A population pharmacokinetic model for posaconazole intravenous solution and oral powder for suspension formulations in pediatric patients with neutropenia.

The objective of this study was to support posaconazole dose regimens in pediatric patients aged ≥2 years, using a population pharmacokinetic (PK) approach with data from a phase 1b study (NCT02452034). A one-compartment model with first-order absorption was fit to pharmacokinetic data from 144 participants aged 2 to 17 years, who were administered posaconazole as intravenous (IV) and powder for oral suspension (PFS) formulations, or IV only, at dosing regimens of 3.5, 4.5, and 6 mg/kg. The influence of demographic and clinical factors on pharmacokinetic parameters was evaluated using a stepwise forward inclusion/backward exclusion procedure. The final model simulated posaconazole exposure in patients aged 2 to <7 and 7 to 17 years at dosing regimens of 4.5, 6, and 7.5 mg/kg. Plasma concentration data following IV and PFS administration were well-described by a one-compartment model with first-order absorption and estimated bioavailability, where clearance and volume were subject to allometric scaling by body weight. The 6-mg/kg dosing regimen achieved the pharmacokinetic target (90% of the pediatric population having an average steady-state plasma concentration of ≥500 and <2,000 ng/mL) for both age groups, regardless of whether patients received IV and PFS or IV only. In a virtual adolescent population (body weight >40 kg), the 300 mg/day posaconazole tablet was also predicted to achieve the pharmacokinetic target and remain within a safe range of exposure. These data informed a weight-based nomogram for PFS dosing to maximize the number of pediatric patients achieving the pharmacokinetic target across weight bands, while also maintaining a favorable benefit/risk profile.

Population Pharmacokinetics of Doravirine and Exposure-Response Analysis in Individuals with HIV-1.

Doravirine is a novel nonnucleoside reverse transcriptase inhibitor for the treatment of human immunodeficiency virus 1 (HIV-1) infection. A population pharmacokinetic (PK) model was developed for doravirine using pooled data from densely sampled phase 1 trials and from sparsely sampled phase 2b and phase 3 trials evaluating doravirine administered orally as a single entity or as part of a fixed-dose combination of doravirine-lamivudine-tenofovir disoproxil fumarate. A one-compartment model with linear clearance from the central compartment adequately described the clinical PK of doravirine. While weight, age, and healthy versus HIV-1 status were identified as statistically significant covariates affecting doravirine PK, the magnitude of their effects was not clinically meaningful. Other intrinsic factors (gender, body mass index, race, ethnicity, and renal function) did not have statistically significant or clinically meaningful effects on doravirine PK. Individual exposure estimates for individuals in the phase 2b and 3 trials obtained from the final model were used for subsequent exposure-response analyses for virologic response (proportion of individuals achieving <50 copies/ml) and virologic failure. The exposure-response relationships between these efficacy endpoints and doravirine PK were generally flat over the range of exposures achieved for the 100 mg once-daily regimen in the phase 3 trials, with a minimal decrease in efficacy in individuals in the lowest 10th percentile of steady-state doravirine concentration at 24 h values. These findings support 100 mg once daily as the selected dose of doravirine, with no dose adjustment warranted for the studied intrinsic factors.

Operating characteristics of stepwise covariate selection in pharmacometric modeling.

Stepwise covariate modeling (SCM) is a widely used tool in pharmacometric analyses to identify covariates that explain between-subject variability (BSV) in exposure and exposure-response relationships. However, this approach has several potential weaknesses, including over-estimated covariate effect and incorrect selection of covariates due to collinearity. In this work, we investigated the operating characteristics (i.e., accuracy, precision, and power) of SCM in a controlled setting by simulating sixteen scenarios with up to four covariate relationships. The SCM analysis showed a decrease in the power to detect the true covariates as model complexity increased. Furthermore, false highly correlated covariates were frequently selected in place of or in addition to the true covariates. Relative root mean square errors (RMRSE) ranged from 1 to 51% for the fixed effects parameters, increased with the number of covariates included in the model, and were slightly higher than the RMRSE obtained with a simple re-estimation exercise with the true model (i.e., stochastic simulation and estimation). RMRSE for BSV increased with the number of covariates included in the model, with a covariance parameter RMRSE of almost 135% in the most complex scenario. Loose boundary conditions on the continuous covariate power relation appeared to have an impact on the covariate model selection in SCM. A stricter boundary condition helped achieve high power (> 90%), even in the most complex scenario. Finally, reducing the sample size in terms of number of subjects or number of samples proved to have an impact on the power to detect the correct model.

