Development of an Adult Physiologically Based Pharmacokinetic Model of Solithromycin in Plasma and Epithelial Lining Fluid

Application of empirical scalars to enable early prediction of human hepatic clearance using IVIVE in drug discovery: an evaluation of 173 drugs

The utilization of in vitro data to predict drug pharmacokinetics (PK) in vivo has been a consistent practice in early drug discovery for decades. However, its success is hampered by mispredictions attributed to uncharacterized biological phenomena/experimental artifacts. Predicted drug clearance (CL) from experimental data (i.e. hepatocyte intrinsic clearance: CLint, fraction unbound in plasma: fu,p) is often systematically underpredicted using the well-stirred model (WSM). The objective of this study was to evaluate using empirical scalars in the WSM to correct for CL mispredictions. Drugs (N=28) were used to generate numerical scalars on CLint (α), and fu,p (β) to minimize the error (AAFE) for CL predictions. These scalars were validated using an additional dataset (N=28 drugs) and applied to a non-redundant AstraZeneca (AZ) dataset available in the literature (N=117 drugs) for a total of 173 compounds. CL predictions using the WSM were improved for most compounds using an α value of 3.66 (~64%<2-fold) compared to no scaling (~46%<2-fold). Similarly, using a β value of 0.55 or combination of α and β scalars (values of 1.74 and 0.66, respectively) resulted in a similar improvement in predictions (~64%<2-fold and ~65%<2-fold, respectively). For highly bound compounds (fu,p{less than or equal to}0.01), AAFE was substantially reduced across all scaling methods. Using the β scalar alone or a combination of α and β appeared optimal; and produce larger magnitude corrections for highly-bound compounds. Some drugs are still disproportionally mispredicted, however the improvements in prediction error and simplicity of applying these scalars suggests its utility for early-stage CL predictions. Significance Statement In early drug discovery, prediction of human clearance using in vitro experimental data plays an essential role in triaging compounds prior to in vivo studies. These predictions have been systematically underestimated. Here we introduce empirical scalars calibrated on the extent of plasma protein binding that appear to improve clearance prediction across multiple datasets. This approach can be used in early phases of drug discovery prior to the availability of pre-clinical data for early quantitative predictions of human clearance.

Penetration of Antibacterial Agents into Pulmonary Epithelial Lining Fluid: An Update

A comprehensive review of drug penetration into pulmonary epithelial lining fluid (ELF) was previously published in 2011. Since then, an extensive number of studies comparing plasma and ELF concentrations of antibacterial agents have been published and are summarized in this review. The majority of the studies included in this review determined ELF concentrations of antibacterial agents using bronchoscopy and bronchoalveolar lavage, and this review focuses on intrapulmonary penetration ratios determined with area under the concentration-time curve from healthy human adult studies or pharmacokinetic modeling of various antibacterial agents. If available, pharmacokinetic/pharmacodynamic parameters determined from preclinical murine infection models that evaluated ELF concentrations are also provided. There are also a limited number of recently published investigations of intrapulmonary penetration in critically ill patients with lower respiratory tract infections, where greater variability in ELF concentrations may exist. The significance of these changes may impact the intrapulmonary penetration in the setting of infection, and further studies relating ELF concentrations to clinical response are needed. Phase I drug development programs now include assessment of initial pharmacodynamic target values for pertinent organisms in animal models, followed by evaluation of antibacterial penetration into the human lung to assist in dosage selection for clinical trials in infected patients. The recent focus has been on β-lactam agents, including those in combination with β-lactamase inhibitors, particularly due to the rise of multidrug-resistant infections. This manifests as a large portion of the review focusing on cephalosporins and carbapenems, with or without β-lactamase inhibitors, in both healthy adult subjects and critically ill patients with lower respiratory tract infections. Further studies are warranted in critically ill patients with lower respiratory tract infections to evaluate the relationship between intrapulmonary penetration and clinical and microbiological outcomes. Our clinical research experience with these studies, along with this literature review, has allowed us to outline key steps in developing and evaluating dosage regimens to treat extracellular bacteria in lower respiratory tract infections.

