Model-informed drug development in public health emergency of international concern: accelerating marketing authorization of simnotrelvir
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<sup>pro</sup> 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 EC<sub>90</sub> 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 log<sub>10</sub> copies/mL, <i>P</i> = 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.
Authors
- Guo‐Xiang Hao (ORCID: https://orcid.org/0000-0003-4847-091X)
- Panpan Ye (ORCID: https://orcid.org/0000-0001-8165-023X)
- Wei Zhang (ORCID: https://orcid.org/0000-0001-9004-1161)
- Wei Zhao (ORCID: https://orcid.org/0000-0002-1830-338X)
- Lian Liu (ORCID: https://orcid.org/0000-0001-5428-2937)
- Yang Yang (ORCID: https://orcid.org/0000-0002-1163-2359)
- Jia Chen (ORCID: https://orcid.org/0000-0001-6597-8577)
- Shunwei Zhu
- Xinfang Zhang (ORCID: https://orcid.org/0000-0002-1912-5060)
- Linlin Song
- Xin‐Mei Yang
- Shansen Xu (ORCID: https://orcid.org/0000-0002-2624-9192)
- Yi Zheng (ORCID: https://orcid.org/0000-0002-7197-9434)
- Honglin Hu (ORCID: https://orcid.org/0000-0003-4334-1270)
- Zi-Jia Guo
- Shu‐Meng Fu
- Bo-Hao Tang
- Bu‐Fan Yao
Institutions
- Shandong University (CN)
- Simcere Pharmaceutical (China) (CN)
- Shandong Provincial QianFoShan Hospital (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Antimicrobial Agents and Chemotherapy
- Published
- 2025-09-18
- DOI
- https://doi.org/10.1128/aac.00614-25
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00