Mechanistic Modeling Improves Drug Discovery Workflows and Speeds Therapeutic Development

What It Covers

John Burke, president and CEO of Applied BioMath, explains how mechanistic modeling integrates with NOAEL and MABEL frameworks to improve first-in-human dose predictions, manage patient variability in clinical trials, and accelerate therapeutic development for gene and cell therapies through quantitative systems pharmacology approaches.

Key Questions Answered

• •NOAEL/MABEL Integration: Mechanistic modeling enhances traditional dose-setting frameworks by replacing concentration-based thresholds like IC50 with mechanism-driven metrics such as target occupancy percentages (e.g., 80–90%) or protein synthesis perturbation rates. This allows species differences to be explained beyond allometric scaling, enabling teams to justify higher, safer starting doses with quantified uncertainty.
• •Backwards and Forwards Translation: Because mechanistic models are built on biological parameters — cell counts, binding affinities, synthesis and degradation rates, feedback loop strengths — they enable bidirectional translation between preclinical and clinical settings. Teams can update model parameters as Phase 1 data arrives, progressively reducing prediction uncertainty across SAD, MAD, and recommended Phase 2 dose decisions.
• •Virtual Patient Analysis in Phase 1: Rather than waiting for Phase 3 statistical power, mechanistic models can simulate patient subpopulations during Phase 1 by sampling distributions of biological parameters. Teams can define dose targets as: achieve greater than X% response in greater than Y% of patients, enabling earlier, data-driven dose escalation decisions with fewer enrolled subjects.
• •Project Optimus Alignment: The FDA Oncology Center of Excellence's Project Optimus initiative explicitly targets dose optimization reform in oncology. Mechanistic and systems modeling directly supports this regulatory direction under PDUFA's Model-Informed Drug Development framework, giving teams a regulatory pathway to justify higher starting doses in end-stage oncology patients where homeopathic starting doses create ethical concerns.
• •PopPK Remains Relevant Late-Stage: Mechanistic modeling does not replace population PK/PD approaches; both run in parallel. PopPK becomes the standard tool at Phase 2–3 and pre-BLA/NDA stages when sufficient patient numbers allow statistical parameter distributions. For novel gene and cell therapies, however, no established PopPK standards yet exist, making mechanistic QSP models the current primary framework.