Proposed Linezolid Dosing Strategies to Minimize Adverse Events for Treatment of Extensively Drug-Resistant Tuberculosis.

BACKGROUND: We evaluated Nix-TB trial data (NCT02333799, N = 109) to provide dosing recommendations to potentially minimize linezolid toxicity in patients with extensively drug-resistant tuberculosis. . METHODS: A pharmacokinetic model and toxicodynamic models for peripheral neuropathy, hemoglobin, and platelets were developed. Simulations compared safety outcomes for daily linezolid of 1200 and 600 mg, with and without dose adjustments for toxicity. Severe neuropathy was based on symptom scores from the Brief Peripheral Neuropathy Screen. Severe anemia and thrombocytopenia were defined as ≥ grade 3 adverse events according to the NIAID Division of Microbiology and Infectious Disease Adult Toxicity table. RESULTS: Predicted concentration-time profiles were a major predictor in all toxicodynamic models. Simulations showed higher percentages of patients with severe neuropathy (median, 19%; 90% confidence interval [CI], 17%-22% vs 5%, 4%-7%) and severe anemia (15%, 12%-17% vs 1%, 0%-2%) between 1200 and 600 mg daily linezolid. No differences in severe thrombocytopenia were observed (median, <1% for both daily doses). Generally, neuropathy occurred after 3 to 6 months of treatment and, with protocol-specified management, reversed within 15 months after onset. Simulations indicated that a >10% decrease in hemoglobin level after 4 weeks of treatment would have maximum sensitivity (82%) and specificity (84%) for predicting severe anemia. Reducing the dose from 1200 to 600 mg triggered by this marker may prevent 60% (90% CI, 45%-72%) of severe anemia. CONCLUSIONS: Simple neuropathy symptom and hemoglobin monitoring may guide linezolid dosing to avoid toxicities, but prospective testing is needed to confirm the benefit-to-risk ratio.

An Exposure-Response Perspective on the Clinical Dose of Pretomanid.

Pretomanid was approved by the U.S. FDA, via the limited population pathway for antibacterial and antifungal drugs, as part of a three-drug regimen with bedaquiline and linezolid for the treatment of extensively drug-resistant and treatment-intolerant or nonresponsive multidrug-resistant tuberculosis. The recommended dose of pretomanid is 200 mg once daily with food. The objective of this work was to retrospectively evaluate this recommended dose by means of exposure-response (E-R) modeling applied to outcomes of both efficacy and safety. Cox proportional-hazards modeling was used, with the steady-state average pretomanid concentration as the exposure metric. The efficacy outcome was time to sputum culture conversion (TSCC) to negative. The safety outcomes were times to the first occurrence of adverse events in classes selected from either pretomanid's investigator brochure or the new drug application (NDA) submission as recognized safety signals for pretomanid based on preclinical as well as clinical experience. Significant E-R relationships were found for TSCC and two adverse-event classes, vomiting (a single preferred term) and gastrointestinal (GI) symptoms (a collection of related terms). No significant E-R relationships were found for the single preferred terms nausea, alanine aminotransferase (ALT) increased, aspartate aminotransferase (AST) increased, and headache and for the collections hepatic disorders, transaminases increased, skin and subcutaneous tissue disorders, and headache. The results suggest that the recommended dose of pretomanid, 200 mg given in the fed state, is appropriate over the range of pharmacokinetic exposures.

Population Pharmacokinetics of the Antituberculosis Agent Pretomanid.

A population pharmacokinetic (PopPK) model for pretomanid was developed using data from 14 studies in the pretomanid development program: six phase 1 studies, six phase 2 studies, and two phase 3 studies. The final analysis data set contained 17,725 observations from 1,054 subjects, including healthy subjects and subjects with drug-sensitive, multidrug-resistant, or extensively drug-resistant pulmonary tuberculosis dosed pretomanid in monotherapy or combination therapy for up to 6 months. Pretomanid pharmacokinetic behavior was described by a one-compartment model that at a given dose was linear in its absorption and clearance processes but where the rate of absorption and extent of bioavailability changed with dose. Clearance and volume of distribution scaled allometrically with weight. Apparent clearance in females was 18% less than in males. Among HIV-positive subjects, absent the effect of CYP3A4-inducing antiretrovirals, apparent clearance was 6% higher. Some effects of total bilirubin and albumin were found, but the impacts on exposure were small. Bioavailability in the fasted condition was about half that in the fed condition. Relative bioavailability decreased with increasing dose in the fasted condition, but not for doses of ≤200 mg in the fed condition. HIV-positive subjects taking efavirenz and lopinavir/ritonavir had exposures that were reduced by 46 and 17%, respectively. There was little evidence for noteworthy effects of regimen partners on pretomanid. Standard diagnostics indicated that the model described the voluminous, diverse data well, so that the model could be used to generate exposure metrics for exposure/response analyses to be reported elsewhere.

