Exposure-response analysis after subcutaneous administration of RBP-7000, a once-a-month long-acting Atrigel formulation of risperidone

AIMS

A new, long-acting, subcutaneous (SC) formulation of risperidone (RBP-7000) has been developed for the treatment of schizophrenia to address issues of non-adherence associated with oral risperidone treatment. The objective of this work was to establish an exposure-response relationship between total active moiety (AM) plasma exposure (risperidone + 9-hydroxy-risperidone) and Positive and Negative Syndrome Scale (PANSS) or Clinical Global Impression severity (CGI-S) scores using data from a registration trial.

METHODS

This was a Phase 3 randomized, double-blind, placebo-controlled, multicenter study in 354 patients to evaluate the efficacy, safety and tolerability of RBP-7000 (90 mg and 120 mg). Non-linear mixed effects modelling was used to develop an integrated population pharmacokinetic/pharmacodynamic (PK/PD) model that included a joint PK model for risperidone and 9-hydroxy-risperidone with placebo and drug-effect models to establish the relation between total AM exposure and PANSS or CGI-S scores.

RESULTS

CYP2D6 poor and intermediate metabolizers had lower formation rates of 9-hydroxy-risperidone (94% and 76% lower, respectively) compared to the extensive CYP2D6 metabolizers. The maximum placebo-corrected relative decrease in PANSS score from baseline following RBP-7000 treatment was 5.4%, half of which could be achieved at plasma concentrations of 4.6 ng ml^-1 of the total AM. A proportional odds model for the CGI-S score related the total AM plasma concentration to the probability of improving/worsening scores over time.

CONCLUSIONS

Exposure-response analysis was established between total AM concentrations and PANSS and CGI-S scores, with good precision in parameter estimates. CYP2D6 phenotype on risperidone metabolism was the only identified covariate.

Allometry Is a Reasonable Choice in Pediatric Drug Development

Pharmacokinetics (PK) plays a key role in bridging drug efficacy and safety from adults to pediatric patients. The principal purpose of projecting dosing in pediatrics is to guide trial design, not to waive the study per se. This research was designed to evaluate whether the allometric scaling (AS) approach is a satisfactory method to design PK studies in pediatric patients aged 2 years and older. We systematically evaluated drugs that had pediatric label information updated from 1998 to 2015. Only intravenous (IV) or oral administration drugs with available PK information in both children and adults from FDA-approved labels were included. The allometric scaling approach was used to extrapolate adult clearance to pediatric clearance. The relative difference between the observed and the allometric scaling approach-predicted clearance was summarized and used to evaluate the predictive power of the allometric scaling approach. A total of 36 drugs eliminated by a metabolic pathway and 10 drugs by the renal pathway after intravenous (IV) or oral administration were included. Regardless of the administration route, elimination pathway, and age group, the allometric scaling approach can predict clearance in pediatric patients within a 2-fold difference; 18 of the included drugs were predicted within a 25% difference, and 31 drugs within a 50% difference. The allometric scaling approach can adequately design PK studies in pediatric subjects 2 years and older.

Population Pharmacokinetics of an Intranasally Administered Combination of Oxymetazoline and Tetracaine in Healthy Volunteers

The primary objective of the current investigation was to establish the pharmacokinetic characteristics of oxymetazoline and tetracaine's primary metabolite, para-butylaminobenzoic acid (PBBA), after the intranasal administration of oxymetazoline/tetracaine. Thirty-six subjects contributing a total of 1791 plasma concentration results from 2 open-label trials were utilized. Model development was achieved using data from the second trial (N = 24) in which 0.3 mg oxymetazoline/18 mg tetracaine was administered. External model validation utilized data from the first trial (N = 12), which included doses of 0.3 mg oxymetazoline/18 mg tetracaine and 0.6 mg oxymetazoline/36 mg tetracaine. Oxymetazoline and PBBA dispositions were described by a 2-compartment model with first-order absorption. An allometric model for body weight was included on volumes and clearances to describe unexplained between-subject variability. The final oxymetazoline parameter estimates were k_a 4.41 h^-1 ; peripheral volume 418 L; clearance 66.4 L/h; central volume 6.97 L; and intercompartmental clearance 419 L/h for a 70-kg subject. The final PBBA parameter estimates were k_a 8.51 h^-1 ; peripheral volume 32.0 L; clearance 16.7 L/h; central volume 29.8 L; and intercompartmental clearance 2.43 L/h for a 70-kg subject. Between-subject variability ranged from 14% to 39% for oxymetazoline and from 10% to 94% for PBBA.

