Model-Informed Approaches to Support Drug Development for Patients With Obesity: A Regulatory Perspective.

Obesity, which is defined as having a body mass index of 30 kg/m2 or greater, has been recognized as a serious health problem that increases the risk of many comorbidities (eg, heart disease, stroke, and diabetes) and mortality. The high prevalence of individuals who are classified as obese calls for additional considerations in clinical trial design. Nevertheless, gaining a comprehensive understanding of how obesity affects the pharmacokinetics (PK), pharmacodynamics (PD), and efficacy of drugs proves challenging, primarily as obese patients are seldom selected for enrollment at the early stages of drug development. Over the past decade, model-informed drug development (MIDD) approaches have been increasingly used in drug development programs for obesity and its related diseases as they use and integrate all available sources and knowledge to inform and facilitate clinical drug development. This review summarizes the impact of obesity on PK, PD, and the efficacy of drugs and, more importantly, provides an overview of the use of MIDD approaches in drug development and regulatory decision making for patients with obesity: estimating PK, PD, and efficacy in specific dosing scenarios, optimizing dose regimen, and providing evidence for seeking new indication(s). Recent review cases using MIDD approaches to support dose selection and provide confirmatory evidence for effectiveness for patients with obesity, including pediatric patients, are discussed. These examples demonstrate the promise of MIDD as a valuable tool in supporting clinical trial design during drug development and facilitating regulatory decision-making processes for the benefit of patients with obesity.

Extrapolation of Efficacy from Adults to Pediatric Patients of Drugs for Treatment of Partial Onset Seizures: A Regulatory Perspective.

The US Food and Drug Administration (FDA) has concluded that the efficacy of drugs approved for the treatment of partial onset seizures (POS) in adults can be extrapolated to pediatric patients 1 month of age and above and that independent efficacy trials in this pediatric population are no longer needed. This paper focuses on the dosing, pharmacokinetic (PK), exposure-response, and clinical information that were leveraged from the approved drugs for the treatment of POS to conduct analyses that supported extrapolation of efficacy in pediatric patients. Clinical data from trials for eight drugs (levetiracetam, oxcarbazepine, topiramate, lamotrigine, gabapentin, perampanel, tiagabine, and vigabatrin) approved in both adults and pediatric patients for the treatment of POS were analyzed. Comparisons of exposures at approved doses, placebo response, and model-based exposure-response relationships were performed. Based on disease similarity, similar response to intervention, and similar exposure-response relationships in adults and pediatric patients, it was concluded that extrapolation of efficacy in pediatric patients aged 1 month and above is acceptable. PK analysis to determine pediatric dose and regimens that provide drug exposure similar to that known to be effective in adult patients with POS will be required, along with long-term open-label safety data in pediatric patients.

Model-Informed Drug Development in Pediatric Dose Selection.

Model-informed drug development (MIDD) has been a powerful and efficient tool applied widely in pediatric drug development due to its ability to integrate and leverage existing knowledge from different sources to narrow knowledge gaps. The dose selection is the most common MIDD application in regulatory submission related to pediatric drug development. This article aims to give an overview of the 3 broad categories of use of MIDD in pediatric dose selection: leveraging from adults to pediatric patients, leveraging from animals to pediatric patients, and integrating mechanism in infants and neonates. Population pharmacokinetic analyses with allometric scaling can reasonably predict the clearance in pediatric patients aged >5 years. A mechanistic-based approach, such as physiologically based pharmacokinetic accounting for ontogeny, or an allometric model with age-dependent exponent, can be applied to select the dose in pediatric patients aged ≤2 years. The exposure-response relationship from adults or from other drugs in the same class may be useful in aiding the pediatric dose selection and benefit-risk assessment. Increasing application and understanding of use of MIDD have contributed greatly to several policy developments in the pediatric field. With the increasing efforts of MIDD under the Prescription Drug User Fee Act VI, bigger impacts of MIDD approaches in pediatric dose selection can be expected. Due to the complexity of model-based analyses, early engagement between drug developers and regulatory agencies to discuss MIDD issues is highly encouraged, as it is expected to increase the efficiency and reduce the uncertainty.

Role of Model-Informed Drug Development in Pediatric Drug Development, Regulatory Evaluation, and Labeling.

