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/.
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Contact: Liz Cole
In September 2018, FDA issued a new draft Guidance for Industry on Adaptive Designs for Clinical Trials of Drugs and Biologics. This guidance replaces the previously published 2010 draft guidance.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 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.
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.
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.
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.
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.
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.
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.
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 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.
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.
In this blog, Paul Fardy, Executive Director of Data Management at Cytel shares his thoughts on how the data manager role has evolved.
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.
Trial sponsors must carefully plan their data consolidation and analysis strategies not only in preparation for CDISC-compliant submissions, but to respond to market influences and evolving clinical partnership models.
Results from a recent Deloitte survey explored if data science could be about to revolutionize the regulatory approval of new drugs.
Highlights from Adam Hamm, Director Biostatistics at Cytel, presentation on best practices and operational considerations for adaptive designs and interim analyses.
In the new era of big and complex data, conventional methods of solving search problems are sometimes ineffective.Genetic algorithms provide a highly effective solution to many such problems, and therefore their popularity and adoption are on the rise.
An important trend in clinical development involves integrating strategic pharmacometric analysis with program-level decision making to make the most use of available data. This article highlights five reasons why you should consider utilizing model-based meta-analyses (MBMAs) for your program or portfolio development.
NCAs are an integral part of establishing an early phase audit trail, it is important to use NCA software that streamlines a detailed and complex workflow.
Many drugs in the IO arena do not follow well understood traditions so the standard statistical approaches to evaluating safety and efficacy may not always be optimal or efficient. As it turns out, as is often the case with methodological research, that alternative methods are available, have been for a long time.