A Population Pharmacokinetic Model for a Solid Oral Tablet Formulation of Posaconazole.

A delayed-release solid tablet formulation that releases posaconazole in the small intestine was developed to maximize systemic absorption. This study aimed to characterize the pharmacokinetics of the posaconazole solid tablet formulation in adult subjects and to investigate the potential impact of demographic and clinical factors on posaconazole exposure through a population pharmacokinetic approach. Nonlinear mixed-effects modeling was performed using data from several studies conducted in healthy volunteers and patients. The influence of demographic and clinical factors on pharmacokinetic parameters was evaluated using a stepwise forward inclusion/backward exclusion procedure. The final pharmacokinetic model was used to simulate posaconazole exposure in patients at high risk for invasive fungal diseases treated with the proposed posaconazole dose of 300 mg twice daily on day 1, followed by 300 mg daily for 27 days. A one-compartment pharmacokinetic model with sequential zero-order and first-order absorption and a first-order disposition from the central compartment adequately described the pharmacokinetic profile of the posaconazole solid tablet formulation. Significant covariates included disease state (acute myeloid leukemia/myelodysplasia versus allogeneic hematopoietic stem cell transplantation), body weight, and formulation on bioavailability; food status on first-order absorption rate; and dosing regimen (a single dose versus multiple doses) on clearance. Except for body weight, the impact of these covariates on posaconazole exposure was considered clinically irrelevant. This population pharmacokinetic analysis confirmed that the proposed dose of the posaconazole solid tablet formulation provides adequate target therapeutic exposure (>0.5 mg/liter) to a broad range of patients at high risk for invasive fungal disease.

Population pharmacokinetics and exposure-response of osimertinib in patients with non-small cell lung cancer.

AIMS: To develop a population (pop) pharmacokinetic (PK) model for osimertinib (AZD9291) and its metabolite (AZ5104) and investigate the exposure-response relationships for selected efficacy and safety parameters. METHODS: PK, safety and efficacy data were collected from two non-small cell lung cancer (NSCLC) patient studies (n = 748) and one healthy volunteer study (n = 32), after single or multiple once-daily dosing of 20-240 mg osimertinib. Nonlinear mixed effects modelling was used to characterise the popPK. Individual exposure values were used to investigate the relationship with response evaluation criteria in solid tumours (RECIST 1.1) efficacy parameters and key safety parameters (rash, diarrhoea, QTcF). RESULTS: A popPK model that adequately described osimertinib and its metabolite AZ5104 in a joint manner was developed. Body weight, serum albumin and ethnicity were identified as significant covariates on PK in the analysis, but were not found to have a clinically relevant impact on osimertinib exposure. No relationship was identified between exposure and efficacy over the dose range studied. A linear relationship was observed between exposure and the occurrence of rash or diarrhoea, and between concentration and QTcF, with a predicted mean (upper 90% confidence interval) increase of 14.2 (15.8) ms at the maximum concentration for an 80 mg once-daily dose at steady state. CONCLUSIONS: PopPK and exposure-response models were developed for osimertinib and AZ5104. There was no relationship between exposure and efficacy but a linear relationship between exposure and safety endpoints (rash, diarrhoea and QTcF) was observed.

Time dependent pharmacokinetics of pembrolizumab in patients with solid tumor and its correlation with best overall response.

Pembrolizumab is a monoclonal antibody that targets the programmed death-1 receptor to induce immune-mediated clearance (CL) of tumor cells. Originally approved by the US Food and Drug Administration in 2014 for treating patients with unresectable or metastatic melanoma, pembrolizumab is now also used to treat patients with non-small-cell lung cancer, classical Hodgkin lymphoma, head and neck cancer, and urothelial cancer. This paper describes the recently identified feature of pembrolizumab pharmacokinetics, the time-dependent or time-varying CL. Overall results indicate that CL decreases over the treatment period of a typical patient in a pattern well described by a sigmoidal function of time with three parameters: the maximum proportion change in CL from baseline (approximately Imax or exactly eImax - 1), the time to reach Imax/2 (TI50), and a Hill coefficient. Best overall response per response evaluation criteria in solid tumor category was found to be associated with the magnitude of Imax.