The unique challenges in pediatric drug development require efficient and innovative tools. Model-informed drug development (MIDD) offers many powerful tools that have been frequently applied in pediatric drug development. MIDD refers to the application of quantitative models to integrate and leverage existing knowledge to bridge knowledge gaps and facilitate development and decision-making processes. This article discusses the current practices and visions of applying MIDD in pediatric drug development, regulatory evaluation, and labeling, with detailed examples. The application of MIDD in pediatric drug development can be broadly classified into 3 categories: leveraging knowledge for bridging the gap, dose selection and optimization, and informing clinical trial design. In particular, MIDD can provide evidence for the assumption of exposure-response similarity in bridging existing knowledge from reference to target population, support the dose selection and optimization based on the "exposure-matching" principle in the pediatric population, and increase the efficiency and success rate of pediatric trials. In addition, the role of physiologically based pharmacokinetics in drug-drug interaction in children and adolescents and in utilizing ontogeny data to predict pharmacokinetics in neonates and infants has also been illustrated. Moving forward, MIDD should be incorporated into all pediatric drug development programs at every stage to inform clinical trial design and dose selection, with both its strengths and limitations clearly laid out. The accumulated experience and knowledge of MIDD has and will continue to drive regulatory policy development and refinement, which will ultimately improve the consistency and efficiency of pediatric drug development.

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling.

Dose selection is one of the key decisions made during drug development in pediatrics. There are regulatory initiatives that promote the use of model-based drug development in pediatrics. Pharmacometrics or quantitative clinical pharmacology enables development of models that can describe factors affecting pharmacokinetics and/or pharmacodynamics in pediatric patients. This manuscript describes some examples in which pharmacometric analysis was used to support approval and labeling in pediatrics. In particular, the role of pharmacokinetic (PK) comparison of pediatric PK to adults and utilization of dose/exposure-response analysis for dose selection are highlighted. Dose selection for esomeprazole in pediatrics was based on PK matching to adults, whereas for adalimumab, exposure-response, PK, efficacy, and safety data together were useful to recommend doses for pediatric Crohn's disease. For vigabatrin, demonstration of similar dose-response between pediatrics and adults allowed for selection of a pediatric dose. Based on model-based pharmacokinetic simulations and safety data from darunavir pediatric clinical studies with a twice-daily regimen, different once-daily dosing regimens for treatment-naïve human immunodeficiency virus 1-infected pediatric subjects 3 to <12 years of age were evaluated. The role of physiologically based pharmacokinetic modeling (PBPK) in predicting pediatric PK is rapidly evolving. However, regulatory review experiences and an understanding of the state of science indicate that there is a lack of established predictive performance of PBPK in pediatric PK prediction. Moving forward, pharmacometrics will continue to play a key role in pediatric drug development contributing toward decisions pertaining to dose selection, trial designs, and assessing disease similarity to adults to support extrapolation of efficacy.

Precompetitive Data Sharing as a Catalyst to Address Unmet Needs in Parkinson's Disease.

Parkinson's disease is a complex heterogeneous disorder with urgent need for disease-modifying therapies. Progress in successful therapeutic approaches for PD will require an unprecedented level of collaboration. At a workshop hosted by Parkinson's UK and co-organized by Critical Path Institute's (C-Path) Coalition Against Major Diseases (CAMD) Consortiums, investigators from industry, academia, government and regulatory agencies agreed on the need for sharing of data to enable future success. Government agencies included EMA, FDA, NINDS/NIH and IMI (Innovative Medicines Initiative). Emerging discoveries in new biomarkers and genetic endophenotypes are contributing to our understanding of the underlying pathophysiology of PD. In parallel there is growing recognition that early intervention will be key for successful treatments aimed at disease modification. At present, there is a lack of a comprehensive understanding of disease progression and the many factors that contribute to disease progression heterogeneity. Novel therapeutic targets and trial designs that incorporate existing and new biomarkers to evaluate drug effects independently and in combination are required. The integration of robust clinical data sets is viewed as a powerful approach to hasten medical discovery and therapies, as is being realized across diverse disease conditions employing big data analytics for healthcare. The application of lessons learned from parallel efforts is critical to identify barriers and enable a viable path forward. A roadmap is presented for a regulatory, academic, industry and advocacy driven integrated initiative that aims to facilitate and streamline new drug trials and registrations in Parkinson's disease.

CYP2D6 genotype information to guide pimozide treatment in adult and pediatric patients: basis for the U.S. Food and Drug Administration's new dosing recommendations.

