The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
In recent times, Single arm trials are being increasingly used to assess new treatment interventions. They establish clinical benefit by demonstrating the effects of a new therapy or treatment, without the need to use placebo or standard of care as a control. Instead, an alternative approach known as external controls or synthetic control arms (SCA) are being used that leverages real world data and historical datasets. Technical knowledge of Bayesian methods is key to being able to design and implement such trials.
Breakthrough treatments in oncology and rare diseases are now commonly approved based on a pivotal single arm trial – however this is not always optimal. Use of single arm trials in oncology or rare diseases requires appropriate comparisons to be developed to document the benefits of the new treatment. Deriving such comparisons from real world or historical trial data is not straightforward and requires data source and methods expertise.
2020 has been an unusually difficult year as the global pandemic impacted all of our lives. This year, the Cytel blog saw a lot of activity as we tried to keep our readers abreast with the latest updates on the COVID-19 clinical trials, and covered other trending and important topics such as, the growing adoption of Synthetic Control Arms, master protocols, Head to Head Comparisons and Bayesian methods. We also collaborated with several experts from both within and outside the company to conduct several series of webinars and provided summaries through our blogs.
Continue reading to learn about the top 10 Cytel blogs that resonated most with our community in 2020.
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.
In this interview with Thomas Wilke, Principal Scientist at Ingress-Health (a Cytel company), we talk to him about his background and experience in Health Economics, understand the important considerations of real-world evidence studies and the impact of COVID-19 pandemic on the work of the health economics outcomes researchers who work at Ingress and Cytel. We also cover important HEOR topics such as its benefits for market access studies and real-world analytics (RWA) for regulatory submission.
Cytel and Ingress-Health will be contributing to a range of events at Virtual ISPOR EU 2020, on November 16th – November 19th. Our Real-World analytics teams will be collaborating to deliver a number of interactive workshops, issue panels, posters and podiums to showcase their work and share innovative insights in HEOR, evidence generation, knowledge synthesis and decision analysis.
Click below to download our full list of sessions at ISPOR EU
A credible evidence base is needed to support and document the economic value of new technologies and therapeutic approaches. Companies need careful cost-effectiveness analyses for successful reimbursement submissions. In this two-part blog series, we interview Bart Heeg, Vice President HEOR and Founder at Ingress Health (A Cytel company). Bart talks about his background in HEOR, founding Ingress Health and its recent acquisition by Cytel. He also talks about the benefits of turning to an HEOR specialist and provides a sneak peek into Cytel’s presentations at the upcoming ISPOR EU 2020 event.
The combination of greater access to electronic health records, bigger electronic claims datasets, and the need for more clinical insight in ensuring patient safety, has made observational studies an important new tool in trial design. Observational studies typically take non-randomized data from outside of a trial and use quantitative and modeling techniques to draw conclusions from big datasets. While typically used for HEOR and market access, augmenting regulatory submissions with observational studies is gaining prominence. As with all data analyses, there is an implicit rule of ‘garbage in-garbage out,’ where data that is not up to the standard required for the formation of sound scientific judgment, should not be used. Sponsors should rely on the most sophisticated tools and advanced analytics to make the most rigorous use of available data.
With the rise in digital technologies, there has been an explosion in the volume and type of data sources. We can obtain information about individual health from social media data and mobile apps, to wearable sensors and electronic health records. Corporations and governments even use insurance claims data as sources of data for analyses.
This data could yield a more robust and complete picture of diseases, the patient journey, and the effectiveness of interventions in the real world. This in turn is often used by life sciences leaders to make better drug development, reimbursement, and clinical decisions. However, apart from accessing and curating this data, we also need to harness advanced analytical techniques to generate evidence, including the sophisticated use of statistical methods. The RWE data sciences team therefore must be chosen carefully to take on the challenges of these novel uses of data.
The delivery of RWE-analyses requires more than simply statistical knowledge. The variety of RWE methodologies reflect the range of opportunities sponsors have, to cast their assets in the best light. In this blog we outline the RWE design and staffing needs of a specific kind of observational study, namely natural history studies, as regulators are increasing demand for these explanatory assessments of the biochemistry of disease progression.
Regulators in both the United States and Europe have responded positively to the use of synthetic control arms (SCA)s in clinical development. The desire to speed up and lower the cost of drug development, coupled with increased availability of rich real-world data, contributed to the increased willingness towards using SCAs as supplementary evidence to accompany regulatory submissions using single arm trial data only.
As with any sophisticated statistical method, deciding on the optimal SCA approach is a necessary condition to ensure robustness of findings. Cytel’s new audiobook "Demystifying synthetic control arms", explains the concept of synthetic controls and offers insights on some common quantitative strategies for trial design and regulatory submission. Continue reading this blog to learn more and get access to the audiobook.
Synthetic control arms (SCA) are virtual trial arms that use historical claims data and observational data to simulate the control arm of a study. When enrollment targets are low and large amounts of data already exist about the performance of a control, then in many cases using quantitative techniques to simulate a control arm of a trial will expedite timelines and serve as a more optimal use of resources.
Cytel’s new audiobook "Demystifying synthetic control arms", provides insights on synthetic controls, suitable conditions for their use, and some common quantitative strategies for trial design and regulatory submission. Click the button download the audiobook.