Impact of patient characteristics on the pharmacokinetics of corifollitropin alfa during controlled ovarian stimulation.

AIM: The aim of the present study was to characterize the pharmacokinetic profile of corifollitropin alfa and examine the relationships between dose, intrinsic factors [body weight, body mass index (BMI), age and race] and corifollitropin alfa pharmacokinetics. METHODS: Data from five phase II and III clinical trials of corifollitropin alfa were evaluated. All subjects included in the analysis received 60 - 180 µg corifollitropin alfa for controlled ovarian stimulation in a gonadotrophin-releasing hormone antagonist protocol followed by daily recombinant follicle stimulating hormone (rFSH) from day 8 onwards. Serum corifollitropin alfa levels (across the entire range of treatment) and total follicle stimulating hormone immunoreactivity levels (up to the start of rFSH treatment) were indicators of drug exposure. The analyses were performed using a nonlinear mixed-effects modelling approach. RESULTS: A total of 2630 subjects were treated with corifollitropin alfa, and 2557 subjects were evaluable for analysis. Body weight, BMI and race (Asian and Black vs. Caucasian) were significant determinants of corifollitropin alfa exposure. Dose-normalized corifollitropin alfa exposure was ~89% higher in women with a body weight of 50 kg vs. 90 kg (in subjects with a similar BMI of 24 kg m(-2) ); 14% higher in women with a BMI of 18 kg m(-2) vs. 32 kg m(-2) (provided they were of similar body weight); and ~15.7% lower in Asian subjects and 13% higher in Black subjects vs. Caucasian subjects. CONCLUSIONS: Body weight was the major determinant of corifollitropin alfa exposure; BMI and race (Asian and Black) were also determinants but to a lesser extent and without associated effects on clinical outcomes. Corifollitropin alfa dose adjustment is indicated, based on body weight but not for BMI or race. These recommendations are consistent with the product label.

Translational Modeling in Schizophrenia: Predicting Human Dopamine D2 Receptor Occupancy.

OBJECTIVES: To assess the ability of a previously developed hybrid physiology-based pharmacokinetic-pharmacodynamic (PBPKPD) model in rats to predict the dopamine D2 receptor occupancy (D2RO) in human striatum following administration of antipsychotic drugs. METHODS: A hybrid PBPKPD model, previously developed using information on plasma concentrations, brain exposure and D2RO in rats, was used as the basis for the prediction of D2RO in human. The rat pharmacokinetic and brain physiology parameters were substituted with human population pharmacokinetic parameters and human physiological information. To predict the passive transport across the human blood-brain barrier, apparent permeability values were scaled based on rat and human brain endothelial surface area. Active efflux clearance in brain was scaled from rat to human using both human brain endothelial surface area and MDR1 expression. Binding constants at the D2 receptor were scaled based on the differences between in vitro and in vivo systems of the same species. The predictive power of this physiology-based approach was determined by comparing the D2RO predictions with the observed human D2RO of six antipsychotics at clinically relevant doses. RESULTS: Predicted human D2RO was in good agreement with clinically observed D2RO for five antipsychotics. Models using in vitro information predicted human D2RO well for most of the compounds evaluated in this analysis. However, human D2RO was under-predicted for haloperidol. CONCLUSIONS: The rat hybrid PBPKPD model structure, integrated with in vitro information and human pharmacokinetic and physiological information, constitutes a scientific basis to predict the time course of D2RO in man.

Effect of a high-fat meal on the pharmacokinetics of 300-milligram posaconazole in a solid oral tablet formulation.

Posaconazole in oral suspension must be taken multiple times a day with food (preferably a high-fat meal) to ensure adequate exposure among patients. We evaluated the effect of food on the bioavailability of a new delayed-release tablet formulation of posaconazole at the proposed clinical dose of 300 mg once daily in a randomized, open-label, single-dose, two-period crossover study with 18 healthy volunteers. When a single 300-mg dose of posaconazole in tablet form (3 tablets × 100 mg) was administered with a high-fat meal, the posaconazole area under the concentration-time curve from 0 to 72 h (AUC0-72) and maximum concentration in plasma (Cmax) increased 51% and 16%, respectively, compared to those after administration in the fasted state. The median time to Cmax (Tmax) shifted from 5 h in the fasted state to 6 h under fed conditions. No serious adverse events were reported, and no subject discontinued the study due to an adverse event. Six of the 18 subjects reported at least one clinical adverse event; all of these events were mild and short lasting. The results of this study demonstrate that a high-fat meal only modestly increases the mean posaconazole exposure (AUC), ∼1.5-fold, after administration of posaconazole tablets, in contrast to the 4-fold increase in AUC observed previously for a posaconazole oral suspension given with a high-fat meal.

