📝 2016, 2017, 2018, 2019 서울아산병원 임상약리학과에 실습 나온 것을 환영합니다. 서브인턴들의 교육을 위해 필요한 자료를 모아두었습니다.
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Jan 23, 2019 - HTML
📝 2016, 2017, 2018, 2019 서울아산병원 임상약리학과에 실습 나온 것을 환영합니다. 서브인턴들의 교육을 위해 필요한 자료를 모아두었습니다.
Development version of ph2rand, an R package for the design of randomized comparative phase II oncology trials
Winning solution of the Novartis Data Science and Artificial Intelligence 2019/2020 competition
PharmAI are tools for Artificial intelligence in drug discovery and development
“Just because we are not ready for scientific progress does not mean it won’t happen.” - Jennifer A. Doudna
Exploring off-patent and off-exclusivity drugs without an FDA-approved generic for gener8tor.
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
PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development
Implementing AI in the Clinical Trial Process for Drug Development
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
PIPET 수련생을 위한 실습교육자료입니다. (R, NCA, Rmarkdown, data science, 임상시험, 약동학/약력학, 논문발표 등)
benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, published in Cell Patterns 2022.
Non-compartmental pharmacokinetics analysis for Julia.
A curated list of awesome lists on Machine Learning for Drug Discovery
Extends the Paper QA package for use with the author's Zotero database papers in organic chemistry, drug discovery & development, cheminformatics and the applications of machine learning to these areas
Awesome list of the data and AI/ML related projects with direct Life Science Companies participation
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