The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
JSM 2018, ASA’s annual gathering of over 6500 attendees attracted statisticians and data scientists to the beautiful city of Vancouver on July 28 – August 2. The conference offers a one of a kind opportunity for statisticians to exchange ideas and explore opportunities for collaboration. In this blog, we will provide access to our team's slide decks from the event, as well as some of their key takeaways from sessions that they attended.
A number of the Cytel team were in Amsterdam, 3rd- 6th June 2018 for the PSI Conference. This year’s conference was held at the magnificent Beurs Van Berlage, a venue full of history and interesting architectural features. We took the opportunity to give delegates a first look at OK GO, our new clinical trial Go/No-Go decision-making software in this magnificent setting.
In this blog, we'll summarize some of the particular highlights from the sessions that our team members attended.
As part of Cytel's new Trial Innovations Webinar Series, Pat Mitchell, Statistical Science Director at AstraZeneca presented the October webinar "Formal Go/No-Go decisions are a key component of risk management in early clinical development."
The ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop is sponsored by the ASA Biopharmaceutical Section in cooperation with the FDA Statistical Association. Each year 800 statistical practitioners come together to absorb new information on statistical practices in all areas regulated by the FDA.
Cytel was honored to be involved in the workshop program, and our subject matter experts added value to the conference by sharing their academic and regulatory experiences.
Don’t worry if you missed the event!
In this blog, we share the full slide set slide from Cytel contributions at the ASA Biopharmaceutical Section Regulatory Industry Statistics Workshop.
A recent paper The case for Bayesian methods in benefit-risk assessment: Overview and future directions (1) co-authored by Cytel Senior Vice President Consulting Yannis Jemiai and published in Therapeutic Innovation and Regulatory Science, tackles the critical issue of benefit risk assessment, and the part Bayesian approaches can play in resolving their challenges.
There is certainly an industry- wide need for more transparent, targeted and robust benefit risk assessments. In this blog we talk with Yannis about the article and why the Bayesian framework is particularly well suited to these efforts.
Robust go/no-go (GNG) decision-making is essential for effectively managing risk across a clinical portfolio. In early phase development, it is particularly important to have the correct tools in place to terminate ineffective compounds quickly, while accelerating promising ones through the process.
We continue our case study series with this example of a Phase 3 design that uses Bayesian decision making combined with frequentist final analysis.
Clinical Development Background
Our biopharmaceutical client’s lead drug candidate is a late clinical-stage cancer immunotherapy for treatment of a rare oncology indication. Clinical development of therapies in this indication faces inherent challenges of patient recruitment and scarcity of data.
The sponsor had previously conducted a randomized, double-blind, placebo-controlled Phase 2 study. Moving into a confirmatory clinical trial setting, they came to Cytel for support with a trial design to address their key questions:
FDA draft guidance on “Co development of two or more unmarketed investigational drugs for use in combination” notes that:
“Combination therapy is an important treatment modality in many disease settings, including cancer, cardio-vascular disease, and infectious diseases. Recent scientific advances have increased our understanding of the pathophysiological processes that underlie these and other complex diseases. This increased understanding has provided further impetus for new therapeutic approaches using combinations of drugs directed at multiple therapeutic targets to improve treatment response or minimize development of resistance.” In this setting, it’s important to be able to design dose escalation studies which can identify the synergistic activity of compounds, and less toxic combinations.