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Updated: Aug 18, 2025
An Automated Culture System for Use in Preclinical Testing of Host-Directed Therapies for Tuberculosis
Published on: August 16, 2021
A comparison of clinical development pathways to advance tuberculosis regimen development
V Chang1,2, P P J Phillips3, M Z Imperial4,3
1Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA. vincent.chang@ucsf.edu.
Background:
Current tuberculosis (TB) regimen development pathways are slow and in urgent need of innovation. We investigated novel phase IIc and seamless phase II/III trials utilizing multi-arm multi-stage and Bayesian response adaptive randomization trial designs to select promising combination regimens in a platform adaptive trial.
Methods:
Clinical trial simulation tools were built using predictive and validated parametric survival models of time to culture conversion (intermediate endpoint) and time to TB-related unfavorable outcome (final endpoint). This integrative clinical trial simulation tool was used to explore and optimize design parameters for aforementioned trial designs.
Results:
Both multi-arm multi-stage and Bayesian response adaptive randomization designs were able to reliably graduate desirable regimens in ≥ 95% of trial simulations and reliably stop suboptimal regimens in ≥ 90% of trial simulations. Overall, adaptive phase IIc designs reduced patient enrollment by 17% and 25% with multi-arm multi-stage and Bayesian response adaptive randomization designs respectively compared to the conventional sequential approach, while seamless designs reduced study duration by 2.6 and 3.5 years respectively (typically ≥ 8.5 years for standard sequential approach).
Conclusions:
In this study, we demonstrate that adaptive trial designs are suitable for TB regimen development, and we provide plausible design parameters for a platform adaptive trial. Ultimately trial design and specification of design parameters will depend on clinical trial objectives. To support decision-making for clinical trial designs in contemporary TB regimen development, we provide a flexible clinical trial simulation tool that can be used to explore and optimize design features and parameters.
Insights
Novel adaptive trial designs accelerate tuberculosis (TB) regimen development. These innovative approaches reduce patient enrollment and study duration compared to traditional methods, paving the way for faster TB treatment discovery.
Area of Science:
- Clinical trial design
- Tuberculosis research
- Adaptive clinical trials
Background:
- Current tuberculosis (TB) regimen development is slow and requires innovation.
- Investigated novel phase IIc and seamless phase II/III trials for TB drug development.
- Utilized multi-arm multi-stage and Bayesian response adaptive randomization designs.
Purpose of the Study:
- To explore and optimize design parameters for adaptive platform trials in TB regimen development.
- To assess the efficiency of multi-arm multi-stage and Bayesian response adaptive randomization designs.
- To provide a flexible clinical trial simulation tool for TB drug development decision-making.
Main Methods:
- Developed predictive and validated parametric survival models for time to culture conversion and TB-related unfavorable outcomes.
- Employed an integrative clinical trial simulation tool to evaluate adaptive trial designs.
- Simulated multi-arm multi-stage and Bayesian response adaptive randomization designs for phase IIc and seamless phase II/III trials.
Main Results:
- Adaptive designs reliably graduated desirable TB regimens (≥95% simulations) and stopped suboptimal ones (≥90% simulations).
- Adaptive phase IIc designs reduced patient enrollment by 17-25% compared to conventional methods.
- Seamless adaptive designs reduced study duration by 2.6-3.5 years versus the standard 8.5+ years.
Conclusions:
- Adaptive trial designs are suitable for accelerating TB regimen development.
- Provided plausible design parameters for a platform adaptive trial in TB.
- A flexible simulation tool aids in optimizing adaptive trial features for TB drug development.
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