1. Development of an integrated database
Information on thousands of drug compounds from public databases were extracted and all the relevant pharmacokinetic data on these compounds were collected. We also acquired both in vitro and in vivo experimental data. The database schema for integrating the public and in-house data were created. The database is going to opened to the public.
2. Construction of an in silico model for predicting pharmacokinetic parameters
We aimed to construct a structure-activity relationship model for predicting physicochemical properties of compounds from their chemical structures.
1) fu,p (fraction unbound in plasma)
2) fu,b (fraction unbound in brain homogenate)
1) Esaki, T.; Watanabe, R.; Kawashima, H.; Ohashi, R.; Natsume-Kitatani, Y.; Nagao, C.; Mizuguchi, K., Data curation can improve the prediction accuracy of metabolic intrinsic clearance. Mol. Inf. 2018, 37, 1800086
2) Watanabe R.; Esaki T.; Kawashima H.; Natsume-Kitatani Y.; Nagao C.; Ohashi R.; Mizuguchi K, Predicting Fraction Unbound in Human Plasma from Chemical Structure: Improved Accuracy in the Low Value Ranges. Mol Pharm. 2018, 15(11), pp5302–5311