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The Prescription Drug and User Fee Act (PDUFA), first enacted in 1992, was put in place to ensure timely FDA approval or licensure decisions of New Drug Applications (NDAs) and Biologics License Applications (BLAs). To streamline this decision-making process, the FDA developed a structured benefit-risk assessment framework designed to highlight uncertainties about a drug’s safety and efficacy in the indicated population and where new findings, as they become available in the post-market setting, can be incorporated into the framework.

Seasonal affective disorder (SAD), also known as major depressive disorder with a seasonal pattern, is a condition of regularly recurring depressive episodes that most commonly occur in autumn and winter and remit during spring and summer. Despite the relatively high prevalence and morbidity of SAD, this disorder still often goes undiagnosed, in large part because health care professionals do not generally consider a potential seasonal pattern in a patient who presents with depression.

Since the introduction of estimands, the answer to “Why are estimands necessary?” has remained constant – to allow for clearer communication about benefits/risks of a potential treatment to the relevant stakeholders. However, as illustrated in this blog, the number of questions as to how & when to use them has grown considerably.

Analyses conducted using the overall population can mask the extent of the benefit-risk in subgroups of patients.  Thus, subgroup analyses are critical to fully understand the benefit-risk in pivotal oncology trials and guide regulatory decisions for approval and labelling.  However, subgroup analyses also present several challenges especially for overall survival (OS) where larger sample sizes and longer follow-up are needed, and where early analyses of immature data may be conducted.

Real-World Data (RWD) is being increasingly utilized in clinical research to help support drug approvals. The U.S. Food and Drug Administration (FDA) guidance on Considerations for the Use of Real-World Data and Real-World Evidence (RWE) to Support Regulatory Decision-Making for Drug and Biological Products provides thoughtful recommendations on the use of RWE to support approval of a new indication for marketed drugs. This guidance is part of the FDAs Real-World Evidence Program which provides additional guidance for the use of RWE to support regulatory decisions.

Interim analyses (IA) are an essential part of clinical trials that—as a form of adaptive design—can help sponsors make informed decisions about whether to keep a trial going or discontinue it entirely. Join Rho’s Brett Gordon, Ben Vaughn, and Scott Mollan for this Q&A roundtable that will cover some of the most frequently asked questions they get from pharma companies about interim analysis.

Rho’s Anna Pinsky, MD, PhD, Medical Director, and Elina Smirnova, Associate Director of Start Up Services Europe are featured in Applied Clinical Trials as they take a deep dive into the European regulatory landscape and share their insights on how US Sponsors can keep their European clinical trials on schedule and within budget.

How do we get both information to rule out harm and assess the overall survival benefit, while still being realistic in our conduct of oncology clinical trials? The answer to that question, depends on a variety of factors, such as the type and aggressiveness of the cancer. As you are designing your next clinical trial assessing OS, we have listed some items to keep in mind.

Overall survival (OS) is an endpoint of significant importance when assessing safety and efficacy in oncology studies. Multiple trial design decisions are made when planning the analysis of OS and analysis of OS is even more complicated when it is analyzed as a non-primary endpoint. Here are some common trial design elements to consider that may have potential pitfalls for your next study.