drug-development

benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, published in Cell Patterns 2022.

PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development

Awesome list of the data and AI/ML related projects with direct Life Science Companies participation

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

Winning solution of the Novartis Data Science and Artificial Intelligence 2019/2020 competition

Drugs Explained is an open-source book takes the mystery out of medications. Learn how drugs are developed, how they work inside your body, and what all that fine print on medication labels really means. Finally understand the science behind your medicine cabinet!

Modernized Flexible Artificial Intelligence Docking (FlexAID) fully flexible, in C++26 with python bindings. Updated NRGsuite, the PyMOL plugin GUI. Fast, Flexible and Free... and it ain't GROMACS 😹😻✨

A curated list of awesome lists on Machine Learning for Drug Discovery

iterative process using two ML models to generate the best inhibitors for a target protein

“Just because we are not ready for scientific progress does not mean it won’t happen.” - Jennifer A. Doudna

Non-compartmental pharmacokinetics analysis for Julia.

Turn any AI agent into a clinical pharmacologist and pharmacometrician. It reviews, reconciles, and prepares evidence. It never selects a dose, signs off, or submits.

Description of work done at Merck pharmaceutical company in the summer of 2018 as a Computational Drug Discovery Intern at West Point, PA. Information excludes all proprietary information belonging to Merck & Co.

GCP合规Skill — 基于中国GCP 2026修订版的 Cursor Agent 合规判定技能

MNC-style pharmaceutical pipeline asset assessment Agent Skill

R package for translating between drug identifiers using the Chemical Translation Service (CTS)

A clean Python library for the ClinicalTrials.gov API

📝 2016, 2017, 2018, 2019 서울아산병원 임상약리학과에 실습 나온 것을 환영합니다. 서브인턴들의 교육을 위해 필요한 자료를 모아두었습니다.

A Python library for automated PK/PD ODE model identification from concentration–time data. Selects the compartmental structure, estimates parameters, and flags identifiability problems; no model specification or starting values required.