Challenges in developing drugs for pediatric CNS disorders: A focus on psychopharmacology

Many psychiatric and behavioral disorders manifest in childhood (attention deficit hyperactivity disorder, obsessive compulsive disorder, anxiety, depression, schizophrenia, autism spectrum disorder, etc.) and the opportunity for intervening early may attenuate full development of the disorder and lessen long term disability. Yet, pediatric drug approvals for CNS indications are limited, and pediatric testing generally occurs only after establishing adult efficacy, more as an afterthought rather than with the initial goal of developing the medication for a pediatric CNS indication. With pharmaceutical companies decreasing funding of their neuroscience research divisions overall, the prospects for moving promising investigational drugs forward into pediatrics will only decline. The goal of this review is to highlight important challenges around pediatric drug development for psychiatric disorders, specifically during clinical development, and to present opportunities for filling these gaps, using new strategies for de-risking investigational drugs in new clinical trial designs/models. We will first present the current trends in pediatric drug efficacy testing in academic research and in industry trials, we will then discuss the regulatory landscape of pediatric drug testing, including policies intended to support and encourage more testing. Obstacles that remain will then be presented, followed by new designs, funding opportunities and considerations for testing investigational drugs safely.

Genetics-based pediatric warfarin dosage regimen derived using pharmacometric bridging

BACKGROUND

Warfarin dosage regimens using CYP2C9 and VKORC1 polymorphisms have been extensively studied in adults and is included in US Food and Drug Administration-approved warfarin labeling. However, no dosage algorithm is available for pediatric patients.

OBJECTIVE

To derive a genetics-based pediatric dosge regimen for warfarin, including starting dose and titration scheme.

METHODS

A model-based approach was developed based on a previously validated warfarin dosage model in adults, with subsequent comparison to pediatric data from pediatric warfarin dose, genotyping, and international normalized ratio (INR) results. The adult model was based on a previously established model from the CROWN (CReating an Optimal Warfarin dosing Nomogram) trial. Pediatric warfarin data were obtained from a study conducted at the Children's Hospital of Los Angeles with 26 subjects. Variant alleles of CYP2C9 (rs1799853 or *2, and rs1057910 or *3) and the VKORC1 single nucleotide polymorphism (SNP) rs9923231 (-1639 G>A) were assessed, where the rs numbers are reference SNP identification tags assigned by the National Center for Biotechnology Information.

RESULTS

A pediatric warfarin model was derived using the previously validated model and clinical pharmacology considerations. The model was validated, and clinical trial simulation and stochastic modeling were used to optimize pediatric dosage and titration. The final dosage regimen was optimized based on simulations targeting a high (≥60%) proportion of INRs within the therapeutic range by week 2 of warfarin therapy while minimizing INRs >3.5 or <2.

CONCLUSIONS

The proposed pediatric warfarin dosage scheme based on individual CYP2C9 (alleles *1,*2,*3) and VKORC1 rs9923231 (-1639 G>A) genotypes may offer improved dosage compared to current treatment strategies, especially in patients with variant CYP2C9 and VKORC1 alleles. This pilot study provides the foundation for a larger prospective evaluation of genetics-based warfarin dosage in pediatric patients.

