Evidence map›Paper›PMID 39263567›Full record

ArticleFrontiers in pharmacology2024

Model informed dose regimen optimizing in development of leritrelvir for the treatment of mild or moderate COVID-19.

Kun Wang, Haijun Li, Youyun Li, Fengyan Xu, Zhongyi Sun, Yuting Yang, Jufang Huang, Xiaoxin Chen

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Trial
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Kun Wang *Shanghai Qiangshi Information Technology Co., Ltd., Shanghai, China.
Haijun Li *Guangdong Raynovent Biotech Co., Ltd., Guangzhou, China.
Youyun LiGuangdong Raynovent Biotech Co., Ltd., Guangzhou, China.
Fengyan XuShanghai Qiangshi Information Technology Co., Ltd., Shanghai, China.
Zhongyi SunShanghai Qiangshi Information Technology Co., Ltd., Shanghai, China.
Yuting YangShanghai Qiangshi Information Technology Co., Ltd., Shanghai, China.
Jufang HuangDepartment of Anatomy and Neurobiology, School of Basic Medical Science, Central South University, Changsha, China.
Xiaoxin ChenGuangdong Raynovent Biotech Co., Ltd., Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Leritrelvir (RAY1216) acts as a main protease inhibitor that hinders the cleavage of viral precursor proteins, thereby inhibiting virus replication of SARS-CoV-2). This antiviral mechanism has shown significant efficacy against the novel coronavirus. Preclinical studies have demonstrated the potent antiviral activity and favorable safety profile of this compound. This study aims to develop a pharmacokinetic model for leritrelvir, with and without ritonavir as a pharmacokinetic enhancer and to evaluate the necessity of co-administration with ritonavir and to investigate different dosage regimens. Method: The model establishment was based on plasma concentration data from a phase I trial involving 72 subjects in single-ascending dose (SAD), multiple-ascending dose (MAD), and a food effect cohort. Analysis was conducted using a nonlinear mixed-effects model, and clinical trial simulations were carried out. Results: The findings of this study demonstrate a favorable safety profile for leritrelvir. With simulation suggests that a 400 mg thrice-daily (TID) regimen may be optimal to maintain the trough concentrations (C Discussion: This findings supported by subsequent phase II and phase III trials validated the appropriateness of a 400 mg TID regimen for the administration of leritrelvir.

Indexed as

3CL proteaseCOVID-19leritrelvirpharmacokincticsRAY1216

Identifiers

PMID39263567
PMCPMC11387175

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.