pkpd-modeling agent skill by K-Dense-AI
Supports pharmacokinetic and pharmacodynamic modelling and simulation, including non-compartmental analysis, population PK, exposure-response, bioequivalence, and dosing regimen evaluation from concentration-time data.
At a glance
| Publisher | K-Dense-AI |
|---|---|
| Repository | K-Dense-AI/claude-scientific-skills (177 listed skills) |
| Category | Science and Research |
| License | MIT |
| Last commit | October 12, 2026 (repository) |
| SKILL.md | 266 lines, 2,108 words |
| Bundled files | 28 files, including references, scripts, assets or templates |
| Quality score | 88/100 · B Passes all seven graded checks |
| Security scan | Not scanned |
| README badge | Get the badges for this listing |
Before you install
Read from the skill's files at the directory's October 19, 2026 snapshot: what ships with it, what its code reads, and the terms it is published under.
- Bundled scripts: 11 script files (11 Python). Your agent may run them, so read them first.
- Tool permissions requested:
Read Write Edit Bash(theallowed-toolsfield of SKILL.md). - License: MIT, an open-source or open-content license.
Install pkpd-modeling
The skills CLI works with Claude Code, Codex, Cursor and other agents; the other routes copy the folder by hand.
npx skills add https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/skills/pkpd-modelingtmp="$(mktemp -d)"
git clone --depth 1 https://github.com/K-Dense-AI/claude-scientific-skills.git "$tmp/repo"
mkdir -p .claude/skills
cp -R "$tmp/repo/"skills/pkpd-modeling .claude/skills/
rm -rf "$tmp"python3 ~/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py \
--repo K-Dense-AI/claude-scientific-skills \
--path skills/pkpd-modelingK-Dense-AI/claude-scientific-skills is third-party code. Read SKILL.md and any bundled scripts before you install it.
How the author describes it
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".
From the description field of SKILL.md. Agents read this line to decide when to load the skill.
Compatibility, from SKILL.md
| Compatibility | Requires Python 3.12+ with NumPy 2+ and SciPy. No network access and no proprietary software. The estimation tools this skill orients you towards (NONMEM, Monolix, Phoenix, Simcyp, GastroPlus) are… |
|---|
Sections in SKILL.md
- When to use
- Fix the question and conventions first
- Environment and output
- Workflow
- 1. Non-compartmental analysis
- 2. Individual compartmental fitting
- 3. Population PK
- 4. Regimen simulation
- 5. Exposure-response and QT
- 6. Bioequivalence
- 7. Scaling and first-in-human orientation
- 8. Drug interaction screening
- 9. Research therapeutic drug monitoring
- Software, provenance and specialist references
- Citing Scientific Agent Skills
Files in the skill folder
SKILL.mdassets/nca-reporting-checklist.mdassets/popk-analysis-plan.mdreferences/antimicrobial-and-tdm.mdreferences/bioequivalence.mdreferences/dataset-standards.mdreferences/ddi-and-qt.mdreferences/nca-conventions.mdreferences/pbpk.mdreferences/pd-and-exposure-response.mdreferences/population-pk.mdreferences/regulatory-guidance.mdreferences/software-ecosystem.mdreferences/source-ledger.mdreferences/special-populations.mdreferences/structural-models.mdreferences/tmdd-and-biologics.mdscripts/_common.pyscripts/_models.pyscripts/allometry_and_fih.pyscripts/bioequivalence.pyscripts/check_popk_dataset.pyscripts/ddi_static.pyscripts/exposure_response.py
Showing 24 of 28 files. Browse the folder on GitHub.
Suede Skill Check: 88/100 · B
Report snapshot · · graded-v2
The rubric totals 100 points; published scores are capped at 99. Security scan: not scanned.
Source revision: a1043ef544e3. Report version 745458690bee. Badge URLs follow the latest listing; save the report to keep this version.
Download report · Request a fresh review
What to review next
- Description length: 1 of 5 points. 5 for 150–600 characters; 3 for 100–900; 1 for 50–1,024.
- Boundary clause: 0 of 4 points. 4 when the description says when not to use the skill (“Not for …”, “Do not use …”, “Use … instead”).
Add declarations and bundled files when they describe the skill’s actual needs. Update the source, then request a fresh review with the changed commit or PR.
pkpd-modeling passes the required frontmatter check and all seven graded checks, which cover the SKILL.md format, a declared license and a commit in the last year. Those checks earn 56 of the score’s points; the rest come from description quality, instruction depth, bundled files, maintenance and curated-list citations. How the score works.
See the checks and points
| Check | Result |
|---|---|
| Frontmatter parses and declares a name and a description | Pass |
| Name uses lowercase letters, digits and hyphens, 64 characters or fewer | Pass |
| Name matches the skill's folder name | Pass |
| Description is between 50 and 1,024 characters | Pass |
| Description says when an agent should use the skill | Pass |
| SKILL.md body is 500 lines or fewer | Pass |
| A license is declared in the frontmatter or the repository | Pass |
| Repository has a commit in the last 12 months | Pass |
| Score component | Points |
|---|---|
| Structural checks | 56 of 56 |
| Description length | 1 of 5 |
| Boundary clause | 0 of 4 |
| Example request | 3 of 3 |
| Instruction depth | 7 of 7 |
| Reference files | 3 of 3 |
| Bundled scripts | 2 of 2 |
| Recent maintenance | 9 of 9 |
| Curated-list citations | 3 of 7 |
| Tool permissions declared | 2 of 2 |
| Compatibility declared | 2 of 2 |
Two badges for pkpd-modeling
Choose the numeric badge, the letter badge, or both. Each links to this skill’s Suede listing; either valid linked badge can qualify for the feature offer.
[](https://skills.suedeai.ai/directory/k-dense-ai/claude-scientific-skills/pkpd-modeling/)
[](https://skills.suedeai.ai/directory/k-dense-ai/claude-scientific-skills/pkpd-modeling/)<a href="https://skills.suedeai.ai/directory/k-dense-ai/claude-scientific-skills/pkpd-modeling/"><img src="https://skills.suedeai.ai/directory/k-dense-ai/claude-scientific-skills/pkpd-modeling/score.svg" alt="Suede Skill Check: 88/100" width="160" height="175"></a>
<a href="https://skills.suedeai.ai/directory/k-dense-ai/claude-scientific-skills/pkpd-modeling/"><img src="https://skills.suedeai.ai/directory/k-dense-ai/claude-scientific-skills/pkpd-modeling/badge.svg" alt="Suede Skill Check: Grade B" width="160" height="175"></a>Suede Certified on the shield refers to this published structural quality check. Security scan: not scanned. Read the methodology.
Limited-time feature offer: display either the numeric or letter badge in your repository or skill README (both also qualify), then request badge verification. Eligible skills scoring 80–99 can receive a featured placement after Suede verifies at least one valid badge linked to the skill’s listing. Suede has not announced an end date.
Where this skill is cited
K-Dense-AI/claude-scientific-skills appears in 2 curated lists: BehiSecc/awesome-claude-skills, travisvn/awesome-claude-skills.