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Recent updates in the therapeutic drug monitoring (TDM) guidelines for vancomycin have rekindled interest in maximum a posteriori‐Bayesian (MAP‐Bayesian) estimation of patient‐specific pharmacokinetic parameters. To create a versatile infrastructure for MAP‐Bayesian dosing of vancomycin or other drugs, a freely available, R‐based software package, Advanced Dosing Solutions (AdDS), was created to facilitate clinical implementation of these improved TDM methods. The objective of this study was to utilize AdDS for pre‐ and post‐processing of data in order to streamline the therapeutic management of vancomycin in healthy and obese veterans. Patients from a local Veteran Affairs hospital were utilized to compare the process of full re‐estimation versus Bayesian updating of priors on healthy adult and obese patient populations for use with AdDS. Twenty‐four healthy veterans were utilized to train (14/24) and test (10/24) the base pharmacokinetic model of vancomycin while comparing the effects of updated and fully re‐estimated priors. This process was repeated with a total of 18 obese veterans for both training (11/18) and testing (7/18). Comparison of MAP objective function between the original and re‐estimated models for healthy adults indicated that 78.6% of the subjects in the training and 70.0% of the subjects in the testing datasets had similar or improved predictions by the re‐estimated model. For obese veterans, 81.8% of subjects in the training dataset and 85.7% of subjects in the testing dataset had similar or improved predictions. Re‐estimation of model parameters provided more significant improvements in objective function compared with Bayesian updating, which may be a useful strategy in cases where sufficient samples and subjects are available. The generation of bespoke regimens based on patient‐specific clearance and minimal sampling may improve patient care by addressing fundamental pharmacokinetic differences in healthy and obese veteran populations. [ABSTRACT FROM AUTHOR]

A circulatory model of granulopoiesis and its regulation is presented that includes neutrophil trafficking in the lungs, liver, spleen, bone marrow, lymph nodes, and blood. In each organ, neutrophils undergo transendothelial migration from vascular to interstitial space, clearance due to apoptosis, and recycling via the lymphatic flow. The model includes cell cycling of progenitor cells in the bone marrow, granulocyte colony‐stimulating factor (G‐CSF) kinetics and its neutrophil regulatory action, as well as neutrophil margination in the blood. From previously reported studies, 111In‐labeled neutrophil kinetic data in the blood and sampled organs were used to estimate the organ trafficking parameters in the model. The model was further developed and evaluated using absolute neutrophil count (ANC), band cell, and segmented neutrophil time course data from healthy volunteers following four dose levels of pegfilgrastim (r2 = 0.77–0.99), along with ANC time course responses following filgrastim (r2 = 0.96). The baseline values of various cell types in bone marrow and blood, as well as G‐CSF concentration in the blood, predicted by the model are consistent with available literature reports. After incorporating the mechanism of action of both paclitaxel and carboplatin, as determined from an in vitro bone marrow studies, the model reliably predicted the observed ANC time course following paclitaxel plus carboplatin observed in a phase I trial of 46 patients (r2 = 0.70). The circulatory neutrophil model may provide a mechanistic framework for predicting multi‐organ neutrophil homeostasis and dynamics in response to therapeutic agents that target neutrophil dynamics and trafficking in different organs. [ABSTRACT FROM AUTHOR]

The roles of the NAT2 genotype and enzyme maturation on isoniazid pharmacokinetics were investigated in South African infants with perinatal HIV exposure enrolled in a randomized, double-blind, controlled trial of isoniazid for prevention of tuberculosis disease and latent infection. Plasma concentration-time measurements of isoniazid from 151 infants (starting at 3-4 months of age) receiving isoniazid 10 to 20 mg/kg/d orally during the course of the 24-month study were incorporated in a population analysis along with NAT2 genotype, body weight, age, and sex. The results showed a different NAT2 enzyme maturation profile for each of the 3 acetylation groups, with the 70-kg body weight–normalized typical apparent clearance for the fast and intermediate acetylators increasing from 14.25 L/h and 10.88 L/h at 3 months of age to 22.84 L/h and 15.58 L/h at 24 months of age, respectively, with no significant change in the apparent clearance of the slow group during this period. A hypothesis is proposed to explain the genotype-dependent enzyme maturation processes for the NAT2 enzyme. [ABSTRACT FROM PUBLISHER]

Because conventional absorption models often fail to describe plasma concentration-time profiles following oral administration, empirical input functions such as the in verse Gaussian function have been successfully used. The purpose of this note is to extend this model by adding a first-order absorption process and to demonstrate the application of population analysis using maximum likelihood estimation via the EM algorithm (implemented in ADAPT 5). In one example, the analysis of bioavailability data of an extended-release formulation, as well as the mean dissolution times estimated in vivo and in vitro with the use of the inverse Gaussian function, is well in accordance, suggesting that the in verse Gaussian function indeed accounts for the in viva dissolution process. In the other example, the kinetics of trapidil in patients with liver disease, the absorption/dissolution parameters are characterized by a high interindividual variability. Adding a first-order absorption process to the inverse Gaussian function improved the fit in both cases. [ABSTRACT FROM AUTHOR]

An introduction is presented for this issue which focuses on the impact of methodological and technological innovation as well as multidisciplinary integration of research in the field of pharmacometrics.

The article discusses the transfer of intellectual technology to the study of pharmacology, pathophysiology, and drug development. The application of systems modeling in respiratory mechanics, viral dynamics, and cardiac function research is mentioned. Examples of successful solutions resulting from the application of transform theory and linear systems analysis to pharmacokinetics are noted.

An introduction is presented for this issue which focuses on the field of pharmacometrics, the American Society of Pharmacometrics, and innovation.

The article comments on the planning for the American Conference on Pharmacometrics (ACoP) meetings in Tucson, Arizona in 2008 and Mystic, Connecticut in 2009, and calls on the pharmacometric community to volunteer their time and skills to the organization via the ACOP Web site which is at www.to-acop.org.