Development of physiologically-based pharmacokinetic models for standard of care and newer tuberculosis drugs.

Tuberculosis (TB) remains a global health problem and there is an ongoing effort to develop more effective therapies and new combination regimes that can reduce duration of treatment. The purpose of this study was to demonstrate utility of a physiologically-based pharmacokinetic modeling approach to predict plasma and lung concentrations of 11 compounds used or under development as TB therapies (bedaquiline [and N-desmethyl bedaquiline], clofazimine, cycloserine, ethambutol, ethionamide, isoniazid, kanamycin, linezolid, pyrazinamide, rifampicin, and rifapentine). Model accuracy was assessed by comparison of simulated plasma pharmacokinetic parameters with healthy volunteer data for compounds administered alone or in combination. Eighty-four percent (area under the curve [AUC]) and 91% (maximum concentration [Cmax ]) of simulated mean values were within 1.5-fold of the observed data and the simulated drug-drug interaction ratios were within 1.5-fold (AUC) and twofold (Cmax ) of the observed data for nine (AUC) and eight (Cmax ) of the 10 cases. Following satisfactory recovery of plasma concentrations in healthy volunteers, model accuracy was assessed further (where patients' with TB data were available) by comparing clinical data with simulated lung concentrations (9 compounds) and simulated lung: plasma concentration ratios (7 compounds). The 5th-95th percentiles for the simulated lung concentration data recovered between 13% (isoniazid and pyrazinamide) and 88% (pyrazinamide) of the observed data points (Am J Respir Crit Care Med, 198, 2018, 1208; Nat Med, 21, 2015, 1223; PLoS Med, 16, 2019, e1002773). The impact of uncertain model parameters, such as the fraction of drug unbound in lung tissue mass (fumass ), is discussed. Additionally, the variability associated with the patient lung concentration data, which was sparse and included extensive within-subject, interlaboratory, and experimental variability (as well interindividual variability) is reviewed. All presented models are transparently documented and are available as open-source to aid further research.

A Laboratory-Specific Scaling Factor to Predict the In Vivo Human Clearance of Aldehyde Oxidase Substrates.

Aldehyde oxidase (AO) efficiently metabolizes a range of compounds with N-containing heterocyclic aromatic rings and/or aldehydes. The limited knowledge of AO activity and abundance (in vitro and in vivo) has led to poor prediction of in vivo systemic clearance (CL) using in vitro-to-in vivo extrapolation approaches, which for drugs in development can lead to their discontinuation. We aimed to identify appropriate scaling factors to predict AO CL of future new chemical entities (NCEs). The metabolism of six AO substrates was measured in human liver cytosol (HLC) and S9 fractions. Measured blood-to-plasma ratios and free fractions (in the in vitro system and in plasma) were used to develop physiologically based pharmacokinetic models for each compound. The impact of extrahepatic metabolism was explored, and the intrinsic clearance required to recover in vivo profiles was estimated and compared with in vitro measurements. Using HLC data and assuming only hepatic metabolism, a systematic underprediction of clearance was observed (average fold underprediction was 3.8). Adding extrahepatic metabolism improved the accuracy of the results (average fold error of 1.9). A workflow for predicting metabolism of an NCE by AO is proposed, and an empirical (laboratory-specific) scaling factor of three on the predicted intravenous CL allows a reasonable prediction of the available clinical data. Alternatively, considering also extrahepatic metabolism, an scaling factor of 6.5 applied on the intrinsic clearance could be used. Future research should focus on the impact of the in vitro study designs and the contribution of extrahepatic metabolism to AO-mediated clearance to understand the mechanisms behind the systematic underprediction. SIGNIFICANCE STATEMENT: This works describes the development of scaling factors to allow in vitro-in vivo extrapolation of the clearance of compounds by aldehyde oxidase metabolism in humans. In addition, physiologically based pharmacokinetic models were developed for each of the aldehyde oxidase substrate compounds investigated.

Risk-Benefit Assessment of Ethinylestradiol Using a Physiologically Based Pharmacokinetic Modeling Approach.

Current formulations of combined oral contraceptives (COC) containing ethinylestradiol (EE) have ≤35 µg due to increased risks of cardiovascular diseases (CVD) with higher doses of EE. Low-dose formulations however, have resulted in increased incidences of breakthrough bleeding and contraceptive failure, particularly when coadministered with inducers of cytochrome P450 enzymes (CYP). The developed physiologically based pharmacokinetic model quantitatively predicted the effect of CYP3A4 inhibition and induction on the pharmacokinetics of EE. The predicted Cmax and AUC ratios when coadministered with voriconazole, fluconazole, rifampicin, and carbamazepine were within 1.25 of the observed data. Based on published clinical data, an AUCss value of 1,000 pg/ml.h was selected as the threshold for breakthrough bleeding. Prospective application of the model in simulations of different doses of EE (20 µg, 35 µg, and 50 µg) identified percentages of the population at risk of breakthrough bleeding alone and with varying degrees of CYP modulation.