Considerations in Analyzing Single-Trough Concentrations Using Mixed-Effects Modeling

The purpose of this study was to assess the effect of trial design and data analysis choices on the bias and precision of pharmacokinetic (PK) parameter estimation. NONMEM was used to simulate and analyze plasma concentrations collected according to a dense (five samples) or sparse (single-trough samples) sampling scheme for a one-compartment open model with intravenous administration. The results indicated that the bias on estimates of CL with only single-trough data was 17% compared to less than 1% for only dense data. The estimates of CL were improved by fixing all other parameters and estimating only mean and variance of CL (-11% to 1.4%, depending on the estimation method). Adding dense data led to further improvements (-2.3% to 0.3%, depending on further improvements). In these cases, first-order conditional estimation (FOCE) methods resulted in better estimates of CL than first-order (FO) methods. These steps also improved the Bayesian estimates of CL. These studies support the following recommendations: (1) avoid collecting single-trough concentrations unless there is reasonable knowledge about the PK of the drug; (2) if collecting single-trough concentrations is inevitable, avoid estimating all parameters when modeling single-trough concentration data; (3) use prior information by modeling the single-trough concentration data along with dense data from other studies; and (4) use Bayes estimates if the PK model and its parameters are known with reasonable certainty.

The Role of SN-38 Exposure,UGT1A1*28Polymorphism, and Baseline Bilirubin Level in Predicting Severe Irinotecan Toxicity

Irinotecan, an anticancer drug, is associated with severe and potentially fatal diarrhea and neutropenia. The objective of this analysis was to evaluate the role of SN-38 exposure, the active metabolite of irinotecan, UGT1A1 genotypes, and baseline bilirubin on the maximum decrease (nadir) in absolute neutrophil counts following irinotecan. This analysis extended the work of a previous study that examined the effect of UGT1A1 genotypes on the incidence of severe neutropenia in 86 advanced cancer patients following irinotecan treatment. Regression analysis showed that the absolute neutrophil count nadir depended on SN-38 exposure (AUC) and UGT1A1*28 homozygous 7/7 genotype. An increased SN-38 AUC and the 7/7 genotype were significantly associated with a lower absolute neutrophil count nadir (R2 = .49). An alternate model suggested that higher baseline bilirubin and the 7/7 genotype were also significantly associated with a lower absolute neutrophil count nadir, although with a lower coefficient of determination (R2 = .31). Based on these findings and other reports, the irinotecan label was modified to indicate the role of UGT1A1*28 polymorphism in the metabolism of irinotecan and the associated increased risk of severe neutropenia. The label modifications also included recommendations for lower starting doses of irinotecan in patients homozygous for the UGT1A1*28 (7/7) polymorphism.

Impact of pharmacometric analyses on new drug approval and labelling decisions: a review of 198 submissions between 2000 and 2008

Pharmacometric analyses have become an increasingly important component of New Drug Application (NDA) and Biological License Application (BLA) submissions to the US FDA to support drug approval, labelling and trial design decisions. Pharmacometrics is defined as a science that quantifies drug, disease and trial information to aid drug development, therapeutic decisions and/or regulatory decisions. In this report, we present the results of a survey evaluating the impact of pharmacometric analyses on regulatory decisions for 198 submissions during the period from 2000 to 2008. Pharmacometric review of NDAs included independent, quantitative analyses by FDA pharmacometricians, even when such analysis was not conducted by the sponsor, as well as evaluation of the sponsor's report. During 2000-2008, the number of reviews with pharmacometric analyses increased dramatically and the number of reviews with an impact on approval and labelling also increased in a similar fashion. We also present the impact of pharmacometric analyses on selection of paediatric dosing regimens, approval of regimens that had not been directly studied in clinical trials and provision of evidence of effectiveness to support a single pivotal trial. Case studies are presented to better illustrate the role of pharmacometric analyses in regulatory decision making.

Bayesian quantitative disease-drug-trial models for Parkinson's disease to guide early drug development

