Goonaseelan Colin Pillai

PubMed2006

Variability in the population pharmacokinetics of pyrazinamide in South African tuberculosis patients.

OBJECTIVE: This study was designed to characterize the population pharmacokinetics of pyrazinamide in South African pulmonary tuberculosis patients, with special reference to interindividual and interoccasional variability (IIV and IOV, respectively). METHODS: Concentration-time measurements obtained from 227 patients receiving oral doses of pyrazinamide were pooled to create a dataset containing 3,092 data points spanning multiple dosing occasions. The software program NONMEM was used to analyze the data. RESULTS: A one-compartment model with first-order absorption, including a zero-order component describing release from formulation, and first-order elimination best described the data. The absorption rate constant was estimated to be bimodally distributed between two distinct subgroups, fast and slow, in approximately even proportion. Absorption rate was threefold greater in fast absorbers (3.56 h(-1)) in comparison to slow absorbers (1.25 h(-1)). Typical values of oral clearance and apparent volume of distribution were estimated as 3.42 L h(-1) and 29.2 l, respectively. IOV was supported in oral clearance (0.0238, variance) and absorption rate (0.623, variance). The duration of zero-order absorption was estimated as 0.290 h, and was quite variable between patients (0.957, variance). CONCLUSION: The absorption of pyrazinamide in the studied population was highly variable and two separate subpopulations were identified. IOV accounted for a proportion of the variability in clearance and the absorption rate constant.

Absorption↗

PubMed2005

Non-linear mixed effects modeling - from methodology and software development to driving implementation in drug development science.

Few scientific contributions have made significant impact unless there was a champion who had the vision to see the potential for its use in seemingly disparate areas-and who then drove active implementation. In this paper, we present a historical summary of the development of non-linear mixed effects (NLME) modeling up to the more recent extensions of this statistical methodology. The paper places strong emphasis on the pivotal role played by Lewis B. Sheiner (1940-2004), who used this statistical methodology to elucidate solutions to real problems identified in clinical practice and in medical research and on how he drove implementation of the proposed solutions. A succinct overview of the evolution of the NLME modeling methodology is presented as well as ideas on how its expansion helped to provide guidance for a more scientific view of (model-based) drug development that reduces empiricism in favor of critical quantitative thinking and decision making.

Algorithms↗