The effect of food on the high clearance drug asenapine after sublingual administration to healthy male volunteers.

PURPOSE: To determine the effects of food on the pharmacokinetics of sublingual asenapine. METHODS: Healthy male volunteers (n=26, age 19-53 years) randomly received a single sublingual dose of asenapine 5 mg after ≥ 10 h fasting (Treatment A, reference), after a high-fat meal (Treatment B) and after ≥ 10 h fasting with a high-fat meal at 4 h post-dose (Treatment C). Blood samples were drawn over 72 h to measure asenapine plasma concentrations. Effects of food intake on asenapine pharmacokinetics were assessed using bioequivalence criteria and evaluated using a compartmental modelling analysis. RESULTS: Compared with the reference, mean asenapine exposure (AUC0-last and AUC0-∞) was approximately 20 % lower after intake of a high-fat meal prior to dosing, whereas Cmax decreased by only about 10 %. When a high-fat meal was taken 4 h post-dose in the fasting state, asenapine concentrations were similar to the reference during the first 4 h post-dose. After the meal intake, asenapine concentrations decreased quickly for several hours. Compartmental modelling indicated that a transient 2.5-fold increase in asenapine clearance after eating could explain the asenapine concentration-time profiles for both food regimens. CONCLUSIONS: To our knowledge, this is the first study investigating the effect of food upon the sublingual administration of a drug. A high-fat meal taken before or 4 h post-dose of sublingual asenapine indirectly caused a transient increase in liver blood flow that resulted in a temporal increase in asenapine clearance. As the effects on asenapine exposure were small and not clinically relevant, no additional restrictions are required for the timing of food intake in relation to asenapine dosing.

Dopamine D2 receptor occupancy as a predictor of catalepsy in rats: a pharmacokinetic-pharmacodynamic modeling approach.

OBJECTIVES: Dopamine D2 receptor occupancy (D2RO) is the major determinant of efficacy and safety in schizophrenia drug therapy. Excessive D2RO (>80%) is known to cause catalepsy (CAT) in rats and extrapyramidal side effects (EPS) in human. The objective of this study was to use pharmacokinetic and pharmacodynamic modeling tools to relate CAT with D2RO in rats and to compare that with the relationship between D2RO and EPS in humans. METHODS: Severity of CAT was assessed in rats at hourly intervals over a period of 8 h after antipsychotic drug treatment. An indirect response model with and without Markov elements was used to explain the relationship of D2RO and CAT. RESULTS: Both models explained the CAT data well for olanzapine, paliperidone and risperidone. However, only the model with the Markov elements predicted the CAT severity well for clozapine and haloperidol. The relationship between CAT scores in rat and EPS scores in humans was implemented in a quantitative manner. Risk of EPS not exceeding 10% over placebo correlates with less than 86% D2RO and less than 30% probability of CAT events in rats. CONCLUSION: A quantitative relationship between rat CAT and human EPS was elucidated and may be used in drug discovery to predict the risk of EPS in humans from D2RO and CAT scores measured in rats.

Population pharmacokinetic-pharmacodynamic modeling of haloperidol in patients with schizophrenia using positive and negative syndrome rating scale.

The aim of this study was to develop a pharmacokinetic-pharmacodynamic (PKPD) model that quantifies the efficacy of haloperidol, accounting for the placebo effect, the variability in exposure-response, and the dropouts. Subsequently, the developed model was utilized to characterize an effective dosing strategy for using haloperidol as a comparator drug in future antipsychotic drug trials. The time course of plasma haloperidol concentrations from 122 subjects and the Positive and Negative Syndrome Scale (PANSS) scores from 473 subjects were used in this analysis. A nonlinear mixed-effects modeling approach was utilized to describe the time course of PK and PANSS scores. Bootstrapping and simulation-based methods were used for the model evaluation. A 2-compartment model adequately described the haloperidol PK profiles. The Weibull and Emax models were able to describe the time course of the placebo and the drug effects, respectively. An exponential model was used to account for dropouts. Joint modeling of the PKPD model with dropout model indicated that the probability of patients dropping out is associated with the observed high PANSS score. The model evaluation results confirmed that the precision and accuracy of parameter estimates are acceptable. Based on the PKPD analysis, the recommended oral dose of haloperidol to achieve a 30% reduction in PANSS score from baseline is 5.6 mg/d, and the corresponding steady-state effective plasma haloperidol exposure is 2.7 ng/mL. In conclusion, the developed model describes the time course of PANSS scores adequately, and a recommendation of haloperidol dose was derived for future antipsychotic drug trials.