The problem we have faced in drug development is in its efficiency. Almost a half of registration trials are reported to fail mainly because pharmaceutical companies employ one-size-fits-all development strategies. Our own experience at the regulatory agency suggests that failure to utilize prior experience or knowledge from previous trials also accounts for trial failure. Prior knowledge refers to both drug-specific and nonspecific information such as placebo effect and the disease course. The information generated across drug development can be systematically compiled to guide future drug development. Quantitative disease-drug-trial models are mathematical representations of the time course of biomarker and clinical outcomes, placebo effects, a drug's pharmacologic effects, and trial execution characteristics for both the desired and undesired responses. Applying disease-drug-trial model paradigms to design a future trial has been proposed to overcome current problems in drug development. Parkinson's disease is a progressive neurodegenerative disorder characterized by bradykinesia, rigidity, tremor, and postural instability. A symptomatic effect of drug treatments as well as natural rate of disease progression determines the rate of disease deterioration. Currently, there is no approved drug which claims disease modification. Regulatory agency has been asked to comment on the trial design and statistical analysis methodology. In this work, we aim to show how disease-drug-trial model paradigm can help in drug development and how prior knowledge from previous studies can be incorporated into a current trial using Parkinson's disease model as an example. We took full Bayesian methodology which can allow one to translate prior information into probability distribution.

Pharmacometrics 2020

This special issue of the Journal of Clinical Pharmacology is dedicated to pharmacometrics, covering topics related to methodological research, application to decisions, standardization, PhRMA survey, and growth strategy. Innovative methodological and technological advances in analyzing disease, drug, and trial data have equipped pharmacometricians with the know-how to influence high-level decisions, which in turn creates more pharmacometric opportunities. Pharmacometrics is revolutionizing drug development and regulatory decision making. To sustain the success and growth of this field, we need to up the ante. Strategic goals for pharmacometric groups in industry, regulatory agencies, and academia are proposed in this report. These goals should be of significance to all stakeholders who have a vested interest in drug development and therapeutics. The future of pharmacometrics depends on how well we all can deliver on the strategic goals.

Exposure-response of posaconazole used for prophylaxis against invasive fungal infections: evaluating the need to adjust doses based on drug concentrations in plasma

The purpose of this article is to report the exposure-response (E-R) relationship of posaconazole oral suspension (POS) for prophylaxis against invasive fungal infections (IFIs), on the basis of the US Food and Drug Administration (FDA) clinical pharmacology review of two randomized, active-controlled clinical studies. Posaconazole average steady state plasma concentrations (C(avg)) ranged from 22 to 3,650 ng/ml after administration of POS 200 mg three times daily (t.i.d.). In a double-blind, randomized clinical trial, the quartile ranges of C(avg) with midpoint values of 289, 736, 1,239, and 2,607 ng/ml had clinical failure rates of 44, 21, 18, and 18%, respectively, indicating an inverse association between C(avg) and clinical failure rate. There were no significant relationships between C(avg) and posaconazole-related major adverse events. Determining posaconazole concentrations in plasma will aid in assessing the need for either POS dose adjustment (e.g., increasing the POS dose) or switching to another systemic antifungal drug, thereby improving the effectiveness of prophylaxis against IFIs.

Leveraging prior quantitative knowledge in guiding pediatric drug development: a case study

The manuscript presents the FDA's focus on leveraging prior knowledge in designing informative pediatric trial through this case study. In developing written request for Drug X, an anti-hypertensive for immediate blood pressure (BP) control, the sponsor and FDA conducted clinical trial simulations (CTS) to design trial with proper sample size and support the choice of dose range. The objective was to effectively use prior knowledge from adult patients for drug X, pediatric data from Corlopam (approved for a similar indication) trial and general experience in developing anti-hypertensive agents. Different scenarios governing the exposure response relationship in the pediatric population were simulated to perturb model assumptions. The choice of scenarios was based on the past observation that pediatric population is less responsive and sensitive compared with adults. The conceptual framework presented here should serve as an example on how the industry and FDA scientists can collaborate in designing the pediatric exclusivity trial. Using CTS, inter-disciplinary scientists with the sponsor and FDA can objectively discuss the choice of dose range, sample size, endpoints and other design elements. These efforts are believed to yield plausible trial design, qrational dosing recommendations and useful labeling information in pediatrics.

Biomarkers in clinical drug development

The primary purpose of this Commentary is to complement the description of biomarkers given in this issue in the Pharmaceutical Research and Manufacturers of America report by Lathia et al. I offer several examples of the use of biomarkers that highlight their value in drug development and regulatory decision making.

