In modern early-phase clinical trials, often times multiple doses of a new drug are tested in multiple indications to identify the promising doses and arms for phase II or phase III trials. Traditionally, each dose or indication is tested separately in a single trial, resulting in multiple protocols and multiple trials.
MUCE is a new Bayesian solution for cohort expansion trials or master protocol trials, in which multiple dose(s) and multiple indication(s) are expanded in parallel. It's built on Bayesian hierarchical models with multiplicity control (BHM-MC) to adaptively borrow information across patient groups to achieve three major goals:
- Increase the power (probability of selecting a promising drug for further development) for drug development
- Reduce sample size
- Control the type I error rate (probability of selecting an unpromising drug for further development)
As a comprehensive statistical solution, MUCE can be used to calculate the sample size or power, and to conduct interim and final data analyses for making critical decisions.
For sample size/power calculation, MUCE requires inputs of type I error, power/sample size, reference rate (historical control rate) and target rate for each arm. For data analysis, MUCE requires inputs of reference rate, number of responders and patients enrolled at the time of interim analysis or final analysis.
These can be applied in any clinical trials with 2 or more arms, including:
- Phase 1b trials with multiple expansion cohorts
- Phase 2 trials with multiple arms
- Master protocols including basket, umbrella, and platform trials
Compared to the Simon’s two-stage design and existing other designs for multiple expansion cohort trials (eg. Berry’s BHM , etc.), MUCE could control the family-wised type 1 error rate and maintain power with a smaller sample size.
MUCE Consulting Service
We offer MUCE consulting servcie that spans the entire trial process
Some of recent examples of MUCE consulting services
- In 2018, MUCE is applied to a Chinese Phase 1a-1b Seamless trial in which up to three doses and four indications will be expanded. This means the trial can expand as many as 12 arms in parallel. The IND application has been approved and trial started with a first patient enrolled. MUCE turns out to be the only design that can manage 12 arms with limited sample size.
- In 2019, MUCE is applied to a US Phase 1a/1b trial to help design the multiple expansion cohorts. The trial has three cohorts to expand after the dose escalation stage, to determine if the RP2D can exhibit anti-tumor activities in three different indications. The trial is submitted for IND approval in US.
- In 2019, MUCE is applied to a three-arm phase II trial in which each arm investigates the efficacy of the combination of two immune therapies in three lines of cancer treatments. The sample size of trial is cut into half compared to Simon’s two-stage design.
- In 2019, MUCE is applied to a two-arm phase 1b/II trial, in which MUCE is used to guide a two-arm expansion cohort design and go/no-go decision for each arm. MUCE is compared to the Bayesian method in Berry et al. (2013) and shows much improved control of type I error rate.