Individual skill
pkpd-modeling
Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".
plugins/KalarisLabs/research-agent-skills/skills/pkpd-modeling/SKILL.md
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# Pharmacokinetic and Pharmacodynamic Modelling
## When to use
Any question about what the body does to a drug or what the drug does to the body: deriving
exposure metrics from concentration-time data, fitting a structural model, building or checking a
population analysis, choosing a dose or a regimen, relating exposure to effect, comparing
formulations, or scaling to a new population.
## The three rules
**1. Fix the exposure metric and the analysis population before computing anything.** AUC(0-t),
AUC(0-inf), AUC(0-tau) at steady state, and Cavg are different quantities and answer different
questions. So do AUCinf based on observed versus predicted Clast. Choosing after seeing the