replicated in standard lab cultures, limiting the discovery of effective therapies.

Under the agreement , MSD will use Turbines Simulated Cells to create virtual tumor models that closely mirror disease subtypes which remain difficult to study in pre-clinical experiments and thus hard to treat. Across millions of simulated experiments, the parties hope to uncover novel dependencies in these highly resistant tumor populations, guiding MSDs wet lab experimental efforts to validate novel drug targets, biomarkers and rational combination therapies. The collaboration is initially set for one year, after which time MSD will have the option to obtain multi-year access to Turbines virtual lab and proprietary virtual tumor models.

Millions of cancer patients are fighting forms of the disease for which no lab-based model exists today, said Daniel Veres, Chief Scientific Officer at Turbine. Unconstrained by the physical limitations of lab-based tumor models, the promise of Simulated Cells is to mimic the biology of disease in patients and open new paths to treat them. Its great to get a chance to make this possible with an organization committed to rethinking the R D process with AI.

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