As acceptance of flexible trial designs continues to advance, many sponsors are increasingly exploring alternate methods for dose escalation to support identification of a maximum tolerated dose (MTD) and recommended Phase II dose (RP2D) in open-label Early Phase or First in Human studies. Bayesian dose escalation designs have also coincided with advances in oncology therapy development, such as immunotherapies and antibody drug conjugates. These more flexible methods are viewed as potentially more appropriate than those initially designed for chemotherapy drug development.
In this webinar, we’ll discuss and cover:
- Common types of open-label adaptive dose escalation designs
- Comparisons with rule-based designs
- How to apply and use these designs in oncology therapy development
- How to determine which design is best suited for your trial
About the Presenter
Vanessa Beddo, Ph.D.,
Vice President, Biostatistical Consulting
Vanessa Beddo, Ph.D. has more than 15 years’ professional experience in clinical trial design and analysis. In her current position as VP of Biostatistical Consulting at Allucent, she is responsible for internal consultation with respect to study planning and use of statistical methods, as well as client involvement in business development and consultancy capacities. As part of her external consultancy duties, she serves as a key member of strategic drug development teams for Allucent clients, providing innovative and complex study design solutions in support of efficiently navigated regulatory paths. She is also responsible for regulatory body interactions on an ongoing basis throughout program life cycles on behalf of her clients.
Prior to this role, Dr. Beddo served in various management roles, involving oversight of statistical and programming staff and leadership with respect to departmental initiatives, processes, and training. Her experience also includes clinical development of pharmaceuticals and biologics, having served as the lead statistician on Phase I-IV clinical trials, and drug submissions leading to successful drug approvals.
Dr. Beddo holds a B.S. degree in Applied Mathematics, M.S. in Mathematics, and Ph.D. in Statistics from the University of California, Los Angeles.