Does Acute Propranolol Treatment Prevent Posttraumatic Stress Disorder, Anxiety, and Depression in Children with Burns?

OBJECTIVE: This study examined whether acute propranolol treatment prevented posttraumatic stress disorder (PTSD), anxiety, and depression in children hospitalized in the pediatric intensive care unit for large burns. We hypothesized that the prevalence of PTSD, anxiety, and depression would be significantly less in the propranolol than nonpropranolol groups. METHODS: Children who had previously participated in a randomized controlled clinical trial of acute propranolol and nonpropranolol controls were invited to participate in long-term follow-up interviews. Eligible participants from 1997 to 2008 were identified from the electronic medical records, and data were collected in 2010-2011. Measures included the Missouri Assessment of Genetics Interview for Children to assess lifetime PTSD, Revised Children's Manifest Anxiety Scale to assess anxiety, and two depression inventories Children's Depression Inventory and Beck Depression Inventory-II. RESULTS: Of 202 participants, 89 were in the propranolol group and 113 were nonpropranolol controls. Children were an average of 7 years postburn. The average total body surface area burned was 56.4 + 15.1% (range = 24%-99%). The mean dose of propranolol was 3.64 ± 3.19 mg/kg per day (range = 0.36-12.12). The duration of propranolol inpatient treatment days varied, mean days 26.5 ± 19.8. The prevalence of lifetime PTSD in the propranolol group was 3.5% and controls 7.2%, but this difference was not statistically significant. We controlled for administration of pain medications, anxiolytics, and antidepressants overall and no significant differences were detected in the rates of PTSD, anxiety, or depression. CONCLUSIONS: The prevalence of PTSD, anxiety, and depression was similar in children who received propranolol acutely and those who did not. This may be influenced by the standard of care that all children received timely pharmacotherapy for pain and anxiety management and psychotherapy beginning in their acute phase of treatment.

Development of a physiologically based pharmacokinetic model to predict the effects of flavin-containing monooxygenase 3 (FMO3) polymorphisms on itopride exposure.

Itopride, a substrate of FMO3, has been used for the symptomatic treatment of various gastrointestinal disorders. Physiologically based pharmacokinetic (PBPK) modeling was applied to evaluate the impact of FMO3 polymorphism on itopride pharmacokinetics (PK). The Asian populations within the Simcyp simulator were updated to incorporate information on the frequency, activity and abundance of FMO3 enzyme with different phenotypes. A meta-analysis of relative enzyme activities suggested that FMO3 activity in subjects with homozygous Glu158Lys and Glu308Gly mutations (Lys158 and Gly308) in both alleles is ~47% lower than those carrying two wild-type FMO3 alleles. Individuals with homozygous Lys158 and Gly308 mutations account for about 5% of the total population in Asian populations. A CLint of 9 µl/min/pmol was optimised for itopride via a retrograde approach as human liver microsomal results would under-predict its clearance by ~7.9-fold. The developed itopride PBPK model was first verified with three additional clinical studies in Korean and Japanese subjects resulting in a predicted clearance of 52 to 69 l/h, which was comparable to those observed (55 to 88 l/h). The model was then applied to predict plasma concentration-time profiles of itopride in Chinese subjects with wild type or homozygous Lys158 and Gly308 FMO3 genotypes. The ratios of predicted to observed AUC of itopride in subjects with each genotype were 1.23 and 0.94, respectively. In addition, the results also suggested that for FMO3 metabolised drugs with a safety margin of 2 or more, proactive genotyping FMO3 to exclude subjects with homozygous Lys158/Gly308 alleles may not be necessary.

Deciding on success criteria for predictability of pharmacokinetic parameters from in vitro studies: an analysis based on in vivo observations.

Prediction accuracy of pharmacokinetic parameters is often assessed using prediction fold error, i.e., being within 2-, 3-, or n-fold of observed values. However, published studies disagree on which fold error represents an accurate prediction. In addition, "observed data" from only one clinical study are often used as the gold standard for in vitro to in vivo extrapolation (IVIVE) studies, despite data being subject to significant interstudy variability and subjective selection from various available reports. The current study involved analysis of published systemic clearance (CL) and volume of distribution at steady state (Vss) values taken from over 200 clinical studies. These parameters were obtained for 17 different drugs after intravenous administration. Data were analyzed with emphasis on the appropriateness to use a parameter value from one particular clinical study to judge the performance of IVIVE and the ability of CL and Vss values obtained from one clinical study to "predict" the same values obtained in a different clinical study using the n-fold criteria for prediction accuracy. The twofold criteria method was of interest because it is widely used in IVIVE predictions. The analysis shows that in some cases the twofold criteria method is an unreasonable expectation when the observed data are obtained from studies with small sample size. A more reasonable approach would allow prediction criteria to include clinical study information such as sample size and the variance of the parameter of interest. A method is proposed that allows the "success" criteria to be linked to the measure of variation in the observed value.