Application of a mechanism-based disease systems model for osteoporosis to clinical data.

A recently proposed mechanism-based disease systems model for osteoporosis (Schmidt et al., J Pharmacokinet Pharmacodyn 38:873-900, 2011) was applied to clinical data from post-menopausal women (n = 767) receiving various doses of the selective estrogen receptor modulator tibolone. Plasma bone-specific alkaline phosphatase activity and urinary N-telopeptide were used as biomarkers reflecting the activity of osteoblasts (bone forming cells) and osteoclasts (bone removing cells), respectively. These data were analyzed in conjunction with data on osteocalcin and on bone mineral density (BMD) (both lumbar spine and total hip), which reflect the activity of both cell types. While the dynamics of bone turnover markers changes rapidly, closely following changes in the activity of bone cells, changes in BMD are slower and have their own dynamics. Application of the mechanism-based disease systems model to the clinical data allowed for an adequate description of the data and yielded parameter estimates that are consistent with physiological values reported in the literature (Lemaire et al., J Theor Biol 229:293-309, 2004). The fitted model enabled characterization of (i) the critical time scales involved in disease progression, (ii) the dynamics of the system during onset and offset of the therapeutic intervention, and (iii) the distinction between responders and low-responders to tibolone treatment.

Modelling and simulation of placebo effect: application to drug development in schizophrenia.

High and variable placebo effect (PE) within and among clinical trials can substantially affect conclusions about the efficacy of new drugs in the treatment of schizophrenia and other neuropsychiatric disorders. In recent years, it has become increasingly difficult to prove drug efficacy against placebo, and one of the reasons is that the placebo response has increased over recent years. The increased placebo response over the years is partly explained by unidentified parallel interventions, patient factors, issues with trial designs, and regional variability or demographic differences. In addition, a nocebo effect, which is undesirable effects a subject manifests after receiving placebo, e.g. extrapyramidal side effects, in placebo arms of antipsychotic trials could also influence the PE and clinical trial outcomes. Placebo effects (PEs) are a natural phenomenon and cannot be avoided completely in clinical trials. However, accounting for the PE via mixed effects modelling approaches could reduce bias in quantifying the overall effect size of the drug treatment. This review article focuses on the PE and its impact on schizophrenia clinical trial outcomes. The authors briefly describe the factors that lead to high and variable PE. Next, pharmacometric approaches to account for the PE and dropouts in schizophrenia clinical trials are described. Finally, some points are provided that could be considered while designing and optimizing antipsychotic trials via simulation approaches.

Pediatric oncology drug development and dosage optimization.

Oncology drug discovery and development has always been an area facing many challenges. Phase 1 oncology studies are typically small, open-label, sequential studies enrolling a small sample of adult patients (i.e., 3-6 patients/cohort) in dose escalation. Pediatric evaluations typically lag behind the adult development program. The pediatric starting dose is traditionally referenced on the recommended phase 2 dose in adults with the incorporation of body size scaling. The size of the study is also small and dependent upon the prevalence of the disease in the pediatric population. Similar to adult development, the dose is escalated or de-escalated until reaching the maximum tolerated dose (MTD) that also provides desired biological activities or efficacy. The escalation steps and identification of MTD are often rule-based and do not incorporate all the available information, such as pharmacokinetic (PK), pharmacodynamic (PD), tolerability and efficacy data. Therefore, it is doubtful if the MTD approach is optimal to determine the dosage. Hence, it is important to evaluate whether there is an optimal dosage below the MTD, especially considering the emerging complexity of combination therapies and the long-term tolerability and safety of the treatments. Identification of an optimal dosage is also vital not only for adult patients but for pediatric populations as well. Dosage-finding is much more challenging for pediatric populations due to the limited patient population and differences among the pediatric age range in terms of maturation and ontogeny that could impact PK. Many sponsors defer the pediatric strategy as they are often perplexed by the challenges presented by pediatric oncology drug development (model of action relevancy to pediatric population, budget, timeline and regulatory requirements). This leads to a limited number of approved drugs for pediatric oncology patients. This review article provides the current regulatory landscape, incentives and how they impact pediatric drug discovery and development. We also consider different pediatric cancers and potential clinical trial challenges/opportunities when designing pediatric clinical trials. An outline of how quantitative methods such as pharmacometrics/modelling & simulation can support the dosage-finding and justification is also included. Finally, we provide some reflections that we consider helpful to accelerate pediatric drug discovery and development.

