Supporting a data-driven approach to regulatory intelligence
Author:
Publisher
Springer Science and Business Media LLC
Subject
Drug Discovery,Pharmacology,General Medicine
Link
http://www.nature.com/articles/d41573-020-00101-4.pdf
Reference5 articles.
1. Kieffer, C. M. et al. FDA reported use of patient experience data in 2018 drug approvals. Ther. Innov. Reg. Sci. https://doi.org/10.1177/2168479019871519 (2019).
2. Kieffer, C. M., Robertson, A. S. Impact of FDA-required cardiovascular outcome trials on type 2 diabetes clinical study initiation from 2008 to 2017. Ther. Innov. Reg. Sci. https://doi.org/10.1177/2168479019860122 (2019).
3. Hu, M., et al. Predictive analysis of first abbreviated new drug application submission for new chemical entities based on machine learning methodology. Clin. Pharmacol. Ther. 106, 174–181 (2019).
4. Daniel, G. W. et al. Improving pharmaceutical innovation by building a more comprehensive database on drug development and use. Health Aff. 34, 319–227 (2015).
5. Audibert, C. et al. Building a drug development database: challenges in reliable data availability. Drug. Dev. Ind. Pharm. https://doi.org/10.1080/03639045.2016.1220565 (2017).
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