Individual skill
pkpd-modeling
Pharmacokinetic/pharmacodynamic modeling — compartmental models, nonlinear mixed effects, and dose selection.
skills/pkpd-modeling/SKILL.md
Source commit faf37c0859ebf627bfcb5225e8057d088691e0ae
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Not checked yet
- Last checked
- Nov 8, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 56
- Repository last updated
- Oct 10, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- ai-agents Repository topic
- ai-agents-automation Repository topic
- ai-skills Repository topic
- awesome Repository topic
- awesome-list Repository topic
- chatgpt Repository topic
- claude-skills Repository topic
- meta-ai Repository topic
- muse-ai Repository topic
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 5,150 bytes
Read excerpt
## Overview
pkpd-modeling covers quantitative models linking drug dose to concentration (pharmacokinetics)
and concentration to effect (pharmacodynamics): compartmental models, nonlinear mixed-effects
(population) modeling, and model-informed dose selection. It is the quantitative backbone of
drug development — from first-in-human dose to label dosing recommendations.
## When to use
- Characterizing PK: absorption, distribution, metabolism, excretion from concentration-time
data.
- Population PK (nonlinear mixed effects): separating inter-individual variability from residual
error, identifying covariates (weight, renal function, genetics).
- PK/PD linkage: Emax models relating exposure to efficacy or safety endpoints.