Regulatory Submissions for Pharmacometric Models
A practical guide to preparing pharmacometric models for regulatory submission, including population PK, exposure-response, PBPK, model analysis plans, model analysis reports, datasets, code, diagnostics, and regulatory documentation.
Model-Informed Labeling Strategies
Learn how population PK, exposure-response, PBPK, and other model-informed approaches can support drug labeling decisions, including dosing, dose adjustment, drug interactions, special populations, and clinical pharmacology information.
Model-Informed Drug-Drug Interaction Assessment
Learn how model-informed drug-drug interaction assessment uses mechanistic PK models, static models, and PBPK simulations to predict changes in drug exposure caused by metabolic enzymes, transporters, inhibition, induction, and other interacting drugs.
Model-Informed Drug Development Strategy
A practical introduction to Model-Informed Drug Development strategy, covering development questions, model selection, evidence generation, model evaluation, regulatory interactions, and lifecycle application of PK, PD, PBPK, QSP, and population models.
Model-Informed Dose Adjustment
Learn how pharmacokinetic and pharmacometric models can support individualized dose adjustment by connecting patient characteristics, drug exposure, therapeutic targets, and dosing decisions.
Model-Based Treatment Duration Selection
Learn how PK, PK/PD, exposure-response, and disease-progression models can support treatment duration selection by linking treatment exposure, response, disease control, and clinically relevant outcomes over time.
Model-Based Endpoint Selection
Learn how model-based endpoint selection uses PK, PD, exposure-response, longitudinal, time-to-event, and disease-progression models to choose informative endpoints for clinical development and trial design.
Model-Based Drug Development vs. MIDD
Learn the difference between Model-Based Drug Development (MBDD) and Model-Informed Drug Development (MIDD), how modeling and simulation support drug development decisions, and where PK, PD, PBPK, QSP, population PK, exposure-response, and clinical trial simulation fit.
Model-Based Dose Optimization
Learn how model-based dose optimization uses pharmacokinetic and pharmacodynamic models, exposure-response relationships, variability, simulations, and clinical targets to select and refine drug dosing regimens.
Model-Based Dose Escalation
Learn how model-based dose escalation uses statistical and pharmacometric models to estimate toxicity risk, characterize dose-response relationships, and guide dose selection in early clinical development.