Master protocols and platform clinical trials have become an innovative and efficient approach to testing multiple compounds in a single and consistent framework. But how can they be applied to animal studies? At the BAYES2022: Bayesian Biostatistics conference (October 12–14, 2022, in Bethesda, Maryland), Cytel’s VP of Scientific Strategy and Innovation Kyle Wathen and Senior Research Principal Krishna Padmanabhan will be presenting. Dr. Wathen’s abstract on such platform trials is below along with his commentary on this important and timely upcoming talk (See our previous post for more information on Dr. Padmanabhan’s talk.)
Platform Trials, Master Protocols, and Challenges in Execution
How can we build an efficient statistical protocol for a clinical trial, if we do not know the therapies that will be tested nor the populations on whom the testing will occur? This is the challenge confronting those working to design an ever-increasing number of platform trials. In a recent webinar, Dr. Kyle Wathen, Cytel’s Vice President of Scientific Strategy and Innovation, discussed a method using platform trials to show how to build such trials.
Quantitative Strategies for Rare Disease Clinical Trials
In 2023, rare diseases accounted for 30% of product pipeline under development, about half of which comprising non-oncology rare diseases. Clinical development in rare diseases has specific challenges. A primary challenge arises from the small populations from which clinical trial participants can be recruited, and from often limited prior knowledge on a disease. The challenge of small populations may be exacerbated by a reluctance of some patients to enroll in the control arm of the trial. Limited knowledge of the disease’s natural history and heterogenous clinical manifestation for many rare diseases leads to difficulty in defining appropriate endpoints that are feasibly measured in clinical trials and to high uncertainty of assumptions that can be used to estimate a trial’s success rate. Effective clinical development strategy for rare diseases requires agility to adapt to accumulating learning.
Here, I provide a brief overview on the construction of endpoints, adaptive and seamless clinical trial designs, Bayesian approaches, and the use of natural history studies in the development of rare disease studies.
Myth Busting: Master Protocol Edition
Interest and appetite for master protocols is growing as sponsors consider opportunities in various therapeutic areas beyond oncology. During initial discussions, most quickly recognize the potential operational and inferential benefits of a master protocol; however, as sponsors dive deeper into the details, doubt creeps in and there are a multitude of reasons expressed for not moving forward with a master protocol. Here are some common myths and the facts around them:
Navigating the Clinical Development Landscape: Insights for Success in 2024
After explosive and frenetic activity in the clinical trial industry during the COVID era, the past two years have seen challenging market dynamics and a drop-off in activity. Every one of us working in clinical development has felt this slowdown, but as we begin 2024, there is reason for optimism. The future looks promising. Here are some things to consider as you go forward.
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New Directions in Indirect Treatment Comparisons
When new treatments are compared with existing therapies in clinical care, population-adjustment techniques need to ensure that the populations in the compared treatments are similar. Key to this process is the identification of effect modifiers: that is, factors, like demographic characteristics or genetics, that can alter the effect of a treatment on a clinical outcome and impact relative effects. Ensuring an unbiased selection of effect modifiers can translate to more confident downstream decision-making throughout the process of obtaining payer approval.
Nitin Patel on 35 Years of Technological Innovation
On the occasion of Cytel’s 35th anniversary, co-founder Professor Nitin Patel sits down with us to discuss the founding of Cytel, its evolution over the last 35 years, and his vision for the future of the field.
On Frequentist and Bayesian Sequential Clinical Trial Designs
In clinical trials, patient enrollment is often staggered, with data collected sequentially. When designing a clinical trial, it is usually advantageous then to plan for interim analyses, which take a look at the accumulating data and present the potential for modifying the trial. Appropriately placed interim analyses are crucial because once a clinical trial has achieved enough data to determine its success or futility, decision-makers can plan for an early stop, saving resources and avoiding unnecessary enrollment. In a recent co-authored publication, University of Chicago Professor Yuan Ji, serving as Cytel’s executive advisor, describes the fundamental and philosophical differences between two approaches to determining this critical stopping point in such adaptive clinical trials: frequentist and Bayesian sequential clinical trial designs.
Operationally Seamless & Inferentially Seamless Adaptive Designs
Fulyzaq® from Napo/Salix was the first drug ever to be approved using an adaptive two-stage “seamless” clinical trial design. However, when Napo Pharmaceuticals sought orphan drug status for Crofelemer (made from the croton lechleri plant, pictured above left), it received a short window from the FDA in which to complete a Phase 3 trial for safety and efficacy. Aiming to diminish both time and cost, Napo submitted an adaptive design for a Crofelemer trial to the FDA. Initially, the design was rejected on grounds that it would not demonstrate strong control of the type-1 error rate.
Napo then approached Cytel consultants which advised it to consider a seamless adaptive trial. A seamless adaptive trial combines 2 phases of a study into one trial, thereby allowing a trial to complete within a short window. Using appropriate techniques, it is possible to conduct such studies while maintaining strong control of type-1 error.
A seamless adaptive design may be operationally seamless or inferentially seamless. An operationally seamless design is one in which a confirmatory trial proceeds after an exploratory one, but the data from the two are kept distinct. By contrast, an inferentially seamless trial combines data from both phases to make the final inference. Due to these two varieties of seamless adaptive designs, Napo/Salix had the following 3 trial designs from which to choose:
Negative Binomial Distribution in Group Sequential Designs
In clinical trials based on count data, the aim is to compare independent treatment groups in terms of the rate of occurrence of a particular outcome, such as number of times a subject responds to a therapy, develops a certain adverse experience, requires specialized care, or takes medication to achieve a particular response — for example, the number of migraines, seizures, recurrent infections, hospitalizations, episodes of diarrhea, and so on.
Negative binomial probability distribution can be used to model the number of times a particular outcome occurs during a clinical trial. Here, I explain this statistical methodology and its application in adaptive group sequential clinical trial designs.