Characterizing the exposure-response relationship of idecabtagene vicleucel in patients with relapsed/refractory multiple myeloma.

Idecabtagene vicleucel (ide-cel; bb2121) is a B-cell maturation antigen-directed chimeric antigen receptor (CAR) T cell therapy approved for treatment of patients with heavily pretreated relapsed and refractory multiple myeloma. This analysis evaluated exposure-response (ER) relationships of ide-cel with key efficacy end points and safety events. Ide-cel exposure data were available from 127 patients treated at target doses of 150, 300, or 450 × 106 CAR+ T cells from the phase II KarMMa study (NCT03361748). Key exposure metrics, including area under the curve of the transgene level from 0 to 28 days and maximum transgene level, were calculated using noncompartmental methods. Logistic regression models, using both linear and maximum response function of exposure on the logit scale, were evaluated to quantify observed ER trends, and modified by including statistically significant individual covariates in a stepwise regression analysis. There was wide overlap of exposures across the target doses. ER relationships were observed for the overall and complete response rates, with higher response rates associated with higher exposures. Model-based evaluations identified female sex and baseline serum monoclonal protein less than or equal to 10 g/L as predictive of a higher objective response rate and a higher complete response rate, respectively. ER relationships were observed for safety events of cytokine release syndrome requiring tocilizumab or corticosteroids. The established ER models were used to quantify the ide-cel dose-response, which showed a positive benefit-risk assessment for the range of ide-cel exposures associated with the target dose range of 150-450 × 106 CAR+ T cells.

Model-Informed Dose Justifications of Posaconazole in Japanese Patients for Prophylaxis and Treatment Against Fungal Infection.

Posaconazole is a globally approved broad-spectrum triazole antifungal compound. In Japanese patients, posaconazole has identical dosing regimens as those approved globally for both tablet and intravenous formulations. This article aims to describe a model-informed approach for dose justification of posaconazole in the Japanese population as either high-risk patients with fungal infections (prophylaxis patients) or patients with fungal infections (treatment patients). A simultaneous population pharmacokinetic (PK) model for tablet and intravenous formulation was developed on the basis of a data set including Japanese data from healthy participants and treatment patients. The PK profiles and exposure distributions in Japanese patients were predicted and compared against foreign patients, that is, patients outside of Japan. Relationships between the post hoc posaconazole exposures and frequently observed clinical adverse events were evaluated. Although clinical trials for Japanese prophylaxis patients were not conducted, PK profiles in Japanese prophylaxis patients were predicted using the population PK model and demographic covariate information obtained from the published literature. Based upon the globally approved dosing regimen, posaconazole exposure distribution was predicted to be the highest in Japanese treatment patients, and generally similar between Japanese and foreign prophylaxis patients. Exposures in Japanese patients exceeded the efficacy target level (500 ng/mL). Safety profiles in Japanese treatment patients with the highest exposures were clinically acceptable without specific concerns to Japanese patients and appeared to have no relationship with posaconazole exposures. From PK, safety, and efficacy perspectives, the use of the same dosing regimen as in foreign patients was justified in Japanese prophylaxis and treatment patients.

Population PK and Semimechanistic PK/PD Modeling and Simulation of Relugolix Effects on Testosterone Suppression in Men with Prostate Cancer.

