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MAXIMIZE THE CLINICAL VALUE OF MY ADC

Identifying drivers of response for payloads would guide rational patient selection and validate ADCs in our targeted therapy paradigm.
Turbine's answer

Selection of cancer sub-indication or molecular biomarker predictive of payload-sensitivity

Finding the right payloads for any disease-subtype would be a pivotal opportunity to address ADC-resistance observed all too frequently in the clinic.
Turbine's answer

Payloads or payload combinations with the highest chance of efficacy in a heterogeneous, biomarker-positive model population

BENEFITS ONLY TURBINE PROVIDES

Pre-trained and validated models to simulate response to payloads or combinations at scale – execute millions of experiments in silico
Patient-representative avatars reach beyond the native prevalence of clinically relevant biomarkers, we can zoom in on any unmet need
Positioning hypotheses are supported by causality and mechanistic explanation of response or resistance
75
%
Turbine finds more than 75% of in vitro biomarkers from drug modifier screens
0.70
Turbine accurately ranks cancer subtypes for payload sensitivity (rank correlation = 0.70)

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