OBJECTIVE: The occurrence of pimozide-induced arrhythmias is concentration dependent. Hence, it is important for prescribers to consider causes of increased pimozide exposure. This article summarizes the U.S. Food and Drug Administration's (FDA's) review of drug interaction and pharmacogenomic studies and discusses pharmacokinetic simulations we performed to develop new cytochrome P450 2D6 (CYP2D6) genotype-guided dosing recommendations for pimozide. METHOD: Pharmacokinetic parameters by CYP2D6 genotype were derived from a published single-dose pharmacogenomic study of pimozide. We simulated what pimozide exposures would result from a multiple-dose scenario in different CYP2D6 genotype groups: extensive, intermediate, and poor metabolizers. The maximum dose for poor metabolizers was defined as the dose that would not exceed pimozide concentrations following 10 mg daily in extensive metabolizers and intermediate metabolizers (the current maximum dose in an unselected population). RESULTS: Dose-ranging analyses revealed that 4 mg daily in CYP2D6 poor metabolizers was the maximum dose that would not result in plasma concentrations in excess of those observed in extensive metabolizer and intermediate metabolizer patients receiving 10 mg daily. CYP2D6 genotyping is now consequently recommended in the pimozide product label before exceeding 4 mg of pimozide daily in adults or 0.05 mg/kg/d in children. Previously, dose adjustment was recommended every 3 days to achieve the desired clinical response for all patients. The label was modified to subsequently reflect that pimozide doses should not be increased earlier than 14 days in patients who are known CYP2D6 poor metabolizers. CONCLUSIONS: Given the risk of increased pimozide concentrations and longer time to steady state in CYP2D6 poor metabolizers, the FDA has revised the pimozide label to provide clinicians with clearer dosing, titration, and genotype testing recommendations. The new information is intended to enhance therapeutic individualization of pimozide in pediatric and adult patients.

Knowledge management for efficient quantitative analyses during regulatory reviews.

Knowledge management comprises the strategies and methods employed to generate and leverage knowledge within an organization. This report outlines the activities within the Division of Pharmacometrics at the US FDA to effectively manage knowledge with the ultimate goal of improving drug development and advancing public health. The infrastructure required for pharmacometric knowledge management includes provisions for data standards, queryable databases, libraries of modeling tools, archiving of analysis results and reporting templates for effective communication. Two examples of knowledge management systems developed within the Division of Pharmacometrics are used to illustrate these principles. The benefits of sound knowledge management include increased productivity, allowing reviewers to focus on research questions spanning new drug applications, such as improved trial design and biomarker development. The future of knowledge management depends on the collaboration between the FDA and industry to implement data and model standards to enhance sharing and dissemination of knowledge.

Vilazodone: clinical basis for the US Food and Drug Administration's approval of a new antidepressant.

OBJECTIVE: Vilazodone was recently approved by the US Food and Drug Administration (FDA) for the treatment of major depressive disorder (MDD). The purpose of this review is to summarize the FDA's approach to its review of the clinical pharmacology and the clinical efficacy and safety data for this new drug application, important issues in its decision-making, and its conclusions. DATA SOURCES: The data sources for this review were the original raw data sets for all clinical trials included in the development program for vilazodone, as well as the sponsor's original analyses of these data. STUDY SELECTION: Data were available from 24 human trials involving vilazodone, and included a total of 2,898 human subjects exposed to 1 or more doses of this drug. DATA EXTRACTION: The FDA had access to original raw data sets for these trials. RESULTS: Vilazodone is effective in treating MDD at a dose of 40 mg/d, but it needs to be incrementally adjusted to this dose to minimize gastrointestinal symptoms. It needs to be taken with food to ensure adequate plasma concentrations. Vilazodone's profile of adverse events is similar to that seen with selective serotonin reuptake inhibitors. No dose adjustment is needed based on age, gender, or renal or hepatic impairment. It is recommended that the vilazodone dose be reduced to 20 mg when it is taken with strong cytochrome P450 (CYP) 3A4 inhibitors, eg, ketoconazole. Vilazodone is not expected to have important effects on the clearance of other drugs that are cytochrome P450 substrates. CONCLUSIONS: Vilazodone is a new treatment for MDD, but it is unknown whether it has any advantages compared to other drugs in the antidepressant class.