The safety of antivirals and neutralising monoclonal antibodies used in prehospital treatment of Covid-19

Objective This proof-of-principle pharmacovigilance study used Electronic Health Record (EHR) data to examine the safety of sotrovimab, paxlovid and molnupiravir in prehospital treatment of Covid-19. Method With NHS England approval, we conducted an observational cohort study using OpenSAFELY-TPP, a secure software-platform which executes analyses across EHRs for 24 million people in England. High-risk individuals with Covid-19 eligible for prehospital treatment were included. Adverse events (AEs) were categorised into events in the drugs Summary of Product Characteristics (SmPC), drug-reactions and immune-mediated. Cox models compared risk across treatments. A pre-pandemic record analysis was performed for comparative purposes. Results Between 2021-2023, 37,449 patients received sotrovimab, paxlovid or molnupiravir whilst 109,647 patients made up an eligible-but-untreated population. The 29-day rates of AEs were low: SmPC 0.34 per 1000 patient-years (95% CI 0.32-0.36); drug-reactions 0.01 (95% CI 0.01-0.02) and immune-mediated 0.03 (95% CI 0.03-0.04), and similar or lower than the pre-pandemic period. Compared with the eligible but untreated population, sotrovimab and paxlovid associated with a risk of SmPC AE [adjHR 1.36 (95% CI 1.15-1.62) and 1.28 (95% CI 1.05-1.55), respectively], whilst sotrovimab associated with a risk of drug-reactions [adjHR 2.95 (95% CI 1.56-5.55)] and immune-mediated events [adjHR 3.22 (95% CI 1.86-5.57)]. Conclusion Sotrovimab, paxlovid and molnupiravir demonstrate acceptable safety profiles. Although the risk of AEs was greatest with sotrovimab, event rates were lower than comparative pre-pandemic period. ### Competing Interest Statement All authors have completed the declaration of interest form and declare the following: KB has received honoraria from Galapagos and UCB. MDR has received honoraria from AbbVie, Lilly, Galapagos, Menarini and Viforpharma, advisory board fees from Biogen, and support for attending educational meetings from Lilly, Pfizer, Janssen and UCB. AM is a former employee and interim Chief Medical Officer of NHS Digital, and RCGP representative on GP Data Professional Advisory Group to NHS Digital. AMe has received consultancy for https://inductionhealthcare.com; he is a member of RCGP health informatics group and the NHS Digital GP data Professional Advisory Group that advises on access to GP Data for Pandemic Planning and Research (GDPPR), he is a senior clinical researcher at the University of Oxford in the Bennett Institute, which is funded by contracts and grants obtained from the Bennett Foundation, Wellcome Trust, NIHR Oxford Biomedical Research Centre, NIHR Applied Research Collaboration Oxford and Thames Valley, Mohn-Westlake Foundation, and NHS England. BG has received research funding from the Laura and John Arnold Foundation, NIHR, NIHR School of Primary Care Research, NHS England, NIHR Oxford Biomedical Research Centre, the Mohn-Westlake Foundation, NIHR Applied Research Collaboration Oxford and Thames Valley, the Wellcome Trust, the Good Thinking Foundation, Health Data Research UK, the Health Foundation, the World Health Organisation, UKRI MRC, Asthma UK, the British Lung Foundation, and the Longitudinal Health and Wellbeing strand of the National Core Studies programme; he is a Non-Executive Director at NHS Digital; he also receives personal income from speaking and writing for lay audiences on the misuse of science. JBG has received honoraria from Abbvie, Amgen, Celgene, Chugai, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Sobi, and UCB, and has research funding from Amgen, Aztra-Zeneca, Gilead, Janssen, Medicago, Novovax and Pfizer. ### Funding Statement KB is funded on a National Institute for Health Research (NIHR) Clinical Lectureship. MDR is funded by a National Institute for Health Research (NIHR) Doctoral Fellowship (NIHR300967). TPP and NECS CSU provided technical expertise and data infrastructure centre pro bono in the context of a national emergency. This work was supported by the Medical Research Council MR/V015737/1. BG work on better use of data in healthcare more broadly is currently funded in part by: NIHR Oxford Biomedical Research Centre, NIHR Applied Research Collaboration Oxford and Thames Valley, the Mohn-Westlake Foundation, NHS England, and the Health Foundation; all DataLab staff are supported by BGs grants on this work (205039/Z/16/Z). The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the funders. The views expressed are those of the authors and not necessarily those of the NIHR, NHS England, Public Health England or the Department of Health and Social Care. Funders had no role in the study design, collection, analysis, and interpretation of data; in the writing of the report; and in the decision, submit the article for publication. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was approved by the Health Research Authority (REC Reference 20/LO/0651) and by the The London School of Hygiene & Tropical Medicine (LSHTM) Ethics Board (Reference 21863). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes If requested, use the following: Access to the underlying identifiable and potentially re-identifiable pseudonymised electronic health record data is tightly governed by various legislative and regulatory frameworks, and restricted by best practice. The data in the NHS England OpenSAFELY COVID-19 service is drawn from General Practice data across England where TPP is the data processor. TPP developers initiate an automated process to create pseudonymised records in the core OpenSAFELY database, which are copies of key structured data tables in the identifiable records. These pseudonymised records are linked onto key external data resources that have also been pseudonymised via SHA-512 one-way hashing of NHS numbers using a shared salt. University of Oxford, Bennett Institute for Applied Data Science developers and PIs, who hold contracts with NHS England, have access to the OpenSAFELY pseudonymised data tables to develop the OpenSAFELY tools. These tools in turn enable researchers with OpenSAFELY data access agreements to write and execute code for data management and data analysis without direct access to the underlying raw pseudonymised patient data, and to review the outputs of this code. All code for the full data management pipeline from raw data to completed results for this analysis and for the OpenSAFELY platform as a whole is available for review at github.com/OpenSAFELY. The data management and analysis code for this paper was led by Katie Bechman and contributed to by James Galloway.