Modeling of randomized hepatitis C vaccine trials: Bridging the gap between controlled human infection models and real-word testing

• Published in: PNAS nexus 2025-01, Vol.4 (1), p.pgae564
• Main Authors: Mackesy-Amiti, Mary-Ellen, Gutfraind, Alexander, Tatara, Eric, Collier, Nicholson T, Cotler, Scott J, Page, Kimberly, Ozik, Jonathan, Boodram, Basmattee, Major, Marian, Dahari, Harel
• Format: Article
• Language: English
• Subjects: Biological, Health, and Medical Sciences
• ISSN: 2752-6542; 2752-6542
• DOI: 10.1093/pnasnexus/pgae564

Global elimination of chronic hepatitis C (CHC) remains difficult without an effective vaccine. Since injection drug use is the leading cause of hepatitis C virus (HCV) transmission in Western Europe and North America, people who inject drugs (PWID) are an important population for testing HCV vaccine effectiveness in randomized-clinical trials (RCTs). However, RCTs in PWID are inherently challenging. To accelerate vaccine development, controlled human infection (CHI) models have been suggested as a means to identify effective vaccines. To bridge the gap between CHI models and real-world testing, we developed an agent-based model simulating a two-dose vaccine to prevent CHC in PWID, representing 32,000 PWID in metropolitan Chicago and accounting for networks and HCV infections. We ran 500 trial simulations under 50 and 75% assumed vaccine efficacy (aVE) and sampled HCV infection status of recruited in silico PWID. The mean estimated vaccine efficacy (eVE) for 50 and 75% aVE was 48% (SD ± 12) and 72% (SD ± 11), respectively. For both conditions, the majority of trials (∼71%) resulted in eVEs within 1 SD of the mean, demonstrating a robust trial design. Trials that resulted in eVEs >1 SD from the mean (lowest eVEs of 3 and 35% for 50 and 75% aVE, respectively), were more likely to have imbalances in acute infection rates across trial arms. Modeling indicates robust trial design and high success rates of finding vaccines to be effective in real-life trials in PWID. However, with less effective vaccines (aVEs∼50%) there remains a higher risk of concluding poor vaccine efficacy due to post-randomization imbalances.