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Master protocol studies typically use an overarching protocol to answer several questions by guiding a variety of sub-studies. These sub-studies can incorporate multiple diseases, therapies, or both. Although this innovative approach offers many benefits, including the ability to deliver clinical research that is more patient-centric and efficient, several common barriers curtail widespread adoption. The Clinical Trials Transformation Initiative (CTTI) convened industry representatives, regulatory agencies, patient groups, and academic institutions to identify emerging best practices and develop resources designed to help sponsors and other stakeholders overcome these challenges. We first identify some broad changes needed in the clinical trials ecosystem to facilitate mainstream adoption of master protocol studies, and we subsequently summarize CTTI's resources designed to support this effort.
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Ecosistema , Humanos , UniversidadesRESUMEN
Drug development for rare diseases is challenged by small populations and limited data. This makes development of clinical trial protocols difficult and contributes to the uncertainty around whether or not a potential therapy is efficacious. The use of data standards to aggregate data from multiple sources, and the use of such integrated databases to develop statistical models can inform protocol development and reduce the risks in developing new therapies. Achieving regulatory endorsement of such models through defined pathways at the US Food and Drug Administration and European Medicines Authority allows such tools to be used by the drug development community for defined contexts of use without further need for discussion of the underlying model(s). The Duchenne Regulatory Science Consortium (D-RSC) has brought together multiple stakeholders to develop a clinical trial simulation tool for Duchenne muscular dystrophy using such an approach. Here we describe the work of D-RSC as an example of how such an approach may be effective at reducing uncertainty in drug development for rare diseases, and thus bringing effective therapies to patients faster.
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Modelos Biológicos , Distrofia Muscular de Duchenne/tratamiento farmacológico , Producción de Medicamentos sin Interés Comercial/métodos , Ensayos Clínicos como Asunto , Simulación por Computador , Humanos , Estados Unidos , United States Food and Drug AdministrationRESUMEN
The identification of the Duchenne muscular dystrophy gene and protein in the late 1980s led to high hopes of rapid translation to molecular therapeutics. These hopes were fueled by early reports of delivering new functional genes to dystrophic muscle in mouse models using gene therapy and stem cell transplantation. However, significant barriers have thwarted translation of these approaches to true therapies, including insufficient therapeutic material (eg, cells and viral vectors), challenges in systemic delivery, and immunological hurdles. An alternative approach is to repair the patient's own gene. Two innovative small-molecule approaches have emerged as front-line molecular therapeutics: exon skipping and stop codon read through. Both approaches are in human clinical trials and aim to coax dystrophin protein production from otherwise inactive mutant genes. In the clinically severe dog model of Duchenne muscular dystrophy, the exon-skipping approach recently improved multiple functional outcomes. We discuss the status of these two methods aimed at inducing de novo dystrophin production from mutant genes and review implications for other disorders.
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Codón de Terminación/genética , Distrofina/metabolismo , Exones/genética , Músculo Esquelético/metabolismo , Distrofia Muscular de Duchenne/terapia , Proteínas Mutantes/metabolismo , Animales , Perros , Distrofina/genética , Humanos , Ratones , Músculo Esquelético/citología , Distrofia Muscular de Duchenne/genética , Proteínas Mutantes/genéticaRESUMEN
Sharing clinical trial data can provide value to research participants and communities by accelerating the development of new knowledge and therapies as investigators merge data sets to conduct new analyses, reproduce published findings to raise standards for original research, and learn from the work of others to generate new research questions. Nonprofit funders, including disease advocacy and patient-focused organizations, play a pivotal role in the promotion and implementation of data sharing policies. Funders are uniquely positioned to promote and support a culture of data sharing by serving as trusted liaisons between potential research participants and investigators who wish to access these participants' networks for clinical trial recruitment. In short, nonprofit funders can drive policies and influence research culture. The purpose of this paper is to detail a set of aspirational goals and forward thinking, collaborative data sharing solutions for nonprofit funders to fold into existing funding policies. The goals of this paper convey the complexity of the opportunities and challenges facing nonprofit funders and the appropriate prioritization of data sharing within their organizations and may serve as a starting point for a data sharing toolkit for nonprofit funders of clinical trials to provide the clarity of mission and mechanisms to enforce the data sharing practices their communities already expect are happening.
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[This corrects the article DOI: 10.2196/23011.].
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INTRODUCTION: The Duchenne Regulatory Science Consortium (D-RSC) was established to develop tools to accelerate drug development for DMD. The resulting tools are anticipated to meet validity requirements outlined by qualification/endorsement pathways at both the U.S. Food and Drug Administration (FDA) and European Medicines Administration (EMA), and will be made available to the drug development community. The initial goals of the consortium include the development of a disease progression model, with the goal of creating a model that would be used to forecast changes in clinically meaningful endpoints, which would inform clinical trial protocol development and data analysis. Methods: In April of 2016 the consortium and other experts met to formulate plans for the development of the model. Conclusions: Here we report the results of the meeting, and discussion as to the form of the model that we plan to move forward to develop, after input from the regulatory authorities.