2021-08-02-世界卫生组织-Report_of_the_technical_consultation_on_Innovative_Clinical_Trial_Designs_for_Development_of_New_TB_Treatments_87页_763kb

Summary of Technical Consultation on Innovative Clinical Trial Designs for Development of New TB Treatments

Translational PK-PD Modeling and Data Integration

• Translational Modeling: Experts agreed that quantitative translational modeling can bridge preclinical and clinical development, predict regimen outcomes, and reduce risks. Key applications include early bactericidal activity (EBA) prediction, long-term combination outcome prediction, and optimal regimen prioritization.
• Data Integration: The lack of data integration, not data scarcity, hinders translation between preclinical and clinical settings. Collaboration between preclinical scientists, trialists, and modelers is critical to address knowledge gaps in acquired resistance, bacterial persisters, and host-pathogen interactions.
• Validation: Translational platforms require rigorous testing and validation through iterative feedback processes to build confidence in clinical predictions.

Biomarkers for Accelerating Regulatory Decisions

• Advanced Biomarkers: Promising biomarkers (e.g., LAM, MBLA, RS ratio, PET-CT) provide quantitative data to predict treatment responses and replace traditional culture-based endpoints. These offer faster insights into bacterial burden and sterilizing activity.
• Biomarker Integration: Biomarkers should be incorporated into Phase 2B/C trials to correlate with early endpoints (culture conversion, time-to-conversion) and primary clinical endpoints (non-relapsing cure). Standardized approaches and specimen quality are needed for regulatory acceptance.
• Challenges: Observational and real-world data face issues with bias, confounding, and regulatory reluctance as primary evidence. Collaboration is needed to address these gaps and align data generation with policy needs.

Adaptive and Seamless Trial Designs

• Accelerated Pathways: Fewer trial stages (e.g., two- or three-trial pathways) can streamline development, but require careful balancing of risk de-risking and accelerated decision-making. The tri-lethality challenge (dose, combination, duration) necessitates staged exploration.
• Adaptive Designs: Bayesian-based adaptive trials, duration randomization, and multi-arm multi-stage (MAMS) designs show potential for efficient regimen selection and duration optimization. These approaches need refinement for regulatory confidence and broader applicability.
• Innovation Trade-offs: Shortened pathways may overburden trials with multiple objectives. Balancing innovative approaches with comprehensive data on safety, efficacy, and real-world applicability remains a key challenge.

Real-World Evidence and Policy Development

• Observational Data Role: Real-world evidence (RWE) can address feasibility, acceptability, and programmatic use beyond randomized trials. However, RWE faces quality, validity, and bias challenges that limit its regulatory use.
• Post-Approval Engagement: Stakeholders called for parallel collection of real-world data (registry studies, post-marketing commitments) to inform ongoing benefit-risk assessments and policy updates.
• Political and Ethical Considerations: Up-to-date evidence generation requires sustained collaboration between regulators, policymakers, and developers. Community engagement helps ensure equitable access and uptake of new regimens.

Special Populations and Safety Concerns

• Vulnerable Populations: Pregnant/lactating women, children, and HIV-coinfected individuals face inclusion barriers in clinical trials. Strategies include staggered enrollment, adaptive eligibility criteria, and child-friendly formulations.
• Safety Considerations: Adequate safety databases are essential for regulatory approvals. Real-world surveillance is needed to monitor rare events and long-term toxicity, particularly with new drugs like bedaquiline and delamanid.
• Exclusion Challenges: Routine trial exclusions of certain populations may delay evidence generation. Integrated approaches that balance scientific rigor with inclusion are required to ensure equitable benefit-risk assessments.

Overall Impact of COVID-19

• Accelerated Collaboration: The pandemic highlighted the potential to rapidly deploy clinical trials and foster cross-sectoral innovation. Lessons include streamlined regulatory engagement and adaptive platform trial designs.
• Ongoing Challenges: Future COVID-related disruptions may affect TB drug development timelines. However, the scientific progress and collaborative momentum offer opportunities to advance TB treatment innovations.

This summary highlights key consensus points, proposes collaborative actions, and identifies areas needing further research to accelerate the development of new, effective, and accessible TB treatments.