Optimizing drug combinations to resurrect the potency of failed antibody therapy against emerging COVID-19 variants using IDentif.AI.

Introduction: Since the outbreak of the COVID-19 pandemic, extensive efforts including vaccine and drug development have been accentuated to address the emergence of SARS-CoV-2 variants. The rising variants and subvariants made early discoveries in effective treatment strategies less relevant and potent. For instance, multiple therapeutics like Evusheld are no longer effective against current variants and therefore have their emergency use authorizations (EUA), a regulatory mechanism allowing emergency use of medical products, revoked until further notice. Similarly, sotrovimab (STV), a human neutralizing monoclonal antibody (MAB), received EUA in May 2021 and was later granted authorization for COVID-19 treatment in Singapore. However, mutations presented in XBB, a subvariant of Omicron, substantially reduced the potency of STV at the currently approved dose. Methods: To retain STV as a part of the treatment strategy for COVID-19 infected patients, it is important to carefully design and prioritize drugs that may further enhance the potency of STV when paired in combinations. In this study, IDentif.AI, an artificial intelligence (AI)-derived drug combination optimization platform, was harnessed to rapidly pinpoint STV-based combinations that may substantially improve the efficacy and potency of STV against XBB, which was predominantly spreading worldwide in 2023. Results: IDentif.AI-pinpointed STV/EIDD-1931 and STV/GS-441524 combinations were able to interact synergistically to enhance efficacy against XBB and importantly, substantially reduce STV's in vitro EC50 (half maximal effective concentration) by up to 7-fold. Discussion: This optimization platform represents a strategic approach to rapidly repurpose existing or previously failed therapeutics and subsequently restore their efficacy against a disease indication by pairing them with the correct drugs in combinations.