Now more than ever, the clinical development path is full of make-or-break data complexities and analytical challenges. As a pioneer in evidence generation, with deep expertise in advanced analytical solutions, we are uniquely equipped to unlock the value from increasingly complex data. Life Sciences companies count on Cytel to deliver exceptional insight, minimize trial risk and accelerate the development of promising new medicines that improve human life. Cytel provides software solutions for the design and analysis of clinical trials, including industry standards East®, StatXact® and LogXact®, as well as data-focused clinical research services. With operations across North America, Europe, and India, Cytel employs 900 professionals, with strong talent in biostatistics, programming, and data management. For more information about Cytel, visit http://www.cytel.com/.


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.



675 Massachusetts Ave # 3

Cambridge, MA 02139


Phone: 617-661-2011

Contact: Liz Cole


  • Are You Harnessing The Power Of Your Clinical Data?

    In clinical development, we all strive to deliver therapies that improve patients’ lives. However, the clinical data we generate can profoundly impact our success in achieving this goal. However, generating high-quality clinical data is far from straightforward, especially if you don’t have the appropriate in-house expertise. In this eBook, we discuss what is involved in planning a clinical data strategy for the entire duration of a development program, as well as for Phase 1 and Phase 2 trials specifically. We also outline some best practices for planning your data strategy, including tips from Cytel experts working in our Strategic Consulting, Clinical Research Services and Data Management teams.

  • The Good Data Submission Doctor: Should I Stay Or Should I Go?

    A recurring question we get from clients is whether it is worth adopting data standards such as CDISC in the early phase of their drug development, and if it is worth spending more to produce SDTM and ADaM packages at an early stage. Learn more about why this could be a good decision for your company and steps you can take towards adopting them.

  • Adaptive Design And Health Economic Analysis: Interview With Laura Flight

    In this Q&A with Laura Flight, National Institute for Health Research (NIHR) Doctoral Fellow we take a deep dive into the objectives of her recent paper "A Review of Clinical Trials With an Adaptive Design and Health Economic Analysis" Learn more about the next steps for promoting better understanding in this area.

  • Advancing Oncology Development With A Synthetic Control Arm Trial

    A specialized biopharmaceutical company had a breakthrough therapy that had the potential to be first-in-class for a rare and aggressive hematological cancer and had shown great potential in earlier clinical trial. In many breakthrough treatment areas, where the patient population is small, or there is overwhelming evidence of efficacy at Phase 2, it has become common for drugs to be approved based on a pivotal single arm trial – however, this is not always optimal. Read how synthetic control offers a practical, effective way to leverage real-world evidence and has been applied in regulatory approvals.

  • Handling The Specialized Data Requirements In Oncology Clinical Trials

    The right design and the right data ultimately leads to the right decisions, so obtaining fit-for-purpose data, collected based on what your protocol is looking for is vital. However, there are several data pressure points facing oncology drug developers that need specialized expertise and processes to handle. In this blog, we run through some key aspects to consider to smooth your data collection and analysis.

  • Predictive Biomarker Signature Characterization

    A client was developing a new drug for complex neurodegenerative disease in pre-clinical development. The drug may be only effective for a particular subgroup of patients. They needed to generate a hypothesis on the molecular pathway and the targeted drug activity and identify a biomarker signature defining potential response to the new drug. Read how Cytel’s analysis produced a biomarker signature that was provided to the client for in-vivo validation.

  • Innovative Data Science And Real-World Analytics Approaches In Practice

    With the rise in digital technologies, there has been an explosion in volume and type of data sources we can obtain. However, new data sources bring inherent challenges to be overcome including lack of standardization, missing data, and variation in quality. Read how Cytel's data science and real-world evidence groups have helped clients apply advanced analytical techniques to large, complex historical or real-world data sets to improve their decision-making, accelerate development pathways, and enhance their probability of success.

