Cytel Blog

In the world of clinical trials, the pace of innovation is accelerating, and approaches such as Bayesian methods are gaining traction. These methods bring flexibility and speed to clinical trial design and analysis, and with increased access to the necessary computational power, are transforming today’s clinical research ^[1]. However, the number of simulation and modeling tools necessary to perform Bayesian computations requires statisticians to be well-resourced technologically. Many biostatisticians may not readily have access to the cloud computing power to make these design approaches practical within the time constraints afforded for statistical design.

There are many dose-finding designs that have been developed over the past 30 years and several more are anticipated ^[2]. Sponsors often face the dilemma of choosing from the various design options available today. Finding the right dose in Phase 2 gives a potential new therapy its best chance to demonstrate efficacy during Phase 3, and Bayesian techniques prove to be useful for optimal dose-finding.

The convergence of several distinct trends has made wearables an increasingly attractive option for use in confirmatory clinical trials. A number of considerations arise, though, when sponsors choose this route, from how to construct clinically meaningful digital biomarkers, to how to determine the quality of the data they collect.

A recent Cytel webinar illustrated how wearables have been used in Parkinson’s disease, as well as in studies where actigraphy became a vital endpoint. Here are three considerations for utilizing wearables in clinical studies that emerged during this study.

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.

Below we identify six elements critical to integrating wearables into your clinical development program.

Bayesian models offer a flexible way of incorporating historical controls in the analysis of trial data (whether single arm and randomized), and with increased access to the necessary computational power, they are transforming today’s clinical research. In a recently published article, Cytel’s scientific community members review the main Bayesian methods used in clinical trial design. Continue reading this blog for a brief overview.

As we enter 2021 with new COVID-19 vaccines and greater optimism about the pipeline of drugs and devices positioned for approval, there remains the question of how this global pandemic has left permanent changes to clinical research and development. We know for example, that more clinical trials have become virtual and that decentralization is going to be a new challenge for clinical data management. Questions about equity and access have also arisen, with new ideas about how the pharmaceutical industry can contribute to greater equality. New quantitative models have also played an important role in expedited data analyses for prediction.

Effective use of the right outsourcing solution can enable sponsors to respond to market needs and change course where necessary, while ensuring a pool of highly qualified personnel are available to work on clinical trial projects. Whether you are a global pharmaceutical company or a virtual biotech, you deserve the dedicated and experienced A-team that can ensure that your projects are executed accurately, on-time and on-budget.

In this blog, we share a Cytel success story to explain how to create a high-quality, globally distributed biometrics team: minimizing recruitment timelines by up to 50% and expanding the team itself by 40% over a two year period

At Cytel, we have been diligently working to become an organization deeply committed to uplifting and enriching society. The core purpose of our business is to help our clients in their endeavor to improve human health. Our employees are committed to upholding the highest standards in our interactions with customers, our colleagues and the communities in which we live and work.

Each year, we have several sustainable programs planned around providing education in healthcare and statistics. However, this year with the pandemic disrupting the socio-economic circumstances of the whole world, we were quick to implement new drives to support the fight against COVID-19.

As Chief Scientific Officer, Dr. Yannis Jemiai plays a pivotal role in maintaining Cytel’s well-established reputation for statistical excellence and our track-record of bringing innovative analytic approaches to the development of medicines for human health. In this blog, we ask Yannis for his favorite Cytel events from 2020.

When designing clinical trials, biostatisticians and clinical development teams are often faced with a conundrum. Given the parameters of their clinical study, they usually begin with five or six possible design options and begin to explore the most promising ones. The likelihood is that none of these trials will be optimal designs. Rather, they meet certain criteria that are “good enough” at which point, clinical development teams might begin to lead one way or another.