著者

猪川 和朗

出版者

一般社団法人日本医療薬学会

雑誌

医療薬学 (ISSN:1346342X)

巻号頁・発行日

vol.42, no.5, pp.305-316, 2016-05-10 (Released:2017-05-10)

参考文献数

54

被引用文献数

1

---

So-called pharmacometrics were used for information creation and decision-making in the drug development and drug approval process. However, for individualized drug therapy in clinical settings, pharmacometrics were not fully utilized. Therefore, our research group has defined, as “clinical pharmacometrics”, clinical contribution to decision-making in individualized drug therapy, especially with dosage optimization support and adverse effects management, by pharmacist-led quantitative analysis, evaluation and prediction using mathematical statistical methods. We show here some examples of practicing clinical pharmacometrics. In the case of supporting meropenem dosage optimization, we developed a population pharmacokinetic model and then performed random simulation to predict the efficacy of dosages (the drug exposure time above the minimum inhibitory concentration) by employing a probabilistic approach considering the variation of the patient and bacteria. The optimized meropenem dosage achieved favorable outcome. In the case of managing adverse effects of voriconazole, we developed a population pharmacogenomic-pharmacokinetic model and a logistic pharmacodynamic model, and then performed simulation to predict the safety of dosages (the hepatotoxic effects). These results optimized the voriconazole dosage according to the body weight and CYP2C19 genotype of the patient, considering the hepatotoxicity probability. As in these examples, for optimal drug therapy in individual patients, pharmacists need to practice clinical pharmacometrics by repeating the cycle of processes: clinical data measurement in the medical setting, acquisition of quantitative pharmaceutical knowledge, and provision of therapeutic benefits to patients.

著者

猪川 和朗 田中 潤

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.36, no.Special_Issue, pp.S3-S18, 2015-06-30 (Released:2015-09-08)

参考文献数

10

被引用文献数

1

---

We describe fundamental knowledge of pharmacokinetics analysis for phase I trials, particularly focusing on basic parameters (such as bioavailability, volume of distribution, fraction unbound, clearance), estimation and analysis methods (such as compartmental and non-compartmental), points to consider (such as steady state and dose proportionality). The NCA is an abbreviation for Non Compartmental Analysis, and the meaning is pharmacokinetic analysis without pharmacokinetic model. There is something that we should consider in NCA such as AUC calculation method, handling method of not detectable concentrations, point selection for λz calculation, and selection of sampling time. Steady state occurs when the overall intake of a drug is equilibrium with its elimination. At steady state the mean plasma concentrations of the drug are similar by any dosing interval. In practice, it is generally considered that steady state is reached when a time of 5 times the half-life for a drug. For the dose proportionality, the measures of exposure, such as maximal blood concentration (Cmax), area under the curve from 0 to infinity (AUC), are proportional to the dose. The three methods, Analysis of variance of the PK response, normalized by dose, linear regression and power model, are used to assess dose proportionality.