Leveraging Physiologically Based Pharmacokinetic Modeling and Experimental Data to Guide Dosing Modification of CYP3A-Mediated Drug-Drug Interactions in the Pediatric Population

Solithromycin is a novel fluoroketolide antibiotic that is both a substrate and time-dependent inhibitor of CYP3A. Solithromycin has demonstrated efficacy in adults with community-acquired bacterial pneumonia and has also been investigated in pediatric patients. The objective of this study was to develop a framework for leveraging physiologically based pharmacokinetic (PBPK) modeling to predict CYP3A-mediated drug-drug interaction (DDI) potential in the pediatric population using solithromycin as a case study. To account for age, we performed in vitro metabolism and time-dependent inhibition studies for solithromycin for CYP3A4, CYP3A5, and CYP3A7. The PBPK model included CYP3A4 and CYP3A5 metabolism and time-dependent inhibition, glomerular filtration, P-glycoprotein transport, and enterohepatic recirculation. The average fold error of simulated and observed plasma concentrations of solithromycin in both adults (1966 plasma samples) and pediatric patients from 4 days to 17.9 years (684 plasma samples) were within 0.5- to 2.0-fold. The geometric mean ratios for the simulated area under the concentration versus time curve (AUC) extrapolated to infinity were within 0.75- to 1.25-fold of observed values in healthy adults receiving solithromycin with midazolam or ketoconazole. DDI potential was simulated in pediatric patients (1 month to 17 years of age) and adults. Solithromycin increased the simulated midazolam AUC 4- to 6-fold, and ketoconazole increased the simulated solithromycin AUC 1- to 2-fold in virtual subjects ranging from 1 month to 65 years of age. This study presents a systematic approach for incorporating CYP3A in vitro data into adult and pediatric PBPK models to predict pediatric CYP3A-mediated DDI potential. SIGNIFICANCE STATEMENT: Using solithromycin, this study presents a framework for investigating and incorporating CYP3A4, CYP3A5, and CYP3A7 in vitro data into adult and pediatric physiologically based pharmacokinetic models to predict CYP3A-mediated DDI potential in adult and pediatric subjects during drug development. In this study, minor age-related differences in inhibitor concentration resulted in differences in the magnitude of the DDI. Therefore, age-related differences in DDI potential for substrates metabolized primarily by CYP3A4 can be minimized by closely matching adult and pediatric inhibitor concentrations.

Investigating the effect of TRPV4 inhibition on pulmonary-vascular barrier permeability following segmental endotoxin challenge

BACKGROUND

Acute Respiratory Distress Syndrome (ARDS) is associated with increased pulmonary-vascular permeability. In the lung, transient receptor potential vanilloid 4 (TRPV4), a Ca²⁺-permeable cation channel, is a regulator of endothelial permeability and pulmonary edema. We performed a Phase I, placebo-controlled, double-blind, randomized, parallel group, proof-of-mechanism study to investigate the effects of TRPV4 channel blocker, GSK2798745, on pulmonary-vascular barrier permeability using a model of lipopolysaccharide (LPS)-induced lung inflammation.

METHODS

Healthy participants were randomized 1:1 to receive 2 single doses of GSK2798745 or placebo, 12 h apart. Two hours after the first dose, participants underwent bronchoscopy and segmental LPS instillation. Total protein concentration and neutrophil counts were measured in bronchoalveolar lavage (BAL) samples collected before and 24 h after LPS challenge, as markers of barrier permeability and inflammation, respectively. The primary endpoint was baseline adjusted total protein concentration in BAL at 24 h after LPS challenge. A Bayesian framework was used to estimate the posterior probability of any percentage reduction (GSK2798745 relative to placebo). Safety endpoints included the incidence of adverse events (AEs), vital signs, 12-lead electrocardiogram, clinical laboratory and haematological evaluations, and spirometry.

