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Year : 2019  |  Volume : 51  |  Issue : 1  |  Page : 17-24

Population pharmacokinetics of primaquine and the effect of hepatic and renal dysfunction: An exploratory approach

1 Department of Clinical Pharmacology, Seth GS Medical College and KEM Hospital, Mumbai, Maharashtra, India
2 GVK Biosciences Private Limited, Hyderabad, Telangana, India
3 Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal University, Manipal, Karnataka, India
4 Department of Nephrology, Seth GS Medical College and KEM Hospital, Mumbai, Maharashtra, India
5 Department of Gastroenterology, Seth GS Medical College and KEM Hospital, Mumbai, Maharashtra, India

Correspondence Address:
Dr. Urmila Thatte
Department of Clinical Pharmacology, Seth GS Medical College and KEM Hospital, Parel, Mumbai - 400 012, Maharashtra
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijp.IJP_230_16

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OBJECTIVES: We attempted to develop a population pharmacokinetic model for primaquine (PQ) and evaluate the effect of renal and hepatic dysfunction on PQ pharmacokinetics. MATERIALS AND METHODS: The data were collected from a prospective, nonrandomized clinical study in healthy volunteers and patients with mild-moderate hepatic dysfunction and renal dysfunction. Model development was conducted using NONMEM® software, and parameter estimation was conducted using first-order conditional estimation with interaction method. RESULTS: Final data included a total of 53 study participants (13 healthy individuals, 12 with mild hepatic dysfunction, 6 with moderate hepatic dysfunction, and 22 with renal dysfunction) with 458 concentrations records. Absorption rate constant (Ka) was constrained to be higher than elimination rate constant to avoid flip-flop situation. Mild hepatic dysfunction was a significant covariate on volume of distribution, and it is approximately three folds higher compared to other subjects. Fixed effects parameter estimates of the final model – absorption rate constant (Ka), volume of distribution (V), and clearance (CL) – were 0.95/h, 498 L, and 39 L/h, respectively. Between-subject variability estimates (% CV) on Ka, V, and CL were 77, 66, and 65, respectively. Residual error was modeled as combination error model with the parameter estimates for proportion error 12% CV and additive error (standard deviation) 1.5 ng/ml. CONCLUSION: Population pharmacokinetic modeling showed that the volume of distribution of PQ in subjects with moderate hepatic dysfunction increases approximately three folds resulting in a significantly lower plasma concentration.


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