  • 2018 vs. 2010 FDA Draft Guidance For Industry On Adaptive Designs For Clinical Trials Of Drugs and Biologics

    In September 2018, FDA issued a new draft Guidance for Industry on Adaptive Designs for Clinical Trials of Drugs and Biologics. This guidance replaces the previously published 2010 draft guidance. Here, we summarize the differences between the two documents and highlight any significant new elements introduced in the most recent material. Of note, the 2018 guidance is more compact and streamlined than its 2010 predecessor, also evident by a fewer number of total pages (36 vs. 50 in the 2010 version).

  • Cytel And Axio Join Forces To Create An Industry Leader In Analytical Solutions For Drug Development

    Cytel Inc., the leading global provider of innovative analytical software and services to the life sciences industry, and Axio Research, a premier provider of biostatistics to pharmaceutical, biotechnology and medical device companies, today announced that they have joined forces to create the largest global biometrics organization focused on delivering advanced analytical solutions for the life sciences industry.

  • Opening The Black Box: Moving To Explainable AI

    For the biopharma industries specifically, AI represents an opportunity to avert the R&D productivity crisis with paradigm-shifting applications such as in-silico drug design, prediction of trial risks and big data analytics. However, with every opportunity, there are risks and challenges, and this blog discusses how pharma needs to address the opacity of AI to ensure trust and credibility with all stakeholders.

  • Assuring Outsourcing Obligations With Specialist Data Management Oversight

    This blog discusses how specialist CROs can add value and streamline processes by providing oversight of data management services delivered by another CRO. This model helps to fulfill essential regulatory obligations for biopharma companies who may lack their own internal oversight resources.

  • Applying Biomarker Driven Strategies In Drug Development

    Determining appropriate stratifications and relevant clinical endpoints for specific sub-populations can be challenging. Therefore, it is necessary for development strategies to incorporate explorations and determinations of suitable biomarkers early in the development of a new therapy.

  • Ensuring Robust ePRO Implementation: Factors For Success

    In this blog, Jonathan Pritchard, Director Business Development at Cytel, draws on his experience in commercial, clinical and technology roles within the biopharmaceutical industry and shares his insights on the primary considerations for sponsors when implementing an ePRO solution.

  • Could Adaptive Designs Be The Answer To Oncology Clinical Development Success?

    Across all therapeutic areas, clinical development faces well-documented, critical challenges that impact the pharmaceutical industry's ability to bring new medicines to patients – but in the oncology space, these issues are particularly acute. Read how adaptive trial designs can help address the challenges encountered in anti-cancer clinical development today by saving time, resources and improving the odds of success.

  • The Model-Based Approach: A Better Way To Forecast Enrollment

    Compared to conventional approaches, a model-based approach to enrollment forecasting provides a more realistic assessment of the possible risks and outcomes for any given scenario, by accounting for the nonlinearity and randomness of real-life enrollment processes. In addition, a model-based approach offers many more advantages other than more realistic expectations.

  • Creating A Common Language: Forging Statistical And Clinical Collaborations

    This article will provide helpful pointers from  Paul Terrill, Director of Strategic Consulting at Cytel to ensure smooth communication between statistical and clinical stakeholders.

  • Data Management Fundamentals For Your Next Clinical Trial

    Data is the most crucial asset in any clinical trial and is used to ultimately drive the decision-making process related to the development candidate. Therefore, for any sponsor, paying close attention to the data management aspects of clinical operations should be paramount. The principles of data management are simple and well-founded. However, the application of these principles needs careful consideration, depending on various scenarios and the size of the organization. When implementing data management for your trial, it is critical to plan ahead and fully understand all the steps and activities involved.

  • What Makes A Good Data Manager? Infographic

    Data managers need to equip themselves with skills to make sense of an ever-expanding world, while maintaining adherence to core principles of safety and efficacy.

  • What Makes A Good Data Manager?

    The shift from on-site monitoring to remote monitoring has given the data manager an increased responsibility for looking at the data in real time and to allow decisions to be made on a site and patient level on an ongoing basis. This article discusses what makes a great data manager in today’s drug development environment.

  • In The Midst Of This: The Data Management Perspective On The Interim Analysis

    Patti Arsenault, Cytel's Global Head of Data Management, shares her thoughts on the three core elements important for the success from the data management standpoint - effective timeline management, thoughtful database design, and a proactive approach to data cleaning.