In Silico Clinical Trials: A Validation Framework for Predictive Modeling
In silico simulations are transforming the way pharmaceutical companies design and execute clinical trials. By combining large-scale patient-level data, biomedical knowledge graphs, and advanced AI, QuantHealth’s platform models diverse patient populations and predicts trial outcomes across thousands of design variations long before patient recruitment begins.
However, predictive power means little without validation.
That’s why QuantHealth developed a rigorous validation framework.
Our new whitepaper, “In Silico Clinical Trials: A Validation Framework for Predictive Modeling,” details the scientific foundation that ensures every model is aligned with real-world outcomes.
Inside the Whitepaper
The whitepaper introduces QuantHealth’s five-layer validation framework, developed to confirm predictive reliability across every stage of model design and testing:
Logical (Conceptual) Validation — Confirms that disease progression, treatment effects, and drug-response relationships align with current clinical and scientific understanding.
Data Validation — Verifies data completeness, accuracy, representativeness, and alignment with epidemiological benchmarks while addressing potential biases to ensure simulated cohorts match actual trial populations.
Mathematical & Statistical Validation — Tests predictive accuracy at the patient level using sensitivity analyses, reproducibility checks, and benchmark comparisons.
Retrospective Clinical Validation — Reconstructs completed clinical trials using only historically available data to compare predicted and observed outcomes across endpoints and subgroups.
Prospective Validation — Generates predictions for ongoing trials before unblinding and evaluates accuracy against predefined criteria, including binary outcomes, effect sizes, and arm-level results.
This systematic process delivers transparent, reproducible evidence of accuracy, empowering clinical development teams to integrate simulations confidently into data-driven decision-making.
📥 Download your copy of “In Silico Clinical Trials: A Validation Framework for Predictive Modeling” and see how QuantHealth’s validated approach is setting a new standard for predictive accuracy in clinical research.