Cytel is the largest provider of statistical software and advanced analytics for clinical trial design and execution. For over thirty years, Cytel’s scientific rigor and operational excellence have enabled biotech and pharmaceutical companies to navigate uncertainty, prove value and make confident, evidence-based decisions. Our experts deliver industry-leading software, data-driven analytics, real-world evidence and strategic consulting. Headquartered in Waltham, Massachusetts, Cytel has more than 1,400 employees across North America, Europe and Asia. For more information about Cytel, please visit us at www.cytel.com. You also can follow us on LinkedIn and Twitter and like us on Facebook.


Cytel brings its expertise in adaptive designs to the design and implementation of the industry’s most innovative clinical trials. These highly flexible trials raise peculiar challenges for enrollment, data collection and regulatory submission. Why not have the industry leaders in adaptive design working on your adaptive trials?

Cytel’s dedicated team of professionals is here to help you address an array of challenges when conducting drug development. Whether you face a complex statistical issue or the need for knowledgeable collaborators to handle biometrics and trial implementation, Cytel has skilled professionals available when you need them.

Cytel data scientists apply advanced statistical techniques including predictive modeling of biological processes and drug interactions to unlock the potential of big data. Our team supports biomarker discovery and diagnostic test development based on biomedical signals and images, and real world evidence analysis.

Exposure (and Dose) Response Analyses, including pharmacokinetic and pharmacodynamics analyses, guide critical decisions in drug development. Cytel’s expert Quantitative Pharmacology and Pharmacometrics group delivers high quality solutions to help our customers get those decisions right.

Cytel has a strong track record in providing CDISC solutions and we are a CDISC Registered Solutions Provider. We have converted more than 150 studies as part of NDA submissions, all of which have been accepted by the FDA. The Clinical Data Interchange Standards Consortium (CDISC) devised the SDTM and ADaM models to standardize data structures for submission of raw and analysis data from clinical trials. These standard formats are increasingly expected by regulatory authorities including the FDA.

Extensive time and energy is often spent designing feasible clinical studies. East's broad range of statistical tools and expert simulations provides an invaluable resource for the rapid construction of trial designs. Illuminating graphs and charts allow for accessible comparison, while a user-friendly interface encourages exploration and experiment.

EnForeSys is a user-friendly decision tool that leverages simulation methods to predict recruitment milestones with high accuracy. Armed with a reliable probability of success, you can rest assured that your trial will reach its targeted enrollment on time and on budget.

We believe that expert statistical input has the power to shape the future of clinical development: de-risking portfolios, accelerating timelines, and increasing the probability of success.



1050 Winter Street

Waltham, MA 02451


Contact: Rebecca Grimm


  • 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.

  • 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.

  • 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?

  • 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.

  • 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.

  • 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.

  • 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?

  • 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?