Building of the equation predict an optimal condition for drug analysis in biological sample

2014 Fiscal Year Final Research Report

• Project/Area Number: 24590850
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Legal medicine
• Research Institution: The University of Tokyo
• Principal Investigator: SAKA Kanju 東京大学, 医学(系)研究科(研究院), 技術専門職員 (30447388)
• Co-Investigator(Renkei-kenkyūsha): YOSHIDA Ken-ichi 東京医科大学, 医学科, 教授 (40166947) ; SHINTANI Kaori (ISHIDA Kaori) 京都府立医科大学, 大学院医学研究科, 准教授 (50345047)
• Project Period (FY): 2012-04-01 – 2015-03-31
• Keywords: 薬毒物分析 / 定量的構造物性（活性）相関 / 予測モデル / 法医学 / 生体試料

Outline of Final Research Achievements

We developed the predictive model for the phenomenon "matrix enhancement effect" in gas chromatography-mass spectrometry. The model was built using quantitative structure-property relationship (QSPR). The predictive equation allows the matrix-effect prediction without experimental measurements. In addition, the parameters such as "the number of H-bond donors" and "molecular volume" were found to be significant in this phenomenon.

Free Research Field

分析化学