Population Pharmacokinetics of Pioglitazone in South Indian Type-II Diabetic Patients

Authors

  • MAHENDER VATTIPALLI Department of Pharmacology and Clinical Pharmacy,University College of Pharmaceutical Sciences, Kakatiya University, Warangal – 506 009, Andhra Pradesh, INDIA.
  • DEVENDER KODATI
  • NARSIMHA REDDY YELLU

Abstract

Introduction: Population pharmacokinetics (PPK) is the study of this variability, its source and magnitude in populations. This information is used
to design dosage regimens that account for individual patient characteristics.
Objective: The objective of this study was to perform a non-linear mixed-effects analysis of the pharmacokinetics of pioglitazone, indicated for
treating diabetes and to study the effect of covariates such as age, body surface area and creatinine clearance on the PPK of pioglitazone in South
Indian diabetic patients.
Materials and Methods: A simple, rapid, and sensitive isocratic high-performance liquid chromatography-ultra violet method for detection and
quantification of pioglitazone in plasma had been developed. Intra- and inter-assay variations were <1 and <2% respectively. Recovery of pioglitazone
was 98-99%. A total of 137 blood samples for pioglitazone plasma concentration measurements following a single 15 mg dose of pioglitazone were
obtained from 43 subjects having age in between 18 and 75 years. The PPK model was built using NONMEM 7.2.0. The first-order (FO) and first-order
conditional estimation (FOCE) method was used to estimate base and covariate models for pioglitazone.
Results: One-compartment model with FO absorption and elimination (ADVAN 2 TRANS 2) was best-fit to the plasma concentration-time data
of pioglitazone. A combined error model was best-described the pattern of residual and between subject variability. The final model estimates of
clearance (CL) and volume (V) estimated by FOCE method were 3.4 lt/hr and 43 L.
Discussion: There were no past reports on PPK of pioglitazone. With covariate models, a significant decrease was observed in object function value,
between and within subject variability when compared with base model. The model found to best describe the data following the FOCE method was:
CL=CL=θ1*EXP ([η1] and V=θ2*EXP [η2]). These parameters are utilized for individualizing the loading and maintenance doses in diabetic patients.
No factor was found as informative covariate of pioglitazone.
Conclusion: In order to minimize the variability associated with drug exposure in Indian diabetic patients, the population parameter estimates were
given without influence of covariates.

Keywords: Covariate, Creatinine clearance, NONMEM, Pioglitazone, Residual variability.

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Published

2014-09-01

How to Cite

VATTIPALLI, M., D. KODATI, and N. R. YELLU. “Population Pharmacokinetics of Pioglitazone in South Indian Type-II Diabetic Patients”. Asian Journal of Pharmaceutical and Clinical Research, vol. 7, no. 4, Sept. 2014, pp. 102-5, https://innovareacademics.in/journals/index.php/ajpcr/article/view/1442.

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