Mesh : Humans SARS-CoV-2 / drug effects Ritonavir / therapeutic use administration & dosage COVID-19 Drug Treatment COVID-19 / prevention & control virology immunology Viral Load / drug effects Antiviral Agents / administration & dosage therapeutic use pharmacology Indazoles / pharmacology Models, Theoretical Post-Exposure Prophylaxis / methods Lactams Leucine Nitriles Proline

来  源:   DOI:10.1038/s41467-024-49458-9   PDF(Pubmed)

Abstract:
In a pivotal trial (EPIC-HR), a 5-day course of oral ritonavir-boosted nirmatrelvir, given early during symptomatic SARS-CoV-2 infection (within three days of symptoms onset), decreased hospitalization and death by 89.1% and nasal viral load by 0.87 log relative to placebo in high-risk individuals. Yet, nirmatrelvir/ritonavir failed as post-exposure prophylaxis in a trial, and frequent viral rebound has been observed in subsequent cohorts. We develop a mathematical model capturing viral-immune dynamics and nirmatrelvir pharmacokinetics that recapitulates viral loads from this and another clinical trial (PLATCOV). Our results suggest that nirmatrelvir\'s in vivo potency is significantly lower than in vitro assays predict. According to our model, a maximally potent agent would reduce the viral load by approximately 3.5 logs relative to placebo at 5 days. The model identifies that earlier initiation and shorter treatment duration are key predictors of post-treatment rebound. Extension of treatment to 10 days for Omicron variant infection in vaccinated individuals, rather than increasing dose or dosing frequency, is predicted to lower the incidence of viral rebound significantly.
摘要:
在一项关键试验(EPIC-HR)中,为期5天的口服利托那韦增强尼马特雷韦疗程,在有症状的SARS-CoV-2感染期间(症状发作后三天内)早期给予,在高危人群中,相对于安慰剂,住院率和死亡率降低89.1%,鼻腔病毒载量降低0.87log.然而,nirmatrelvir/ritonavir在试验中作为暴露后预防失败,并且在随后的队列中观察到频繁的病毒反弹。我们开发了一个数学模型,捕获病毒免疫动力学和nirmatrelvir药代动力学,从这个和另一个临床试验(PLATCOV)中概括病毒载量。我们的结果表明,nirmatrelvir的体内效力明显低于体外试验预测。根据我们的模型,在第5天时,相对于安慰剂,最大有效的药物将使病毒载量减少约3.5log.该模型确定,较早的开始和较短的治疗持续时间是治疗后反弹的关键预测因素。在接种疫苗的个体中,Omicron变异型感染的治疗延长至10天,而不是增加剂量或给药频率,预计将显著降低病毒反弹的发生率。
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