In drug discovery, too many promising candidates fail because critical feasibility questions are addressed too late. Early Feasibility Assessment (EFA) offers a data-driven, model-informed approach to evaluate potential therapies earlier—before major time and resources are invested.

In this on-demand webinar, Dr. Joshua Apgar demonstrates how EFA empowers researchers to predict success probabilities, uncover key knowledge gaps, and make informed go/no-go decisions in early discovery. Learn how this quantitative framework improves productivity, reduces uncertainty, and enables smarter R&D investments.

Key Takeaways

• Integrate data, modeling, and systems pharmacology to assess early-stage feasibility.
• Quantify uncertainty and use confidence intervals to prioritize therapeutic programs.
• Identify critical data gaps influencing program success and risk.
• Apply real-world EFA examples to de-risk discovery and accelerate clinical readiness.
• Enhance cross-functional collaboration using structured, quantitative frameworks.