An R package is designed to perform all noncompartmental analysis (NCA) calculations for pharmacokinetic (PK) data.

PIPET 수련생을 위한 실습교육자료입니다. (R, NCA, Rmarkdown, data science, 임상시험, 약동학/약력학, 논문발표 등)

📖 책: R을 사용한 비구획분석과 생물학적동등성 평가, 2020. https://asancpt.github.io/book-ncar

2019 EDISON 경진대회 대상 수상작: Edison App: Bioequivalence Study Data Analysis https://asancpt.github.io/BE-apps

☀️ Shinyapp: PK Simulation - 1-comp intravenous administration. https://asan.shinyapps.io/pk1c

R code for manuscript: Hughes JH, Upton RN, Reuter SE, Phelps MA, Foster DJR. Optimising time samples for determining AUC of pharmacokinetic data using non-compartmental analysis. - Web App can be found at:

Validation of Noncompartmental Analysis Performed by NonCompart R package https://asancpt.github.io/NonCompart-tests/validation_0.4.4.pdf

Edison App: pk1cEdison:

📖 Book: R packages for Noncompartmental Analysis, 2018. https://asancpt.github.io/book-ncar-en

😩 OBSOLETE! R package: Noncompartmental Analysis of Pharmacokinetic Data for CDISC Standardized Parameters

R을 통한 비구획분석 ncar 실습 교재입니다. https://asancpt.github.io/handout

Raw R code used in manuscript: Hughes JH, Upton RN, Foster DJR. Comparison of non-compartmental and mixed effect modelling methods for establishing bioequivalence for the case of two compartment kinetics and censored concentrations. J Pharmacokinet Pharmacodyn. 2017:1-12.

Raw R code for manuscript: Hughes JH, Upton RN, Reuter SE, Phelps MA, Foster DJR. Optimising time samples for determining AUC of pharmacokinetic data using non-compartmental analysis.

Open Python Web App for Pharmcological Modeling and Analysis