FEATURED ARTICLES

• De-Risking The Unknown: Optimizing Statistical Design For Clinical Strategy

  What if Governance Board meetings began with hundreds of potential clinical trial designs presented to decision-makers in an easy to visualize way? In this webinar Dr. Yannis Jemiai, Cytel’s Chief Scientific Officer, will answer that question along with a few other and share a solution for achieving clinical trial success.

• Wearables-Based Clinical Trials: The Biostats And Clinical Overview Of A Growing Clinical Development Strategy

  The past two years have witnessed a heightened interest in the use of wearables in clinical development. The unexpected changes to the industry ushered in by the COVID-19 pandemic has highlighted the need for remote monitoring and patient-centric outcomes and accelerated the changes in the trials conduct. In this blog we identify six elements critical to integrating wearables into your clinical development program.

• New Dimensions Of Clinical Trial Optimization

  The complexity of clinical trial optimization comes from the need to align priorities on the one hand, and to understand opportunities on the other. We know that at a very general level, clinical operations specialists benefit from simplicity in clinical trial design, and that commercial teams prefer shorter clinical trials to longer ones. We also know that the statistical design of a clinical trial can influence both simplicity and duration. Yet how many sponsors have their clinical operations and commercial teams, sit with their R&D teams to review various statistically nuanced design options?

• Computing & Statistics: Are You Ready For The Industry Transformation?

  Over the past ten years High-Performance Computing (HPC) has transformed medical research through advances in genomics, computational biology, cryo-electron microscopy, and numerous others forms of scanning, sequencing, and simulation. Yet there have been few reports of how computational power can affect the design and operations of clinical trials. Learn how revolutions in computing are now set to transform clinical studies, and how sponsors can remain competitive in this modern industry terrain by learning to harness the power of new technology.

• Aligning Commercial Strategy And Statistical Design

  Da Volterra wanted to maximize the power of their clinical trial for scenarios with a smaller treatment effect, and were contemplating a Sample Size Re-estimation design. Unfortunately, with a strict enrollment limit of 1,100 patients, this particular study design produced only marginal gains in power over the fixed sample size design. By working with Cytel’s statistical consultants and their powerful new software platform Solara, Da Volterra was able to maximize the chance of a successful trial result with precise insight into the tradeoffs in speed, savings and success with a simple, low-risk trial design identified within hours.

• Hybrid Bayesian And Frequentist Clinical Trial Designs

  Most people know that clinical drug discovery is usually conducted using either Frequentist or Bayesian methods. These two statistical paradigms have enjoyed a degree of competition historically, with some statisticians tauting the statistical rigor of Frequentist designs and others the intuitiveness and flexibility of Bayesian clinical trials. Recently, though, a number of hybrid methods have arisen, that leverage the benefits of both paradigms for singularly powerful clinical trials. There are benefits of these combined methods.

• Comparisons of Bayesian And Traditional Phase 2 Methods For Oncology

  The rise of Bayesian methods has meant that predictive power can be used to assess efficacy during these single arm Phase 2 studies, but how do they differ from traditional designs and when should they be used?

• Simulation Based Clinical Trial Optimization

  The past decade has witnessed the rise of simulations-based clinical trial optimization in a manner unimaginable to most only a few years ago. Such optimization has become an integral aspect of strategic clinical trial design. Nowadays, technology can produce innumerable simulations within a short space of time. Why is it then, that some trial sponsors still struggle to make use of such simulations?