Establishment of personalized therapy with molecularly targeted anticancer drugs based on next-generation sequencing and PK/PD models

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K06708
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 47060:Clinical pharmacy-related
• Research Institution: Akita University (2023); Tohoku University (2021-2022)
• Principal Investigator: Masafumi Kikuchi 秋田大学, 医学部附属病院, 教授 (90420025)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Keywords: がんクリニカルシーケンス / 分子標的抗がん薬 / PK/PD / Modeling & Simulation / 個別化医療

Outline of Final Research Achievements

To establishment of personalized therapy with molecularly targeted anticancer drugs based on next-generation sequencing and pharmacokinetic/pharmacodynamic (PK/PD) models, we developed a quantification method for oral molecularly targeted anticancer drugs using high-performance liquid chromatography/tandem mass spectrometry (LC-MS/MS). Using this quantification method, we determined the association between blood lenvatinib concentration and adverse events in hepatocellular carcinoma, the prediction accuracy of blood lenvatinib concentration using nonlinear mixed effects model (NONMEM), and the association between blood imatinib concentration and antitumor effect in glioma patients with activating mutations of platelet derived growth factor receptor alpha (PDGFRA).

Free Research Field

医療薬学

Academic Significance and Societal Importance of the Research Achievements

LC-MS/MSを用いた20種の経口分子標的抗がん薬とその代謝物のハイスループットな一斉定量法は、汎用性が高く、臨床だけでなく、多くの研究に活用することが可能である。また、NONMEMを用いて、様々ながん種における血中レンバチニブ濃度を予測できる可能性を明らかにしたことは、がんクリニカルシーケンスと分子標的抗がん薬のPK/PDモデルに基づく個別化医療の確立に大きく貢献することが期待される。