Large scale clinical trials: lessons from the COVID-19 pandemic.
Horsley AR., Pearmain L., Knight S., Schindler N., Wang R., Bennett M., Robey RC., Davies JC., Djukanović R., Heaney LG., Hussell T., Marciniak SJ., McGarvey LP., Porter J., Wilkinson T., Brightling C., Ho L-P.
BACKGROUND: The COVID-19 pandemic has presented substantial new challenges to clinical and research teams. Our objective was to analyse the experience of investigators and research delivery staff regarding the research response to COVID-19 in order to identify these challenges as well as solutions for future pandemic planning. METHODS: We conducted a survey of diverse research staff involved in delivery of COVID-19 clinical trials across the UK. This was delivered online across centres linked to the NIHR Respiratory Translational Research Collaboration. Responses were analysed using a formal thematic analysis approach to identify common themes and recommendations. RESULTS: 83 survey participants from ten teaching hospitals provided 922 individual question responses. Respondents were involved in a range of research delivery roles but the largest cohort (60%) was study investigators. A wide range of research experiences were captured, including early and late phase trials. Responses were coded into overarching themes. Among common observations, complex protocols without adaptation to a pandemic were noted to have hampered recruitment. Recommendations included the need to develop and test pandemic-specific protocols, and make use of innovations in information technology. Research competition needs to be avoided and drug selection processes should be explicitly transparent. CONCLUSIONS: Delivery of clinical trials, particularly earlier phase trials, in a pandemic clinical environment is highly challenging, and was reactive rather than anticipatory. Future pandemic studies should be designed and tested in advance, making use of pragmatic study designs as far as possible and planning for integration between early and later phase trials and regulatory frameworks.