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

Non-compartmental pharmacokinetics analysis for Julia.

An iterative process that uses two machine learning models to generate the best inhibitors for a target protein to help reduce the time and cost of the drug discovery process

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

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

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.

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

가톨릭대학교 의과대학 약리학교실, Department of Pharmacology, College of Medicine http://pharmacology.catholic.ac.kr

Exploring off-patent and off-exclusivity drugs without an FDA-approved generic for gener8tor.

Development version of ph2rand, an R package for the design of randomized comparative phase II oncology trials

PharmAI are tools for Artificial intelligence in drug discovery and development

Implementing AI in the Clinical Trial Process for Drug Development