benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, published in Cell Patterns 2022.
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Updated
Jun 24, 2025 - Python
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
Winning solution of the Novartis Data Science and Artificial Intelligence 2019/2020 competition
PIPET 수련생을 위한 실습교육자료입니다. (R, NCA, Rmarkdown, data science, 임상시험, 약동학/약력학, 논문발표 등)
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
Non-compartmental pharmacokinetics analysis for Julia.
“Just because we are not ready for scientific progress does not mean it won’t happen.” - Jennifer A. Doudna
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!
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.
📝 2016, 2017, 2018, 2019 서울아산병원 임상약리학과에 실습 나온 것을 환영합니다. 서브인턴들의 교육을 위해 필요한 자료를 모아두었습니다.
R package for translating between drug identifiers using the Chemical Translation Service (CTS)
Implementing AI in the Clinical Trial Process for Drug Development
Duke AIPI 520 Project 2 • Predicting Monoclonal Antibody Clinical Trial Success
Development version of ph2rand, an R package for the design of randomized comparative phase II oncology trials
가톨릭대학교 의과대학 약리학교실, Department of Pharmacology, College of Medicine http://pharmacology.catholic.ac.kr
Clinical trial patient retention simulator. Predicts dropout risk using behavioral decay modeling. Saves CROs millions in trial delays. Enterprise-ready.
chemical viewer
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