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Updated: Sep 1, 2025

Use of Rabbit Eyes in Pharmacokinetic Studies of Intraocular Drugs
Published on: July 23, 2016
Utilizing public and private sector data to build better machine learning models for the prediction of
Masataka Kuroda1, Reiko Watanabe2, Tsuyoshi Esaki3
1Artificial Intelligence Centre for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), 7-6-8, Saito-Asagi, Ibaraki, Osaka 567-0085, Japan; Discovery Technology Laboratories, Mitsubishi Tanabe Pharma Corporation, 1000, Kamoshida-cho, Aoba-ku, Yokohama, Kanagawa 227-0033, Japan.
Abstract:
One solution to compensate for the shortage of publicly available data is to collect more quality-controlled data from the private sector through public-private partnerships. However, several issues must be resolved before implementing such a system. Here, we review the technical aspects of public-private partnerships using our initiative in Japan as an example. In particular, we focus on the procedure for collecting data from multiple private sector companies and building prediction models and discuss how merging public and private sector datasets will help to improve the chemical space coverage and prediction performance. Teaser: Japan's first public-private consortium in pharmacokinetics has incorporated data from multiple pharmaceutical companies to create useful predictive models.
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