Daily Dosing for Bedaquiline in Patients with Tuberculosis.

The bedaquiline regimen for the treatment of multidrug-resistant tuberculosis (MDR-TB) in adults is a loading dose of 400 mg QD for 2 weeks followed by 200 mg thrice weekly (TIW) for 22 weeks. Most TB antibiotics administered with bedaquiline are given QD. Using pharmacokinetic simulations, we explored alternative QD bedaquiline regimens and determined that 200 mg QD for 8 weeks followed by 100 mg QD provides comparable exposures to the approved regimen. This simpler regimen is under clinical evaluation.

Long-Term Effects on QT Prolongation of Pretomanid Alone and in Combinations in Patients with Tuberculosis.

Concentration-QTc modeling was applied to pretomanid, a new nitroimidazooxazine antituberculosis drug. Data came from eight phase 2 and phase 3 studies. Besides pretomanid alone, various combinations with bedaquiline, linezolid, moxifloxacin, and pyrazinamide were considered; special attention was given to the bedaquiline-pretomanid-linezolid (BPaL) regimen that has demonstrated efficacy in the Nix-TB study in subjects with extensively drug-resistant or treatment-intolerant or nonresponsive multidrug-resistant tuberculosis. Three heart rate corrections to QT were considered: Fridericia's QTcF, Bazett's QTcB, and a population-specific correction, QTcN. QTc increased with the plasma concentrations of pretomanid, bedaquiline's M2 metabolite, and moxifloxacin in a manner described by a linear model in which the three slope coefficients were constant across studies, visits within study, and times postdose within visit but where the intercept varied across those dimensions. The intercepts tended to increase on treatment to a plateau after several weeks, a pattern termed the secular trend. The slope terms were similar for the three QTc corrections, but the secular trends differed, suggesting that at least some of the secular trend was due to the elevated heart rates of tuberculosis patients decreasing to normal levels on treatment. For pretomanid 200 mg once a day (QD) alone, a typical steady-state maximum concentration of drug in plasma (Cmax) resulted in a mean change from baseline of QTcN of 9.1 ms, with an upper 90% confidence interval (CI) limit of 10.2 ms. For the BPaL regimen, due to the additional impact of the bedaquiline M2 metabolite, the corresponding values were 13.6 ms and 15.0 ms. The contribution to these values from the secular trend was 4.0 ms.

Diagnostics for confounding in PK/PD models for oxcarbazepine.

One type of pharmacokinetic/pharmacodynamic (PK/PD) relationship that is used to characterize the therapeutic action of a drug is the relationship between some univariate summary of the plasma-concentration-versus-time profile and the drug effect on a response outcome. Operationally, such a relationship may be observed in a large clinical trial where randomly sampled patients are randomized to different values of the concentration summary. If, under such conditions, the relationship between concentration and effect does not depend on the dose needed to attain the target concentration, such a relationship will be called a true PK/PD relationship. When the true PK/PD relationship is assessed as an object of estimation in a dose-controlled clinical trial (i.e. when dose is randomized), observed drug concentration is an outcome variable. The estimated PK/PD relationship between observed outcome and observed concentration, which we then refer to as the conventional PK/PD relationship, may be biased for the true PK/PD relationship. Because of this bias, the conventional relationship is called confounded for the true one. We show that diagnostics for confounding can be devised under reasonable assumptions. We then apply these diagnostics to PK/PD assessments of adults and children on oxcarbazepine adjunctive therapy. It was necessary to demonstrate the similarity of the true PK/PD relationships of adults and children on adjunctive therapy in order to support the approval of oxcarbazepine monotherapy in children by a bridging argument.

On some "disadvantages" of the population approach.

In a seminal article on population pharmacokinetic modeling, researchers demonstrated how means and variances of pharmacokinetic parameters for a patient population could be inferred from sparse data collected under conditions of routine patient care. But they also identified 4 potential concerns about their methodology: unobserved confounding variables may bias the inferences; conditions under which data are collected may lead to inaccuracies of reporting or recording; correlations among important predictor variables may reduce statistical efficiency; and costs cannot be controlled by principles of study design. Experiences are reviewed that relate to these potential disadvantages. A method is presented for diagnosing the possible presence of confounding. A model is constructed and applied that captures the influences of data inaccuracies. An example of selecting from among correlated covariates is summarized. Finally, a methodology for optimal study design is reviewed and applied to an example.