Publication: Towards optimal design of anti-malarial pharmacokinetic studies
Issued Date
2009-09-04
Resource Type
ISSN
14752875
Other identifier(s)
2-s2.0-69449095133
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Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Malaria Journal. Vol.8, No.1 (2009)
Suggested Citation
Julie A. Simpson, Kris M. Jamsen, Ric N. Price, Nicholas J. White, Niklas Lindegardh, Joel Tarning, Stephen B. Duffull Towards optimal design of anti-malarial pharmacokinetic studies. Malaria Journal. Vol.8, No.1 (2009). doi:10.1186/1475-2875-8-189 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/27662
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Title
Towards optimal design of anti-malarial pharmacokinetic studies
Abstract
Background. Characterization of anti-malarial drug concentration profiles is necessary to optimize dosing, and thereby optimize cure rates and reduce both toxicity and the emergence of resistance. Population pharmacokinetic studies determine the drug concentration time profiles in the target patient populations, including children who have limited sampling options. Currently, population pharmacokinetic studies of anti-malarial drugs are designed based on logistical, financial and ethical constraints, and prior knowledge of the drug concentration time profile. Although these factors are important, the proposed design may be unable to determine the desired pharmacokinetic profile because there was no formal consideration of the complex statistical models used to analyse the drug concentration data. Methods. Optimal design methods incorporate prior knowledge of the pharmacokinetic profile of the drug, the statistical methods used to analyse data from population pharmacokinetic studies, and also the practical constraints of sampling the patient population. The methods determine the statistical efficiency of the design by evaluating the information of the candidate study design prior to the pharmacokinetic study being conducted. Results. In a hypothetical population pharmacokinetic study of intravenous artesunate, where the number of patients and blood samples to be assayed was constrained to be 50 and 200 respectively, an evaluation of varying elementary designs using optimal design methods found that the designs with more patients and less samples per patient improved the precision of the pharmacokinetic parameters and inter-patient variability, and the overall statistical efficiency by at least 50%. Conclusion. Optimal design methods ensure that the proposed study designs for population pharmacokinetic studies are robust and efficient. It is unethical to continue conducting population pharmacokinetic studies when the sampling schedule may be insufficient to estimate precisely the pharmacokinetic profile. © 2009 Simpson et al; licensee BioMed Central Ltd.