Literature DB >> 31925955

Application of Machine Learning in Drug Development and Regulation: Current Status and Future Potential.

Qi Liu1, Hao Zhu1, Chao Liu1, Daphney Jean1, Shiew-Mei Huang1, M Khair ElZarrad2, Gideon Blumenthal3, Yaning Wang1.   

Abstract

Year:  2020        PMID： 31925955     DOI： 10.1002/cpt.1771

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN： 0009-9236            Impact factor:   6.875


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  9 in total

1.  "Artificial Intelligence" for Pharmacovigilance: Ready for Prime Time?

Authors:  Robert Ball; Gerald Dal Pan
Journal:  Drug Saf       Date:  2022-05-17       Impact factor: 5.228

2.  Application of Machine Learning in Translational Medicine: Current Status and Future Opportunities.

Authors:  Nadia Terranova; Karthik Venkatakrishnan; Lisa J Benincosa
Journal:  AAPS J       Date:  2021-05-18       Impact factor: 4.009

3.  Application of Machine Learning for Tumor Growth Inhibition - Overall Survival Modeling Platform.

Authors:  Phyllis Chan; Xiaofei Zhou; Nina Wang; Qi Liu; René Bruno; Jin Y Jin
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2020-12-13

4.  Clinical Pharmacology Regulatory Sciences in Drug Development and Precision Medicine: Current Status and Emerging Trends.

Authors:  Qi Liu; Mitra Ahadpour; Mitra Rocca; Shiew-Mei Huang
Journal:  AAPS J       Date:  2021-04-12       Impact factor: 4.009

5.  Population pharmacokinetic model selection assisted by machine learning.

Authors:  Emeric Sibieude; Akash Khandelwal; Pascal Girard; Jan S Hesthaven; Nadia Terranova
Journal:  J Pharmacokinet Pharmacodyn       Date:  2021-10-27       Impact factor: 2.745

Review 6.  Review: Role of Model-Informed Drug Development Approaches in the Lifecycle of Drug Development and Regulatory Decision-Making.

Authors:  Rajanikanth Madabushi; Paul Seo; Liang Zhao; Million Tegenge; Hao Zhu
Journal:  Pharm Res       Date:  2022-05-12       Impact factor: 4.580

7.  Neural-ODE for pharmacokinetics modeling and its advantage to alternative machine learning models in predicting new dosing regimens.

Authors:  James Lu; Kaiwen Deng; Xinyuan Zhang; Gengbo Liu; Yuanfang Guan
Journal:  iScience       Date:  2021-06-30

8.  Pharm-AutoML: An open-source, end-to-end automated machine learning package for clinical outcome prediction.

Authors:  Gengbo Liu; Dan Lu; James Lu
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2021-05-02

Review 9.  Digital Progression Biomarkers as Novel Endpoints in Clinical Trials: A Multistakeholder Perspective.

Authors:  Diane Stephenson; Reham Badawy; Soania Mathur; Maria Tome; Lynn Rochester
Journal:  J Parkinsons Dis       Date:  2021       Impact factor: 5.568
  9 in total

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