A Cambridge-based company has used artificial intelligence (AI) to identify the top candidate drugs that could be effective in treating Covid-19.
Covid-19
AI VIVO used its prediction engine to rank 90,000 candidate drug compounds in order of efficacy. The team took 15 days and produced a shortlist of 31 candidate drugs that are already approved and in use, or are in Phase II/III clinical trials.
The company has now begun talks with the UK government to initiate trials of the approved drugs, with five of those ranked already having entered clinical trials for Covid-19, including the anti-malarial drug Chloroquine, and the cancer treatment Thalidomide.
For Chloroquine, AI VIVO’s system identified how the drug’s efficacy could be improved and side effects moderated by combining the drug with other compounds to make a more effective treatment.
AI VIVO uses a phenotypic approach to drug discovery that could help scientists accelerate the time it takes to discover a drug compound and get it through clinical trials. The company started by building a phenotypic model of the impact of Covid-19 on the lungs using real samples from Covid-19 infected cells. This enabled the AI VIVO to identify unexpected compounds that may treat Covid-19 by moderating the undesirable phenotypic changes that it causes.
AI VIVO founder and CEO, Dr Peyman Gifani, said: “We are a team of molecular biologists, system pharmacologists, control engineers and machine learning experts. We believe identifying phenotypic changes in disease states is key to finding effective therapies. There is little known about the COVCovidID-19 virus itself, its effect on the host tissue and potential targets for discovery research. This limits our knowledge about the best targets for Covid-19 and means that AI VIVO's phenotypic approach could provide the most powerful, logical and rapid pathway to Covid drug discovery.”