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rangching/taiwan-scientific-agent-skills

v1.1.0MIT

臺灣學術界適用的繁體中文科學 Agent Skills 庫(中英雙語對照),衍生自 K-Dense Scientific Agent Skills。Ready-to-use scientific Agent Skills for Taiwan academia (zh-Hant-TW / English).

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".

Version
1.2
License
MIT
Compatibility
Requires Python 3.11+ with numpy and scipy. No network access and no proprietary software. The estimation tools this skill orients you towards (NONMEM, Monolix, Phoenix, Simcyp, GastroPlus) are licensed separately and are never invoked by these scripts.
Read SKILL.md at the source

Pinned to revision 70a605012eee, so it is the text this page describes rather than whatever the author pushed since.

Pre-approved tools experimental

Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.

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