The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
A disease is generally considered to be rare if it affects one patient per 200,000 people (1) and most rare diseases affect far fewer than this. However, collectively rare diseases are relatively common, affecting 350 million patients worldwide (2). The path to diagnosis for these patients is often a long, difficult battle and even once the diagnosis is made, it is likely there will be no suitable treatment available. For 90% of rare diseases, there is no approved therapy (2). There is, therefore, a pressing need to develop new, effective therapies that can bring hope to rare disease patients. However, the clinical development environment for life-threatening, rare diseases is fraught with challenges. By their very nature, rare indications have few patients and limited sample size. This scarcity of patients also results in a lack of available information and knowledge about the disease from the best endpoints, to the treatment effect size or the variability of response between subgroups.
No one plans to have a trial whose data collection needs rescuing. However, lagging enrollment rates, operational struggles, and diminished budgets can leave some trials in need of intervention. A great deal has been written about how to prevent the need for rescues (e.g., more investment in study planning and improved communication between stakeholders). Far less has been said about how to assemble a rescue team – the roles that need to be filled and the process of analysis that ensures the completion of a failing trial.
Nand Kishore Rawat is a Director and Head, Early Phase Biostatistics based in the King of Prussia, PA Cytel office. We recently spoke with Nand for the Cytel podcast to gain his thoughts on the unique aspects of Phase 1 development and where innovative approaches supported by thorough planning can meet these challenges head-on. Read on for key insights or listen to the podcast.
Happy New Year! As we look ahead to future successes and the new advancements in drug development that 2019 will bring, we are taking a moment to reflect on the topics that resonated most with our community on the Cytel blog in 2018. While these 6 most popular blogs encompass a variety of topics from across the data science, statistics, and statistical programming space, they all have in common a focus on innovative practices and application of statistical, data management, and data science excellence to achieve better outcomes in drug development.
In this blog, Paul Terrill, Director of Strategic Consulting at Cytel outlines his blueprint for ensuring smooth communication between statistical and clinical stakeholders. Paul draws upon his 20 years of experience working as a statistician and his training background to share his guidelines for success. Whether you are a statistician looking to hone your project communication skills, or a clinician keen to maximize the benefit of statistical input to your trial, this article will provide helpful pointers.
This is the third in our blog series ' The Good Data Submission Doctor' in which Angelo Tinazzi, Director of Standards, Systems and CDISC Consulting at Cytel tackles key issues in preparing data for CDISC submission. In the previous “Good Data Submission Doctor” blog Angelo discussed his top 5 SDTM FAQ; in this article he turns his attention to the top FAQs for ADaM. Read on for Angelo's insights.
Cytel biostatisticians Cyrus Mehta and Lingyun Liu, together with Charles Theuer, CEO of TRACON Pharmaceuticals have recently co-authored a publication in the journal Annals of Oncology: “ An Adaptive Population Enrichment Phase 3 Trial of TRC105 and Pazopanib Versus Pazopanib Alone in Patients with Advanced Angiosarcoma (TAPPAS Trial)”. The paper explores the features of this innovative population enrichment, adaptive sample size re-estimation trial and how it overcomes some fundamental challenges of clinical development in ultra-orphan oncology indications. The publication is timely, in the context of the August 2018 news that the FDA has launched a complex and innovative designs pilot program to facilitate and advance the use of complex adaptive, Bayesian, and other novel clinical trial designs in late-stage drug development. The initiative seeks to further innovation by allowing the FDA to publicly discuss those trial designs that are being considered through the pilot program. Indeed, the TAPPAS trial incorporated regulatory input from both the FDA and EMA and received a Special Protocol Assessment from the FDA. As of the date of publication, the authors were not aware of any other pivotal population enrichment trial that has been implemented in oncology, and therefore the paper’s deconstruction of the design’s key elements will be invaluable to researchers considering similar innovative approaches.
In this second post of the “Good Data Submission Doctor” ( read my first post The Master Recipe: Quality and Attention to Detail Matter here) I would like to go through some of my favorite SDTM Frequently Asked Questions. These are questions I regularly receive in my capacity as a CDISC Subject Matter Expert, either from my colleagues or from the sponsor. Let’s start by taking a look at five of the most recent.