Comprehensive analysis of influencing factor of effect/adverse effect for anti-cancer drug using virtual clinical study

2017 Fiscal Year Final Research Report

• Project/Area Number: 16K18972
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Medical pharmacy
• Research Institution: Institute of Physical and Chemical Research
• Principal Investigator: Toshimoto Kota 国立研究開発法人理化学研究所, イノベーション推進センター, 特別研究員 (70740504)
• Project Period (FY): 2016-04-01 – 2018-03-31
• Keywords: 薬物動態学 / モデリング＆シミュレーション / 遺伝子多型 / 仮想臨床試験

Outline of Final Research Achievements

Various factors such as genetic polymorphism, which leading pharmacological and toxicological effects of anti-cancer drugs, are reported among clinical studies. The aim of this research is to predict what factor is the most effective using computational virtual clinical study (VCS). Mathematical models are required to perform VCS. Because the mathematical models of anti-cancer drugs are complicated, the conventional parameter estimation method could not be applied. To overcome this problem, a new parameter optimization algorithm were newly introduced. The mathematical models which can be reproduced clinical observed plasma concentration-time profiles of drug were successfully obtained. By performing VCS, we could quantitatively predict how many times the statistical significance for each genetic polymorphism.

Free Research Field

薬物動態学