Lecture Notes
PK and PKPD Modeling Course Lectures
1 Pharmacokinetics (PK) Course
Foundational pharmacokinetics lectures covering ADME, compartmental models, clearance, and dosing.
| Week | Lecture | Topic |
|---|---|---|
| 1 | Foundations of PK Terminology and Data | Variables, parameters, constants, errors |
| 1 | Units, Dimensionality, and Rate Processes | Dimensional analysis, zero/first-order rates |
| 1 | Mathematical Foundations of PK | Exponentials, logarithms, calculus for PK |
| 2 | One-Compartment IV Bolus Model | Monoexponential decline, ke, half-life |
| 3 | Drug Transport, Diffusion, and Distribution | Membrane permeability, Fick’s law, distribution |
| 4 | Volume of Distribution and Protein Binding | Vd, fu, tissue partitioning |
| 5 | Volume of Distribution — Mechanisms and Determinants | Vss, Vd derivations, physiological determinants |
| 6 | Clearance, Hepatic Extraction, and Intrinsic Clearance | CL, ER, CLint, hepatic microanatomy |
| 7 | Hepatic Clearance — Intrinsic Clearance and Extraction Ratio | Vmax/KM, high vs low ER drugs, DDIs |
| 7 | Well-Stirred Model and Renal Elimination | Well-stirred model, GFR, renal CL |
| 8 | Extravascular Dosing and Oral Absorption | First-order absorption, bioavailability, flip-flop |
| 9 | IV Infusion Kinetics | Zero-order input, steady state, loading doses |
2 PKPD Modeling Course
Population pharmacokinetic-pharmacodynamic modeling lectures covering NLME theory, diagnostics, and covariate analysis.
| Week | Lecture | Topic |
|---|---|---|
| 1 | Philosophy, Principles, and Practice | Modeling philosophy, two pillars, parsimony |
| 2 | Structural Models and Parameter Estimation | Model building, estimation approaches |
| 4 | Population PK Model Components and NLME | Structural/variability/covariate submodels, η, ε |
| 5 | Base Model Diagnostics and Likelihood Comparison | GOF, -2LL, LRT, AIC |
| 6 | Graphical Diagnostics and Residual Analysis | DV vs PRED/IPRED, CWRES interpretation |
| 7 | Residual Diagnostics and Error Model Specification | Additive/proportional/combined error, RUV |
| 7.5 | Covariate Modeling Fundamentals | Covariate types, functional forms, parameterization |
| 8 | Covariate Diagnostics and Methodology | EBE screening, shrinkage, SCM/GAM/FFM |