Endpoints and analyses to discern disease-modifying drug effects in early Parkinson's disease

Parkinson's disease is an age-related degenerative disorder of the central nervous system that often impairs the sufferer's motor skills and speech, as well as other functions. Symptoms can include tremor, stiffness, slowness of movement, and impaired balance. An estimated four million people worldwide suffer from the disease, which usually affects people over the age of 60. Presently, there is no precedent for approving any drug as having a modifying effect (i.e., slowing or delaying) for disease progression of Parkinson's disease. Clinical trial designs such as delayed start and withdrawal are being proposed to discern symptomatic and protective effects. The current work focused on understanding the features of delayed start design using prior knowledge from published and data submitted to US Food and Drug Administration (US FDA) as part of drug approval or protocol evaluation. Clinical trial simulations were conducted to evaluate the false-positive rate, power under a new statistical analysis methodology, and various scenarios leading to patient discontinuations from clinical trials. The outcome of this work is part of the ongoing discussion between the US FDA and the pharmaceutical industry on the standards required for demonstrating disease-modifying effect using delayed start design.

Quantitative disease, drug, and trial models

Quantitative disease-drug-trial models allow learning from prior experience and summarize the knowledge in a ready to apply format. Employing these models to plan future development is proposed as a powerful solution to improve pharmaceutical R&D productivity. The disease and trial models are, to a large extent, independent of the product, but the drug model is not. The goals are to apply the disease and trial models to future development and regulatory decisions, and publicly share them. We propose working definitions of these models, describe the various subcomponents, provide examples, and discuss the challenges and potential solutions for developing such models. Building useful disease-drug-trial models is a challenging task and cannot be achieved by any single organization. It requires a consorted effort by industry, academic, and regulatory scientists. We also describe the strategic goals of the FDA Pharmacometrics group.

Leveraging prior quantitative knowledge to guide drug development decisions and regulatory science recommendations: impact of FDA pharmacometrics during 2004-2006

The End-of-Phase 2A meetings are proposed to identify opportunities to make innovative medical products available sooner and to increase the quality of drug applications through early meetings between sponsors and the FDA. This article summarizes the overall experience across 11 pilot End-of-Phase 2A meetings since 2004. Four case studies are presented in more detail to demonstrate the various issues and methods encountered at these meetings. Overall, industry and FDA scientists ranked these meetings to be "very helpful" (average score of 4 on a scale of 1 to 5). In almost all the instances the sponsors changed their drug development plans subsequent to these extensive quantitative analyses-based meetings. A draft Guidance is being developed to be issued in 2008, and we hope this initiative will be resourced by then.

Optimising piperacillin/tazobactam dosing in paediatrics

Piperacillin/tazobactam, an intravenous antibacterial combination product, has recently been approved for paediatric (age 2 months to 17 years) use in the USA. The purpose of this analysis is to describe the basis for the dosing recommendations in this age group. Pharmacokinetic (PK) parameters and demographic covariates from 53 children enrolled in two paediatric studies were used in the analysis. Individual drug clearance (CL) values calculated by non-compartmental methods were available. The influence of demographic covariates on CL was investigated by non-linear regression. The analysis identified CL to be dependent on body weight. CL was also found to be influenced by age in paediatric patients<or=2 years, which is consistent with the expectation based on maturation of renal function. The population PK analysis and simulations, utilising comparable adult exposures as a basis to explore optimal dosing, resulted in the following dosing recommendations: for paediatric patients>or=9 months, a dose of 100/12.5 mg/kg every 8h showed exposures similar to adults; for paediatric patients aged 2-9 months, the dose of 100/12.5 mg/kg should be reduced by a factor of 0.8 (i.e. 80/10 mg/kg), likely due to immature renal function. Based upon this analysis, dosing recommendations for paediatric patients down to 2 months of age were incorporated in the labelling. No data were available to allow additional recommendations for paediatric patients<2 months of age to be made.

Pharmacometrics at FDA: evolution and impact on decisions

Drug development and regulatory decisions are driven by information that is compiled primarily from clinical trials and other supportive experiments, but also through clinical experience in the post-market period. The wisdom of these decisions determines the efficiency of drug development, the decision to approve the drug, and the resultant drug product quality including guidance on how to use the product known as the label. Although the decisions are usually simple in nature (e.g., trial design and project progression at the company, product and labeling approval at the Food and Drug Administration (FDA)), the information informing the decision is complex and diverse.

