SARS-CoV-2

Combination therapy
Computatational modelling allows screening of thousands of combinations of drugs to find the most effective treatments. This allows for better protection against the emergence of resistance, as well as rapid drug repurposing e.g. to combat emerging diseases such as COVID-19.
Matthew A. Clarke
Kreuzaler & Clarke et al. (2019) Kreuzaler & Clarke et al. (2019) Howell, Clarke & Reuschl et al. (2022) Howell, Clarke & Reuschl et al. (2022) Howell & Davies et al. (2023) Howell & Davies et al. (2023) Clarke, Barker & Nicholls et al. (2025)
Combination therapy
Executable Network of SARS-CoV-2-Host Interaction Predicts Drug Combination Treatments
The COVID-19 pandemic has pushed healthcare systems globally to a breaking point. The urgent need for effective and affordable COVID-19 …
Rowan Howell, Matthew A. Clarke, Ann-Kathrin Reuschl, Tianyi Chen, Sean Abbott-Imboden, Mervyn Singer, David M. Lowe, Clare L. Bennett, Benjamin Chain, Clare Jolly, Jasmin Fisher
PDF Dataset Project DOI
Executable Network of SARS-CoV-2-Host Interaction Predicts Drug Combination Treatments