1988 Fiscal Year Final Research Report Summary
Basic research on the population pharmacokinetics and individualization of dosage of drug
| Project/Area Number |
61480440
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| Research Category |
Grant-in-Aid for General Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
応用薬理学・医療系薬学
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| Research Institution | Hamamatsu University School of Medicine |
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Principal Investigator |
NAKASHIMA Mitsuyoshi Department of Pharmacology Hamamatsu University School of Medicine, 医学部, 教授 (00092982)
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| Co-Investigator(Kenkyū-buntansha) |
TAKIGUCHI Yoshiharu Department of Pharmacology Hamamatsu University School of Medicine, 医学部, 助教授 (40163349)
UEMATSU Toshihiko Department of Pharmacology Hamamatsu University School of Medicine, 医学部, 助教授 (50151832)
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| Project Period (FY) |
1986 – 1987
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| Keywords | Population pharmacokinetics / Bayesian method / lidocaine / リドカイン / NONMEM |
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| Research Abstract |
Population pharmacokinetic approach for individual dosage adjustment was evaluated in Japanese patients' population. In the first year a computer program NONMEM (non-linear mixed effect model) for population pharmacokinetics was transplanted in our large computer. and a Bayesian program in a microcomputer for individualization of drug dosage was composed. In addition, caffeine, which we consume in every-day life as beverages, was discussed as a possible marker for estimating the individual hepatic clearance of drug. For this purpose we have devised a new collecting method of saliva instead of blood for drug monitoring.
In the second year we evaluated patient population pharmacokinetic parameters of lidocaine, which is mainly by the liver, and new aminoglycoside antibiotics (astromicin and isepamicin), which are mainly excreted as unchanged drug from the kidney, with use of the NONMEM. After obtaining the means and variances of parameters we tried to adjust the dosage of drug prospectively in other patients of the same population in order to clarify the applicability of the Bayesian approach. In both types of drugs the Bayesian approach was proved to be sufficiently accurate and precise, and to be practically useful for individual dosage adjustment.
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Research Products
(13 results)