Relugolix, the first orally active, nonpeptide gonadotropin-releasing hormone receptor antagonist, is approved in the United States and the European Union for the treatment of adult patients with advanced prostate cancer. The recommended dosing regimen is a 360-mg loading dose followed by a 120-mg daily dose. Relugolix and testosterone concentration data and clinical information from two phase I studies, two phase II studies, and the phase III safety and efficacy study (HERO) were used to develop a population pharmacokinetic (PopPK) model and a semimechanistic population pharmacokinetic/pharmacodynamic (PopPK/PD) model that characterized relugolix exposure and its relationship to testosterone concentrations. Age, body weight, and Black/African American race had at most minimal effects on relugolix exposure or testosterone concentrations with no clinical relevance. Simulations using the PopPK/PD model confirmed the recommended dosing regimen of relugolix, with the median simulated testosterone concentrations predicted to achieve castration levels (< 50 ng/dL) and profound castration levels (< 20 ng/dL) by day 2 and day 9, respectively, and demonstrated that 97.3% and 85.5% of the patients remained at castration levels (< 50 ng/dL) upon temporary interruption of treatment for 7 days and 14 days, respectively. Collectively, simulations based on the PopPK and PopPK/PD models were consistent with actual data from clinical studies, reflecting the high predictiveness of the models and supporting the reliability of model-based simulations. These models can be used to provide guidance regarding dosing recommendations under various circumstances (e.g., temporary interruption of treatment, if needed) for relugolix.

Model-based meta-analysis of non-small cell lung cancer with standard of care PD-1 inhibitors and chemotherapy for early development decision making.

Single-arm cohorts/trials are often used in early phase oncology programs to support preliminary clinical activity assessments for investigational products, administered alone or in combination with standard of care (SOC) agents. Benchmarking clinical activity of those combinations against other treatments, including SOC, requires indirect comparisons against external trials, which presents challenges including cross-study differences in trial populations/other factors. To facilitate such nonrandomized comparisons, we developed a comprehensive model-based meta-analysis (MBMA) framework to quantitatively adjust for factors related to efficacy in metastatic non-small cell lung cancer (mNSCLC). Data were derived from 15 published studies assessing key programmed cell death protein-1 (PD-1) inhibitors pembrolizumab (n = 8) and nivolumab (n = 7), representing current SOC in mNSCLC. In the first stage, a mixed-effects logistic regression model for overall response rate (ORR) was developed accounting for effects of various population covariates on ORR. The ORR model results indicated an odds ratio (OR) of 1.02 for squamous versus non-squamous histology and OR of 1.20 for PD-ligand 1 tumor proportion score (TPS) per every 10% increase of TPS level. Next, a nonparametric mixed-effects model for overall survival (OS) was developed with ORR/other clinical covariates as input. Subsequently, MBMA simulations of relevant hypothetical scenarios involving single-arm trial design predicted OS hazard ratios as a function of ORR with matched patient characteristics. Findings from this MBMA and derived parameter estimates can be generally applied by the reader as a framework for interpreting efficacy data from early phase trials to support ORR-based go/no-go decisions and futility rules, illustrated through examples in this report.

Pharmacokinetic-pharmacodynamic modeling of the D2 and 5-HT (2A) receptor occupancy of risperidone and paliperidone in rats.

PURPOSE: A pharmacokinetic-pharmacodynamic (PK-PD) model was developed to describe the time course of brain concentration and dopamine D2 and serotonin 5-HT(2A) receptor occupancy (RO) of the atypical antipsychotic drugs risperidone and paliperidone in rats. METHODS: A population approach was utilized to describe the PK-PD of risperidone and paliperidone using plasma and brain concentrations and D2 and 5-HT(2A) RO data. A previously published physiology- and mechanism-based (PBPKPD) model describing brain concentrations and D2 receptor binding in the striatum was expanded to include metabolite kinetics, active efflux from brain, and binding to 5-HT(2A) receptors in the frontal cortex. RESULTS: A two-compartment model best fit to the plasma PK profile of risperidone and paliperidone. The expanded PBPKPD model described brain concentrations and D2 and 5-HT(2A) RO well. Inclusion of binding to 5-HT(2A) receptors was necessary to describe observed brain-to-plasma ratios accurately. Simulations showed that receptor affinity strongly influences brain-to-plasma ratio pattern. CONCLUSION: Binding to both D2 and 5-HT(2A) receptors influences brain distribution of risperidone and paliperidone. This may stem from their high affinity for D2 and 5-HT(2A) receptors. Receptor affinities and brain-to-plasma ratios may need to be considered before choosing the best PK-PD model for centrally active drugs.