Did you miss our webinar on Single and Dual Agent Dose escalation designs earlier in the year? In this blog we have made the replay available for your review, and also take the opportunity to recap key reasons why you should consider a model based design for your dose escalation study.
Rule-based methods like 3+3 may have the unfortunate consequence of under-dosing initial recipients of treatments and overdosing others. Under-dosing occurs because the effective use of rule-based methods requires the administration of very low doses at the outset.
Informed patient care
When using rule-based methods such as 3+3, critical information gained as a trial progresses cannot inform appropriate dose-recommendations for study participants. This is because rule-based models determine levels of dosages prior to the start of a study. Bayesian modeling, by contrast, has a learn-as-you-go feature. As data accumulates, clinicians are offered suggestions on how to fine-tune recommended dosages that are then administered to patients.
Increased familiarity and uptake
There is increased familiarity with Bayesian model-based designs for Phase 1 oncology trials within the industry and among regulators.
In the past, a barrier to implementation was the lack of validated computational packages to support what are undoubtedly complex calculations. However, East 6.4's Escalate module now accomodates both single and dual agent designs including mTPI, CRM, BLRM and PIPE.This webinar, led by Pantelis Vlachos will walk through:
Simulating and comparing designs under different dose-toxicity profile assumptions
Determining the best dose for next patient cohort based on modeling the accumulating data
Communicating more effectively with clinicians to better guide dosing decisions
Improving your active agents' screening and selection process to increase clinical success rates
It begins by reviewing the underlying methodologies, then shares case studies that illustrate how to choose the optimal design parameters.