Physiologically based pharmacokinetic modeling and simulations to inform dissolution specifications and clinical relevance of release rates on elagolix exposure.

The aim of this analysis was to use a physiologically based pharmacokinetic (PBPK) model to predict the impact of changes in dissolution rates on elagolix exposures and define clinically relevant acceptance criteria for dissolution. Varying in vitro dissolution profiles were utilized in a PBPK model to describe the absorption profiles of elagolix formulations used in Phase 3 clinical trials and for the to be marketed commercial formulations. Single dose studies of 200 mg elagolix formulations were used for model verification under fasted conditions. Additional dissolution scenarios were evaluated to assess the impact of dissolution rates on elagolix exposures. Compared to the Phase 3 clinical trial formulation, sensitivity analysis on dissolution rates suggested that a hypothetical scenario of ∼75% slower dissolution rate would result in 14% lower predicted elagolix plasma exposures, however, the predicted exposures are still within the bioequivalence boundaries of 0.8-1.25 for both Cmax and AUC. A clinically verified PBPK model of elagolix was utilized to evaluate the impact of wider dissolution specifications on elagolix plasma exposures. The simulation results indicated that a slower in vitro dissolution profile, would not have a clinically significant impact on elagolix exposures. These model results informed the setting of wider dissolution specifications without requiring in vivo studies.

Clinical evaluation of P-glycoprotein inhibition by venetoclax: a drug interaction study with digoxin.

1. Venetoclax is a novel, small molecule B-cell lymphoma-2 (BCL-2) inhibitor that has demonstrated clinical efficacy in a variety of haematological malignancies. Since venetoclax is an inhibitor of P glycoprotein (P-gp) transporter, a study was conducted in healthy, female volunteers to evaluate the effect of venetoclax on the pharmacokinetics of digoxin, a P-gp probe substrate. 2. Volunteers received a single oral dose of digoxin (0.5 mg) with or without a single oral dose of venetoclax (100  mg). Serial blood samples were obtained for pharmacokinetic assessments of digoxin and venetoclax and serial urine samples were obtained for measurement of digoxin concentrations. Safety was assessed throughout the study. 3. Coadministration of digoxin and venetoclax increased digoxin maximum observed plasma concentration (Cmax) by 35% and area under the plasma-concentration time curve (AUC0-∞) by 9%. Digoxin half-life, renal clearance and the fraction excreted unchanged in urine remained relatively similar. The results of this study indicate that venetoclax can increase the concentrations of P-gp substrates. Narrow therapeutic index P-gp substrates should be administered six hours prior to venetoclax to minimise the potential interaction.

Altered xanthine oxidase and N-acetyltransferase activity in obese children.

AIMS: It is well established that oxidative and conjugative enzyme activity differs between obese and healthy-weight adults. However, the effect of obesity on drug metabolism in children has not been studied extensively. This study examined whether obese and healthy-weight children vary with respect to oxidative enzyme activity of CYP1A2, xanthine oxidase (XO) and conjugative enzyme activity of N-acetyltransferase 2 (NAT2). METHODS: In vivo CYP1A2, XO and NAT2 activity was assessed in obese (n= 9) and lean (n= 16) children between the ages of 6-10 years using caffeine (118.3 ml Coca Cola®) as probe. Urine samples were collected in 2-h increments over 8 h. Caffeine and metabolites were measured using LC/MS, and urinary metabolic ratios were determined based on reported methods. RESULTS: Sixteen healthy-weight and nine obese children were evaluated. XO activity was elevated in paediatric obese volunteers compared with non-obese paediatric volunteers (XO metabolic ratio of 0.7 ± 0.06 vs. 0.6 ± 0.06, respectively, 95% CI 0.046, 0.154, P < 0.001). NAT2 activity was fivefold higher in the obese (1 ± 0.4) as compared with non-obese children (0.2 ± 0.1), 95% CI 0.26, 1.34, P < 0.05. However, no difference was observed in CYP1A2 activity between the groups (95% CI -2.72, 0.12, P > 0.05). CONCLUSIONS: This study provides evidence that obese children have elevated XO and NAT2 enzyme activity when compared with healthy-weight controls. Further studies are needed to determine how this may impact the efficacy of therapeutic agents that may undergo metabolism by these enzymes.

Mechanistic Modeling of Intra-Tumor Spatial Distribution of Antibody-Drug Conjugates: Insights into Dosing Strategies in Oncology.

Antibody drug conjugates (ADCs) provide targeted delivery of cytotoxic agents directly inside tumor cells. However, many ADCs targeting solid tumors have exhibited limited clinical efficacy, in part, due to insufficient penetration within tumors. To better understand the relationship between ADC tumor penetration and efficacy, previously applied Krogh cylinder models that explore tumor growth dynamics following ADC administration in preclinical species were expanded to a clinical framework by integrating clinical pharmacokinetics, tumor penetration, and tumor growth inhibition. The objective of this framework is to link ADC tumor penetration and distribution to clinical efficacy. The model was validated by comparing virtual patient population simulations to observed overall response rates from trastuzumab-DM1 treated patients with metastatic breast cancer. To capture clinical outcomes, we expanded upon previous Krogh cylinder models to include the additional mechanism of heterogeneous tumor growth inhibition spatially across the tumor. This expansion mechanistically captures clinical response rates by describing heterogeneous ADC binding and tumor cell killing; high binding and tumor cell death close to capillaries vs. low binding, and high tumor cell proliferation far from capillaries. Sensitivity analyses suggest that clinical efficacy could be optimized through dose fractionation, and that clinical efficacy is primarily dependent on the ADC-target affinity, payload potency, and tumor growth rate. This work offers a mechanistic basis to predict and optimize ADC clinical efficacy for solid tumors, allowing dosing strategy optimization to improve patient outcomes.

Quantitative Assessment of Elagolix Enzyme-Transporter Interplay and Drug-Drug Interactions Using Physiologically Based Pharmacokinetic Modeling.

INTRODUCTION: Elagolix is approved for the management of moderate-to-severe pain associated with endometriosis. The aim of this analysis was to develop a physiologically based pharmacokinetic (PBPK) model that describes the enzyme-transporter interplay involved in the disposition of elagolix and to predict the magnitude of drug-drug interaction (DDI) potential of elagolix as an inhibitor of P-glycoprotein (P-gp) and inducer of cytochrome P450 (CYP) 3A4. METHODS: A PBPK model (SimCYP® version 15.0.86.0) was developed using elagolix data from in vitro, clinical PK and DDI studies. Data from DDI studies were used to quantify contributions of the uptake transporter organic anion transporting polypeptide (OATP) 1B1 and CYP3A4 in the disposition of elagolix, and to quantitatively assess the perpetrator potential of elagolix as a CYP3A4 inducer and P-gp inhibitor. RESULTS: After accounting for the interplay between elagolix metabolism by CYP3A4 and uptake by OATP1B1, the model-predicted PK parameters of elagolix along with the DDI AUC∞ and Cmax ratios, were within 1.5-fold of the observed data. Based on model simulations, elagolix 200 mg administered twice daily is a moderate inducer of CYP3A4 (approximately 56% reduction in midazolam AUC∞). Simulations of elagolix 150 mg administered once daily with digoxin predicted an increase in digoxin Cmax and AUC∞ by 68% and 19%, respectively. CONCLUSIONS: A PBPK model of elagolix was developed, verified, and applied to characterize the disposition interplay between CYP3A4 and OATP1B1, and to predict the DDI potential of elagolix as a perpetrator under dosing conditions that were not tested clinically. PBPK model-based predictions were used to support labeling language for DDI recommendations of elagolix.