Artificial intelligence tool identifies current drugs for future pandemics

Researchers have developed an artificial intelligence (AI)-based algorithmic tool that calculates how current drugs can be effectively reused to fight both COVID-19 and future pandemics.

The work, reported Monday in Heliyon, could enable faster response to public health crises, the researchers said.

SARS-CoV-2 – the virus that causes COVID-19 – has proven to be a formidable medical and social challenge over the past three years. Although vaccines and sanitation practices have reduced severity, COVID-19 continues to spread, causing disease and death. This is in part due to the virus’ ability to rapidly diversify its variants, immune response pathways, and modes of transmission. These features make traditional approaches to vaccine and drug design less effective than in previous diseases.

While the current pandemic has accelerated the need to efficiently identify potential COVID-19 drug candidates, knowledge of the host immune response to SARS-CoV-2 infection remains limited as few drugs have been approved to date.

The team explored an approach aimed at closing the preparedness gap in the event of future pandemics – that is, repurposing existing medicines in advance. Early identification and selection of the best drug candidates can potentially help delay costly and time-consuming in vitro and in vivo experiments and clinical trials and facilitate disease-specific drug development.

To achieve this, the researchers developed a systems biology tool: the phenotype simulator (Phensim). Phensim simulates tissue-specific infection of SARS-CoV-2 host cells. By leveraging available transcriptomic and proteomic databases, the tool enables modeling of a SARS-CoV-2 infection in host cells and then performs a series of computational experiments – in silico – to predict with high probability the viral effects on the host’s cellular immune response determine sensitivity and specificity, resulting in specific cellular SARS-CoV-2 signatures. It then uses these cell-specific signatures to identify the best candidate drugs for reuse.

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Using Phensim, along with expertise, the researchers identified several potential COVID-19 drugs including methylprednisolone and metformin. They also identified key SARS-CoV-2 affected cellular signaling pathways as potential drugworthy targets for COVID-19. They confirmed the validity of the tool by comparing their results to recently published in vitro studies and concluded that Phensim and other drug reuse strategies can potentially provide an effective approach for rapidly targeting potential new interventions.

Medical immunologist and lead author Naomi Maria, PhD, is part of RxCovea, a multidisciplinary group dedicated to developing innovative strategies to combat COVID-19. “There is no magic bullet to defeat the COVID-19 pandemic as it takes us on a public health roller coaster of death and devastation,” Maria noted in a statement. “However, by using this AI tool in conjunction with in vitro data and other resources, we were able to model SARS-CoV-2 infection and identify several currently available COVID-19 drugs as potentially effective in fighting the next outbreak .”