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


  • 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?

  • Selecting Your Next Clinical Trial Design Using Quantitative Decision Methods

    C-Suite and R&D decision-makers are always striving to make evidence-driven decisions. Yet the rules by which evidence is evaluated can bias these decisions, even when the method of decision-making seems objective. Our Chief Scientific Officer, Dr. Yannis Jemiai, has worked extensively on how to operationalize decision theoretic tools for clinical development decision-making. Here he introduces three quantitative frameworks that life-sciences decision-makers can quickly incorporate into their selection process when selecting an optimal design for their next clinical trial.

  • Computation And Clinical Trial Design: New Directions

    Recent advances in computational tools have made the construction of high-efficiency clinical trials more rigorous than ever, with the ability to thoroughly explore a design space consisting of hundreds of thousands of possible simulations. Not only does such capability enable the optimization and de-risking of clinical trial design, it enables sponsors to ask questions they might never have had opportunity to explore before now.

  • Bayesian Statistics In Early Phase Clinical Trials

    Bayesian clinical trials are gaining prominence across the clinical development journey. Learn how to employ Bayesian statistics in early phase trials with Professor Yuan Ji of the University of Chicago, including two new innovative clinical trial designs invented by Professor Ji that are quickly gaining popularity.

  • Bayesian Clinical Trial Methods For Multiple Cohort Expansion: An Innovative Clinical Trial Design

    MUCE is a Bayesian solution for cohort expansion trials where multiple dose(s) and multiple indication(s) are tested in parallel. Such methods are particularly important for areas like oncology where several doses and several indications must be tested for successful completion of early phase trials, and optimal choice of dose and population to move on from early phase to a reasonable dosage for Phase 3.

  • Bayesian Statistics And Health Economic Outcomes: An Interview With Dr. Bart Heeg

    In this two-part blog series, we interview Bart Heeg, Vice President HEOR and Founder at Ingress Health (A Cytel company). Bart provides us insights on the trends in HEOR and explains why Bayesian methods are also important for Health Economics.

  • The Technology You Need for Bayesian Clinical Trial Design

    Gain some behind-the-scenes insights into the development of this new module and understand how your company can leverage East Alloy to conduct computationally intensive designs with ease, confidence, and speed.

  • Regulatory Approval For Bayesian Clinical Trials

    Clinical trials designed using Bayesian statistics are gaining prominence due to challenges raised by coronavirus. Former FDA Director of Biostatistics, Gregory Campbell, discusses best practices for securing regulatory approval when submitting a trial that employs Bayesian clinical trial design.

  • Need For Technology Solutions To Support Computationally Intensive Bayesian Designs

    As the industry seeks new levels of clinical trial efficiency and probability of success, more companies are looking to use advanced, innovative and computationally intensive designs like Bayesian methods. With East AlloyTM, a web-native extension of Cytel’s world-renowned East® software, users can sustainably adopt Bayesian designs to expedite clinical development and overcome uncertainty without compromising scientific rigor.

  • Re-imagining Clinical Trials: Leveraging Statistics & Cloud-Computing To Increase Development Productivity

    While regulatory and operational barriers remain a cause for concern in the sphere of research and development, there is mounting evidence that regulators will accept well  designed flexible studies that put patients first. There is even more evidence that clinical operations teams can rise to the challenge. There are a growing number of drug approvals, for example, which include adaptive designs for regulatory findings, even for pivotal studies. What Development teams now need in the age of cloud computing is a process that allows new technology to explore more designs strategically.

  • Re-Imagining Clinical Trials In The Era Of Cloud Computing: A Conversation

    The widespread use of cloud-computing has altered the clinical trial design process. Whereas three or four years ago, it would take a statistician perhaps two or three days to design five clinical trial designs, a well-resourced statistician can now simulate and model well over 100,000 designs in less than 30 minutes. How does this affect the process of designing clinical trials?

  • Advanced Design Framework Part 3 – Communication Techniques To Ensure Alignment On Data-Driven Clinical Trial Designs

    The stakes are high in pharmaceutical development, and selection of the statistical trial design often requires several layers of approval before a team has authorization to proceed. Unfortunately, incomplete information, misinformation or bias during these preliminary discussions can have long-term consequences. In this blog we explore how clear articulation of the chosen design’s benefits and drawbacks can help ensure data-driven decision-making that improves speed, success, and savings.

  • Advanced Design Framework: Part 2 – The Need For A Quantitative Evaluation Approach For Deciding

    Has your organization ever completed the execution of a long, expensive Phase 3 clinical trial only to learn that the organization is unable to commercialize the therapy? This blog shares how to effectively incorporate varied perspectives to efficiently design innovative clinical trials.

  • Advanced Design Framework: Part 1 – Methods For Thorough Exploration Of Design Space

    Time and design tool limitations have restricted the breadth of design exploration possible, so it has been necessary to carefully select the portion of the design space to examine for consideration. This blog reveals how to explore hundreds of thousands of designs available to sponsors, rapidly and in real-time, to improve the chances of identifying the design that optimizes for speed, success, and savings.

  • An Advanced Design Framework For Clinical Development In The Era Of Cloud-Computing

    While the number of trial designs and types have gently expanded, finding the optimal trial design for a specific context remains an elusive goal. Cloud-computing has altered the process of trial design, by taking familiar techniques for simulation and modeling, and generating thousands of different trial designs.

  • An Illustrative Guide To Clinical Trial Design In The Era Of Cloud-Computing

    The mere availability of complex innovative trial design methodologies cannot translate into higher success rates in regulatory submission or approval if the process that drug development teams use for statistical design remains unchanged. Advanced technology now enables leaders to actively facilitate process improvements. Cytel’s new Infographic demonstrates the combination of technology and design process advances required to unify statistics with commercial strategy.

  • Why You Should Construct Primary Endpoints Using Bayesian Methods: Lessons From COVID-19

    One of the revelations of the COVID-19 pandemic is that the flexibility and potential of Bayesian designs goes far beyond the benefits connected to informed priors. This blog summarizes a recent panel on COVID-19 drug discovery where biostatisticians and former regulators reflected on certain misconceptions about Bayesian methods.

  • The Good Data Submission Doctor: CDISC For COVID-19

    From the time the COVID-19 outbreak was declared a pandemic, the number of studies conducted around the world to either diagnose, prevent or treat the virus literally exploded. Moreover, the pandemic impacted the regular schedule of ongoing clinical trials. This blog provides a quick summary of the CDISC guidances that address ongoing studies disrupted by COVID-19 and new COVID-19 studies.

  • Three Reasons Why Oncology Trials Need Clear Estimands

    Unlike many therapeutic areas, oncology benefits from having standardized endpoints like overall survival and progression-free survival, as well as standardized methods of measuring such endpoints. While oncology might have the advantage of certain standard endpoints, there are still challenges that suggest estimands can clarify the research plan.

  • Platform Trials, Medical Supply And Cooperation For COVID-19 Vaccines

    COVID-19 has brought a number of stakeholders together to seek ingenious new methods for vaccines development. Here James Orbinski, who received the Nobel Prize as the head of Medecins Sans Frontieres joins Trevor Mundel, President of the Bill and Melinda Gates Foundation, Robin Mogg of the Bill & Melinda Gates Research Institute, and Derek Angus of REMAP-CAP, one of the largest platform trials in the search for a coronavirus vaccines, to discuss new opportunities for public-private and non-profit cooperation for vaccine development.