RESULTS

Forty-seven participants were dosed and 45 completed the study (22 on GSK2798745 and 23 on placebo). Overall, GSK2798745 was well tolerated. Small reductions in mean baseline adjusted BAL total protein (~9%) and neutrophils (~7%) in the LPS-challenged segment were observed in the GSK2798745 group compared with the placebo group; however, the reductions did not meet pre-specified success criteria of at least a 95% posterior probability that the percentage reduction in the mean 24-h post LPS BAL total protein level (GSK2798745 relative to placebo) exceeded zero. Median plasma concentrations of GSK2798745 were predicted to inhibit TRPV4 on lung vascular endothelial cells by ~70-85% during the 24 h after LPS challenge; median urea-corrected BAL concentrations of GSK2798745 were 3.0- to 8.7-fold higher than those in plasma.

CONCLUSIONS

GSK2798745 did not affect segmental LPS-induced elevation of BAL total protein or neutrophils, despite blood and lung exposures that were predicted to be efficacious. CLINICALTRIALS.

GOV IDENTIFIER

NCT03511105.

Comparison of solithromycin with erythromycin in Enterococcus faecalis and Enterococcus faecium from China: antibacterial activity, clonality, resistance mechanism, and inhibition of biofilm formation

Solithromycin (SOL), a fourth-generation macrolide and ketolide, has been reported to have robust antibacterial activity against a wide spectrum of Gram-positive bacteria. However, the impact of SOL on planktonic growth and biofilm formation of clinical enterococcus isolates remains unclear. In this study, 276 Enterococcus faecalis isolates and 122 Enterococcus faecium were retrospectively collected from a tertiary hospital from China. SOL against clinical isolates of enterococci from China were evaluated the antimicrobial activity in comparison with erythromycin, and explore its relationship with the clonality, virulence genes and resistance mechanism of these isolates. Our data showed that the MICs of SOL against clinical E. faecalis and E. faecium isolates from China were ≤4 and ≤8 mg l^-1, respectively. ST16 and ST179 were regarded as the risk factor to SOL resistance in E. faecalis. SOL could inhibit but not eradicate the biofilm formation of E. faecalis. The bactericidal effects of SOL against E. faecalis and E. faecium were demonstrated to be similar to linezolid and vancomycin using time-kill assays. In conclusion, SOL showed significantly enhanced antibacterial activity against clinical isolates of E. faecalis and E. faecium from China in comparison to erythromycin. Furthermore, SOL could inhibit the biofilm formation of E. faecalis and have the similar bactericidal ability as linezolid and vancomycin against both E. faecalis and E. faecium.

Use of normalized prediction distribution errors for assessing population physiologically-based pharmacokinetic model adequacy

Currently employed methods for qualifying population physiologically-based pharmacokinetic (Pop-PBPK) model predictions of continuous outcomes (e.g., concentration-time data) fail to account for within-subject correlations and the presence of residual error. In this study, we propose a new method for evaluating Pop-PBPK model predictions that account for such features. The approach focuses on deriving Pop-PBPK-specific normalized prediction distribution errors (NPDE), a metric that is commonly used for population pharmacokinetic model validation. We describe specific methodological steps for computing NPDE for Pop-PBPK models and define three measures for evaluating model performance: mean of NPDE, goodness-of-fit plots, and the magnitude of residual error. Utility of the proposed evaluation approach was demonstrated using two simulation-based study designs (positive and negative control studies) as well as pharmacokinetic data from a real-world clinical trial. For the positive-control simulation study, where observations and model simulations were generated under the same Pop-PBPK model, the NPDE-based approach denoted a congruency between model predictions and observed data (mean of NPDE =  - 0.01). In contrast, for the negative-control simulation study, where model simulations and observed data were generated under different Pop-PBPK models, the NPDE-based method asserted that model simulations and observed data were incongruent (mean of NPDE =  - 0.29). When employed to evaluate a previously developed clindamycin PBPK model against prospectively collected plasma concentration data from 29 children, the NPDE-based method qualified the model predictions as successful (mean of NPDE = 0). However, when pediatric subpopulations (e.g., infants) were evaluated, the approach revealed potential biases that should be explored.

