BackgroundSulphadoxine–pyrimethamine (SP) is widely used as an intermittent preventive treatment for malaria in pregnancy (IPTp). However, pharmacokinetic studies in pregnancy show variable and often contradictory findings. We describe population and trimester-specific differences in SP pharmacokinetics among Ugandan women.MethodsSP (three tablets) were administered to 34 nonpregnant and 87 pregnant women in the second trimester. Seventy-eight pregnant women were redosed in the third trimester. Blood was collected over time points ranging from 0.5 h to 42 days postdose. Data on the variables age, body weight, height, parity, gestational age, and serum creatinine, alanine transaminase and albumin levels were collected at baseline. Plasma drug assays were performed using high-performance liquid chromatography with ultraviolet detection. Population pharmacokinetic analysis was done using NONMEM software.ResultsA two-compartment model with first-order absorption and a lag time best described both the sulphadoxine and pyrimethamine data. Between trimesters, statistically significant differences in central volumes of distribution (V2) were observed for both drugs, while differences in the distribution half-life and the terminal elimination half-life were observed for pyrimethamine and sulphadoxine, respectively. Significant covariate relationships were identified on clearance (pregnancy status and serum albumin level) and V2 (gestational age) for sulphadoxine. For pyrimethamine, clearance (pregnancy status and age) and V2 (gestational age and body weight) were significant. Considering a 25 % threshold for clinical relevance, only differences in clearance of both drugs between pregnant and nonpregnant women were significant.ConclusionWhile clinically relevant differences in SP disposition between trimesters were not seen, increased clearance with pregnancy and the increasing volume of distribution in the central compartment with gestational age lend support to the revised World Health Organization guidelines advocating more frequent dosing of SP for IPTp.

PurposePlasma albumin, a biomarker for hepatic function, is reported to correspondingly decrease in concentration as disease severity increases in chronic infections including HIV and TB. Our objective was to develop a semi-mechanistic disease progression model to quantify plasma albumin concentration changes during TB and HIV therapy and identify the associated covariate factors.MethodsPlasma albumin concentration data was collected at specified times for 3 months from 262 HIV participants receiving efavirenz based anti retroviral therapy. Of these, 158 were TB co-infected and on Rifampicin based anti –tuberculosis co-treatment. An indirect response model with zero order albumin production and first order elimination was developed in NONMEM version 7.2 to describe our data. Genotype (CYP2B6*6 and 11, CYP3A5, ABCB1c.3435C>T and ABCB1rs), TB disease status, baseline age, body weight, plasma creatinine, alanine transaminase enzyme and CD4+ count were the potential model covariates tested.ResultsThe proposed model successfully described plasma albumin concentration changes in the study population. There was a 10.9% and 48.6% increase in albumin production rates in HIV only and TB co-infected participants respectively. Participants co-infected with TB showed a 44.2% lower baseline albumin secretion rate than those without TB while ABCB1c.3435C>T mutation was associated with a 16% higher steady state albumin secretion rate following treatment.ConclusionA semi-mechanistic model describes plasma albumin concentration changes in HIV patients on ART. Further work is required to establish the utility of the model in monitoring disease progression and predicting prognosis in HIV and TB co-infected patients in absence of or during treatment.Electronic supplementary materialThe online version of this article (doi:10.1186/s40203-014-0003-9) contains supplementary material, which is available to authorized users.

Paclitaxel-associated peripheral neuropathy (PN), a major dose-limiting toxicity, significantly impacts patients' quality of life/treatment outcome. Evaluation of risk factors often ignores time of PN onset, precluding the impact of time-dependent factors, e.g. drug exposure, needed to comprehensively characterize PN. We employed parametric time-to-event (TTE) analysis to describe the time-course of risk of first occurrence of clinically relevant PN grades≥2 (PN2+, n=105, common terminology criteria v4.0) and associated patient/treatment characteristics, leveraging data from 365 patients (1454 cycles) receiving 3-weekly paclitaxel (plus carboplatin AUC=6 or cisplatin 80 mg/m 2) for ≤6 cycles. Paclitaxel was intravenously administered (3 h) as standard 200 mg/m 2 doses (n=182) or following pharmacokinetic-guided dosing (n=183). A cycle-varying hazard TTE model linking surge in hazard of PN2+ to paclitaxel administration (PN2+ proportions (i.e. cases/1000 patients), first day, cycle 1: 4.87/1000, cycle 6: 7.36/1000) and linear decline across cycle (last day, cycle 1: 1.64/1000, cycle 6: 2.48/1000) adequately characterized the time-varying hazard of PN2+. From joint covariate evaluation, PN2+ proportions (first day, cycle 1) increased by 1.00/1000 with 5-μmol. h/L higher paclitaxel exposure per cycle (AUC cycle , most relevant covariate), 0.429/1000 with 5year higher age, 1.31/1000 (smokers versus non-smokers), and decreased by 0.670/1000 (females versus males). Compared to 200 mg/m 2 3-weekly dosing, model-predicted cumulative risk of PN2+ was significantly higher (42%) with 80 mg/m 2 weekly dosing but reduced by 11% with 175 mg/m 2 3-weekly dosing. The established TTE modelling framework enables quantification and comparison of patient's cumulative risks of PN2+ for different clinically-relevant paclitaxel dosing schedules, sparing patients PN2+ to improve paclitaxel therapy.