Application of Model-Informed Drug Development in Dose Selection and Optimization for siRNA Therapies.

The application of model-informed drug development (MIDD) has revolutionized drug development and regulatory decision making, transforming the process into one that is more efficient, effective, and patient centered. A critical application of MIDD is to facilitate dose selection and optimization, which play a pivotal role in improving efficacy, safety, and tolerability profiles of a candidate drug. With the surge of interest in small interfering RNA (siRNA) drugs as a promising class of therapeutics, their applications in various disease areas have been extensively studied preclinically. However, dosing selection and optimization experience for siRNA in humans is limited. Unique challenges exist for the dose evaluation of siRNA due to the temporal discordance between pharmacokinetic and pharmacodynamic profiles, as well as limited available clinical experience and considerable interindividual variability. This review highlights the pivotal role of MIDD in facilitating dose selection and optimization for siRNA therapeutics. Based on past experiences with approved siRNA products, MIDD has demonstrated its ability to aid in dose selection for clinical trials and enabling optimal dosing for the general patient population. In addition, MIDD presents an opportunity for dose individualization based on patient characteristics, enhancing the precision and effectiveness of siRNA therapeutics. In conclusion, the integration of MIDD offers substantial advantages in navigating the complex challenges of dose selection and optimization in siRNA drug development, which in turn accelerates the development process, supports regulatory decision making, and ultimately improves the clinical outcomes of siRNA-based therapies, fostering advancements in precision medicine across a diverse range of diseases.

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.

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.