Pitfalls of using numerical predictive checks for population physiologically-based pharmacokinetic model evaluation

Comparisons between observed data and model simulations represent a critical component for establishing confidence in population physiologically-based pharmacokinetic (Pop-PBPK) models. Numerical predictive checks (NPC) that assess the proportion of observed data that correspond to Pop-PBPK model prediction intervals (PIs) are frequently used to qualify such models. We evaluated the effects of three components on the performance of NPC for qualifying Pop-PBPK model concentration-time predictions: (1) correlations (multiple samples per subject), (2) residual error, and (3) discrepancies in the distribution of demographics between observed and virtual subjects. Using a simulation-based study design, we artificially created observed pharmacokinetic (PK) datasets and compared them to model simulations generated under the same Pop-PBPK model. Observed datasets containing uncorrelated and correlated observations (± residual error) were formulated using different random-sampling techniques. In addition, we created observed datasets where the distribution of subject body weights differed from that of the virtual population used to generate model simulations. NPC for each observed dataset were computed based on the Pop-PBPK model's 90% PI. NPC were associated with inflated type-I-error rates (> 0.10) for observed datasets that contained correlated observations, residual error, or both. Additionally, the performance of NPC were sensitive to the demographic distribution of observed subjects. Acceptable use of NPC was only demonstrated for the idealistic case where observed data were uncorrelated, free of residual error, and the demographic distribution of virtual subjects matched that of observed subjects. Considering the restricted applicability of NPC for Pop-PBPK model evaluation, their use in this context should be interpreted with caution.

Better prediction of the local concentration-effect relationship: the role of physiologically based pharmacokinetics and quantitative systems pharmacology and toxicology in the evolution of model-informed drug discovery and development

Model-informed drug discovery and development (MID3) is an umbrella term under which sit several computational approaches: quantitative systems pharmacology (QSP), quantitative systems toxicology (QST) and physiologically based pharmacokinetics (PBPK). QSP models are built using mechanistic knowledge of the pharmacological pathway focusing on the putative mechanism of drug efficacy; whereas QST models focus on safety and toxicity issues and the molecular pathways and networks that drive these adverse effects. These can be mediated through exaggerated on-target or off-target pharmacology, immunogenicity or the physiochemical nature of the compound. PBPK models provide a mechanistic description of individual organs and tissues to allow the prediction of the intra- and extra-cellular concentration of the parent drug and metabolites under different conditions. Information on biophase concentration enables the prediction of a drug effect in different organs and assessment of the potential for drug-drug interactions. Together, these modelling approaches can inform the exposure-response relationship and hence support hypothesis generation and testing, compound selection, hazard identification and risk assessment through to clinical proof of concept (POC) and beyond to the market.

Population Pharmacokinetics and Safety of Solithromycin following Intravenous and Oral Administration in Infants, Children, and Adolescents

Solithromycin is a novel fluoroketolide antibiotic which was under investigation for the treatment of community-acquired bacterial pneumonia (CABP). A phase 1 study was performed to characterize the pharmacokinetics (PK) and safety of solithromycin in children. Eighty-four subjects (median age, 6 years [age range, 4 days to 17 years]) were administered intravenous (i.v.) or oral (capsules or suspension) solithromycin (i.v., 6 to 8 mg/kg of body weight; capsules/suspension, 14 to 16 mg/kg on days 1 and 7 to 15 mg/kg on days 2 to 5). PK samples were collected after the first and multidose administration. Data from 83 subjects (662 samples) were combined with previously collected adolescent PK data (n = 13; median age, 16 years [age range, 12 to 17 years]) following capsule administration to perform a population PK analysis. A 2-compartment PK model characterized the data well, and postmenstrual age was the only significant covariate after accounting for body size differences. Dosing simulations suggested that 8 mg/kg i.v. daily and oral dosing of 20 mg/kg on day 1 (800-mg adult maximum) followed by 10 mg/kg on days 2 to 5 (400-mg adult maximum) would achieve a pediatric solithromycin exposure consistent with the exposures observed in adults. Seventy-six treatment-emergent adverse events (TEAEs) were reported in 40 subjects. Diarrhea (6 subjects) and infusion site pain or phlebitis (3 subjects) were the most frequently reported adverse events related to treatment. Two subjects experienced TEAEs of increased hepatic enzymes that were deemed not to be related to the study treatment. (The phase 1 pediatric studies discussed in this paper have been registered at ClinicalTrials.gov under identifiers NCT01966055 and NCT02268279.).