BACKGROUND: There are two concerns regarding rifabutin and INH pharmacokinetics in this population: 1) Malabsorption of anti-TB medications is frequent in this population and 2) Many antiretrovirals and other drugs frequently used in the management of HIV-infected individuals are inhibitors of the cytochrome p450 3A4 isoform and result in increased levels of rifabutin. Correlation of the pharmacokinetic and clinical outcomes in the setting of these interactions is essential. METHODS: The study will be done on the General Clinical Research Center at Duke University Medical Center, on an inpatient basis (depending on where the patient lives). No one who is suspected of being infectious or is infectious from TB will be enrolled on the GCRC. After informed consent is obtained, each subject will be admitted to the GCRC twice; the first admission will occur after at least four twice weekly doses of intermittent rifabutin and prior to beginning antiretroviral therapy and the second admission will occur two to six weeks following the institution of an antiretroviral regimen including efavirenz. During Admission #1, blood will be drawn at 0, 1, 3, 5, 7, 9, and 21 hours post dosing with INH and rifabutin. During Admission #2, blood will be drawn at 0, 2, 4, 6, 8, 10, 12, and 24 hours. Efavirenz will be given at time points 0 and 24 hours post sampling. TB drugs will be given at 3 hours (so that sampling times subsequent to INH/rifabutin dosing will correspond to those of Admission #1). Patients will be interviewed regarding concomitant medications, gastrointestinal symptoms and meals relative to study drug dosing. Sixty days following the last dose of PK study medicines, a follow-up visit or phone call (including review of medical record) will identify any adverse events. DATA ANALYSIS: Frequency distributions will include plots of the data, distribution curves to test for normality, parametric and non-parametric measures of central tendency and dispersion, as well as the Shapiro-Wilk W test for normality. Means will be reported + the standard deviation (SD). The percent coefficient of variation (CV) will be calculated as (SD/mean) multiplied by 100%. Correlation analysis (JMP) will be performed across the subject and outcome variables using non-parametric techniques (Spearman Rho, continuous data only).

The dependence of outcome variables (the pharmacokinetic parameters) upon subject characteristics (demographic data such as age, weight, CD4 count, etc.) will be determined by using Y by X analyses, one parameter at a time (continuous or nominal data). Subsequently, models with multiple X variables will be constructed using forward addition and backward deletion. Correlations between parameters and covariates will be considered statistically significant at p 3/4 0.05.