Mariam A. Ahmed

The FDA published guidance on assessing pharmacokinetics (PK) in participants with impaired renal function in 2024. The IQ CPLG Organ Impairment Working Group summarized the industry’s perspective on this guidance by highlighting a few key updates in the 2024 guidance, including: (1) the recommendation of using estimated glomerular filtration rate (eGFR) over the Cockcroft‐Gault (CG) equation to determine renal function; (2) the designs for dedicated renal impairment studies; and (3) characterizing the impact of impaired renal impairment in phase 2/3 trials. The use of absolute eGFR for dosing recommendations, differentiation between intermittent hemodialysis (IHD) and continuous renal replacement therapy (CRRT) in study design, and a preference for regression analysis over categorical analysis to model the relationship between renal function and PK parameters were also discussed. The updates in the FDA guidance resulted in better alignment with the European Medicines Agency (EMA) guidance on this topic, making global drug development more efficient. The manuscript also presented challenges in using different eGFR equations, the impact of protein binding on dose determination, and the need for further guidance on pediatric equations and novel drug modalities. In conclusion, the manuscript underscores the significance of the updated FDA guidance in enhancing the design, implementation, and data analysis of renal impairment studies while identifying areas for future updates to address emerging topics in drug development.

Clinical pharmacologists face unique challenges when developing drugs for rare diseases. These conditions are characterized by small patient populations, diverse disease progression patterns, and a limited understanding of underlying pathophysiology. This tutorial serves as a comprehensive guide, offering practical insights and strategies to navigate its complexities. In this tutorial, we outline global regulatory incentives and resources available to support rare disease research, describe some considerations for designing a clinical development plan for rare diseases, and we highlight the role of biomarkers, real‐world data, and modeling and simulations to navigate rare disease challenges. By leveraging these tools and understanding regulatory pathways, clinical pharmacologists can significantly contribute to advancing therapeutic options for rare diseases.

In the relentless pursuit of optimizing drug development, the intricate process of determining the ideal dosage unfolds. This involves “dose‐finding” studies, crucial for providing insights into subsequent registration trials. However, the challenges intensify when tackling rare diseases. The complexity arises from poorly understood pathophysiologies, scarcity of appropriate animal models, and limited natural history understanding. The inherent heterogeneity, coupled with challenges in defining clinical end points, poses substantial challenges, hindering the utility of available data. The small affected population, low disease awareness, and restricted healthcare access compound the difficulty in conducting dose‐finding studies. This white paper delves into critical dose selection aspects, focusing on key therapeutic areas, such as oncology, neurology, hepatology, metabolic rare diseases. It also explores dose selection challenges posed by pediatric rare diseases as well as novel modalities, including enzyme replacement therapies, cell and gene therapies, and oligonucleotides. Several examples emphasize the pivotal role of clinical pharmacology in navigating the complexities associated with these diseases and emerging treatment modalities.

Model‐informed approaches provide a quantitative framework to integrate all available nonclinical and clinical data, thus furnishing a totality of evidence approach to drug development and regulatory evaluation. Maximizing the use of all available data and information about the drug enables a more robust characterization of the risk–benefit profile and reduces uncertainty in both technical and regulatory success. This offers the potential to transform rare diseases drug development, where conducting large well‐controlled clinical trials is impractical and/or unethical due to a small patient population, a significant portion of which could be children. Additionally, the totality of evidence generated by model‐informed approaches can provide confirmatory evidence for regulatory approval without the need for additional clinical data. In the article, applications of novel quantitative approaches such as quantitative systems pharmacology, disease progression modeling, artificial intelligence, machine learning, modeling of real‐world data using model‐based meta‐analysis and strategies such as external control and patient‐reported outcomes as well as clinical trial simulations to optimize trials and sample collection are discussed. Specific case studies of these modeling approaches in rare diseases are provided to showcase applications in drug development and regulatory review. Finally, perspectives are shared on the future state of these modeling approaches in rare diseases drug development along with challenges and opportunities for incorporating such tools in the rational development of drug products.

Modeling the relationships between covariates and pharmacometric model parameters is a central feature of pharmacometric analyses. The information obtained from covariate modeling may be used for dose selection, dose individualization, or the planning of clinical studies in different population subgroups. The pharmacometric literature has amassed a diverse, complex, and evolving collection of methodologies and interpretive guidance related to covariate modeling. With the number and complexity of technologies increasing, a need for an overview of the state of the art has emerged. In this article the International Society of Pharmacometrics (ISoP) Standards and Best Practices Committee presents perspectives on best practices for planning, executing, reporting, and interpreting covariate analyses to guide pharmacometrics decision making in academic, industry, and regulatory settings.

The promise of viral vector‐based gene therapy (GT) as a transformative paradigm for treating severely debilitating and life‐threatening diseases is slowly coming to fruition with the recent approval of several drug products. However, they have a unique mechanism of action often necessitating a tortuous clinical development plan. Expertise in such complex therapeutic modality is still fairly limited in this emerging class of adeno‐associated virus (AAV) vector‐based gene therapies. Because of the irreversible mode of action and incomplete understanding of genotype–phenotype relationship and disease progression in rare diseases careful considerations should be given to GT product's benefit–risk profile. In particular, special attention needs to be paid to safe dose selection, reliable dose exposure response (including clinically relevant endpoints), or creative approaches in study design targeting small patient populations during clinical development. We believe that quantitative tools encompassed within model‐informed drug development (MIDD) framework fits quite well in the development of such novel therapies, as they enable us to benefit from the totality of data approach in order to support dose selection as well as optimize clinical trial designs, end point selection, and patient enrichment. In this thought leadership paper, we provide our collective experiences, identify challenges, and suggest areas of improvement in applications of modeling and innovative trial design in development of AAV‐based GT products and reflect on the challenges and opportunities for incorporating MIDD tools and more in rational development of these products.

Pediatric populations represent a major fraction of rare diseases and compound the intrinsic challenges of pediatric drug development and drug development for rare diseases. The intertwined complexities of pediatric and rare disease populations impose unique challenges to clinical pharmacologists and require integration of novel clinical pharmacology and quantitative tools to overcome multiple hurdles during the discovery and development of new therapies. Drug development strategies for pediatric rare diseases continue to evolve to meet the inherent challenges and produce new medicines. Advances in quantitative clinical pharmacology research have been a key component in advancing pediatric rare disease research to accelerate drug development and inform regulatory decisions. This article will discuss the evolution of the regulatory landscape in pediatric rare diseases, the challenges encountered during the design of rare disease drug development programs and will highlight the use of innovative tools and potential solutions for future development programs.