Turbine.ai: Accelerating Oncology Drug Discovery with AI-Powered Virtual Experiments

Turbine.ai is a biology-first, interpretable digital lab platform revolutionizing biopharmaceutical research and development by enabling scientists to simulate millions of biological experiments—across cells, animals, and patients—before executing them in wet labs. Designed for oncology-focused R&D, its flagship Simulated Cell™ platform leverages AI to predict therapy response using patient-representative avatars, offering actionable hypotheses and mechanistic insights while integrating seamlessly into existing workflows. By combining multimodal data in real time and employing a lab-in-the-loop system, Turbine.ai reduces model training time by half and achieves equivalent performance with up to 5X fewer data points, slashing costs by as much as 80%. The platform supports critical applications such as target selection, antibody-drug conjugate (ADC) payloads, clinical positioning, and DNA Damage Response (DDR), helping to de-risk development and cut Phase II failure rates. With its EFFECT™ Benchmark Suite, Turbine.ai provides rigorously validated, publicly available datasets and evaluation tools for assessing cancer drug sensitivity and gene essentiality models, ensuring realistic, bias-aware performance testing. Backed by industry leaders like AstraZeneca, Bayer, MSD, Merck, and Accenture Ventures, and supported by an elite Scientific Advisory Board, Turbine.ai is a cutting-edge force in computational biology, empowering researchers to move from scientific question to validation at twice the speed.

Key Features:

• Simulated Cell™ Platform: AI-driven simulation of biological experiments across cell lines, animals, and patients.
• Virtual Lab: A live, accessible computational environment for running billions of virtual experiments.
• Lab-in-the-Loop Workflow: Integrates real-world validation with iterative simulation to improve model predictivity.
• Biology-Driven Insights: Identifies first-in-class therapeutic targets using mechanistic, interpretable AI.
• High-Throughput Simulation: Capable of running over 50 million experiments per day.
• Simulation-Guided Data Generation: Achieves same model performance with 5X fewer data points, reducing costs by up to 80%.
• Accelerated R&D Timelines: Cuts development time by 2x from hypothesis to validation.
• EFFECT™ Benchmark Suite: Publicly available benchmarking tools for evaluating cancer drug sensitivity and gene essentiality models with true holdout splits.
• Multimodal Real-Time Integration: Combines diverse biological data types to enhance predictive accuracy.
• Preclinical Risk Reduction: Improves experiment quality to lower Phase II clinical trial failure rates.
• Interpretable AI Models: Ensures transparency and trust in mechanistic predictions.
• Support for Multiple Applications: Target selection, ADC payloads, clinical positioning, and DDR (DNA Damage Response).
• Open Evaluation Tools & Scripts: Licensed under CC-BY-SA 4.0 for community use and research reproducibility.
• Compliance with Data Integrity Standards: Enforces strict data splits to prevent leakage between drug and gene dependency domains.

Pricing: Turbine.ai offers a free access tier for researchers to explore its Virtual Lab and benchmarking suite, with premium features and expanded capabilities available through subscription-based enterprise plans.

Conclusion: Turbine.ai stands at the forefront of AI-driven drug discovery in oncology, delivering a powerful, scientifically rigorous platform that accelerates R&D, reduces costs, and enhances decision-making through unprecedented simulation fidelity and open research tools.