Approval summary: sunitinib for the treatment of imatinib refractory or intolerant gastrointestinal stromal tumors and advanced renal cell carcinoma

PURPOSE

To describe the Food and Drug Administration (FDA) review and approval of sunitinib malate (Sutent). Sunitinib received regular approval for the treatment of gastrointestinal stromal tumor (GIST) after disease progression or intolerance to imatinib mesylate (Gleevec). Additionally, sunitinib received accelerated approval for the treatment of advanced renal cell carcinoma.

EXPERIMENTAL DESIGN

For the GIST indication, FDA reviewed data from a randomized, placebo-controlled trial with supportive evidence from a single-arm study. For the advanced renal cell carcinoma indication, FDA reviewed data from two single-arm studies of patients with cytokine-refractory metastatic renal cell carcinoma.

RESULTS

In patients with imatinib refractory or intolerant GIST, time-to-tumor progression of sunitinib-treated patients was superior to that of placebo-treated patients. Median time-to-tumor progression of sunitinib-treated patients was 27.3 weeks, compared with 6.4 weeks for placebo-treated patients (P < 0.0001). Partial responses were observed in 6.8% of sunitinib-treated patients. In patients with metastatic renal cell carcinoma, partial responses were observed in 25.5% (95% confidence interval, 17.5, 34.9) and 36.5% (95% confidence interval, 24.7, 49.6) of patients treated with sunitinib. Median response durations were 27.1 and 54 weeks. The most common adverse events attributed to sunitinib included diarrhea, mucositis, skin abnormalities, and altered taste. Reductions in left ventricular ejection fraction and severe hypertension were also more common in sunitinib-treated patients.

CONCLUSIONS

On January 26, 2006, the FDA approved sunitinib for the treatment of patients with imatinib refractory or intolerant GIST. Accelerated approval was granted for the treatment of advanced renal cell carcinoma.

Population pharmacokinetic-based dosing of intravenous busulfan in pediatric patients

The objective of this study was to characterize the pharmacokinetics (PK) of intravenous busulfan in pediatric patients and provide dosing recommendations. Twenty-four pediatric patients were treated with intravenous busulfan, 1.0 or 0.8 mg/kg for ages < or = 4 years or > 4 years, respectively, 4 times a day for 4 days. Dense PK sampling was performed. Body weight, age, gender, and body surface area were explored for effects on PK, and Monte Carlo simulations were performed to assess different dosing regimens. The PK of intravenous busulfan was described by a 1-compartment model with clearance of 4.04 L/h/20 kg and volume of distribution of 12.8 L/20 kg. Simulations indicated that the mg/kg and mg/m2 regimens were similar and achieved the desired target exposure in approximately 60% of patients. This model suggests that patients < or = 12 kg should be dosed at 1.1 mg/kg and those > 12 kg dosed at 0.8 mg/kg. Therapeutic drug monitoring and dose adjustment will further improve therapeutic targeting.

Impact of Pharmacometric Reviews on New Drug Approval and Labeling Decisions—a Survey of 31 New Drug Applications Submitted Between 2005 and 2006

Exploratory analyses of data pertaining to pharmacokinetic, pharmacodynamic, and disease progression are often referred to as the pharmacometrics (PM) analyses. The objective of the current report is to assess the role of PM, at the Food and Drug Administration (FDA), in drug approval and labeling decisions. We surveyed the impact of PM analyses on New Drug Applications (NDAs) reviewed over 15 months in 2005-2006. The survey focused on both the approval and labeling decisions through four perspectives: clinical pharmacology primary reviewer, their team leader, the clinical team member, and the PM reviewer. A total of 31 NDAs included a PM review component. Review of NDAs involved independent quantitative evaluation by FDA pharmacometricians. PM analyses were ranked as important in regulatory decision making in over 85% of the 31 NDAs. Case studies are presented to demonstrate the applications of PM analysis.