Model-informed drug development in public health emergency of international concern: accelerating marketing authorization of simnotrelvir

Abstract

During a Public Health Emergency of International Concern (PHEIC), rapid drug development is critical, but traditional clinical trials are time-consuming and high-risk. This study used coronavirus disease 2019 (COVID-19) as an example to highlight the pivotal role of model-informed drug development (MIDD) in expediting the marketing authorization of simnotrelvir in China, a 3CL^pro inhibitor for COVID-19 treatment. Three simnotrelvir clinical trials (Phase Ia, Ib, II/III) were optimized using the MIDD approach. Pharmacokinetics was investigated using nonlinear mixed-effects models, exposure was calculated through Monte Carlo simulation and Bayes estimation, and exposure-efficacy/safety relationships were analyzed using linear/logistic regression models. The MIDD approach began with a translational study to predict patients' starting doses using first-in-human data, preclinical data, and pharmacodynamic surrogate marker. A dose level of 750 mg/100 mg simnotrelvir/ritonavir was recommended, using simulation results with 90.6% of participants' trough concentration exceeding EC₉₀ for anti-Omicron variant. Then, a biomarker confirmation study to investigate dose-exposure-response relationship found that 750 mg suppressed viral load more than 300 mg (-4.995 vs. -4.236 log₁₀ copies/mL, P = 0.0367) in Phase Ib. Finally, a randomized controlled trial to confirm benefit-risk ratio found that simnotrelvir/ritonavir reduced time to sustained resolution of 11 clinical syndromes by 1.5 days compared with placebo, had no serious adverse events, and had a flat exposure-response relationship with viral load reduction, time to sustained resolution, and ≥2 grade treatment-emergent adverse event rate with approved dosage. MIDD enhanced clinical trial success, optimized the benefit-risk profile, and expedited marketing authorization for new drug development in response to PHEIC.CLINICAL TRIALSThis study is registered with ClinicalTrials.gov as NCT05339646, NCT05369676, and NCT05506176.

Keywords: Omicron variant; exposure-response analysis; model-informed drug development; nonlinear mixed-effects model; public health emergency; simnotrelvir.