2006 Fiscal Year Final Research Report Summary
Development of clinical genome information systems for pharmacokinetics analysis
| Project/Area Number |
16200038
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Medical systems
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| Research Institution | The University of Tokyo |
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Principal Investigator |
OYAMA Hiroshi The University of Tokyo, Faculty of Medicine, Project Professor, 医学部附属病院, 科学技術振興特任教員(特任教授) (30194640)
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| Co-Investigator(Kenkyū-buntansha) |
SASAKI Yasutsuna Saitama Medical School, Department of Clinical Oncology, Professor, 臨床腫瘍科, 教授 (20235279)
ANDO Yuichi Nagoya University Hospital, Department of Clinical Oncology and Chemotherapy, Assistant Professor, 医学部附属病院, 助教授 (10360083)
ONOGI Yuzo The University of Tokyo, Faculty of Medicine, Project Associate Professor, 医学部附属病院, 科学技術振興特任教員(特任助教授) (90233593)
KOIDE Daisuke The University of Tokyo, Faculty of Medicine, Project Associate Professor, 医学部附属病院, 科学技術振興特任教員(特任助教授) (50313143)
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| Project Period (FY) |
2004 – 2006
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| Keywords | pharmacokinetics / anti-cancer drug / polymorphism / individual medicine / grid computing / data base / drug adverse reaction / search |
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| Research Abstract |
We developed a clinical genome information grid search system that can extract comprehensive drug-related information from two or more life-science databases (DBs) using OGSA-WebDB technology, which is a database grid technology. The retrieval DBs are TOXINET (an adverse-drug-reaction document information DB), PharmGKB (a drug-related gene DB), Entrez Protein (a protein information DB), LSBM (a gene-expression organ DB), KEGG (a pathway-information DB), and JSNP (a single nucleotide polymorphism (SNP) information DB). The system can extract references to the newest drug responsibility genes and organs, metabolic pathway data, and protein information relevant to adverse reactions to anti-cancer or other drugs, and researchers can estimate the causal relationships between a drug responsibility gene and an adverse drug reaction. Using this, we verified the adverse drug reaction between irinotecan hydrochloride and cisplatin in combination therapy. The common pathways are the ABC transporters that are involved in the metabolism of xenobiotics by cytochrome P450, and starch and sucrose metabolism and 56 SNPs were extracted as relevant polymorphisms. A pharmacokinetics analysis algorithm for irinotecan hydrochloride was created based on clinical case data. We developed a clinical genome pharmacokinetics simulation system in which the chronological concentration change of CPT-11, SN-38, and SN-38G in each compartment can be visualized as a graph after selecting the genotype (wild-type, heterozygote, homozygote), body height, weight, and actual drug dose. It can also simulate the UGT1A1 allele type patterns of ^*28 and ^*6. We propose the system specifications for a clinical genome information-management system that includes clinical genome data, patient case data, and pharmacokinetics data. The prototype system was developed using Apache2.2.0, PHP5.1.1, MySQL5.0.18, and Java programming language on a UNIX server.
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