The emergence of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) led to multiple drug repurposing clinical trials that have yielded largely uncertain outcomes. To overcome this challenge, we used IDentif.AI, a platform that pairs experimental validation with artificial intelligence (AI) and digital drug development to rapidly pinpoint unpredictable drug interactions and optimize infectious disease combination therapy design with clinically relevant dosages. IDentif.AI was paired with a 12‐drug candidate therapy set representing over 530,000 drug combinations against the SARS‐CoV‐2 live virus collected from a patient sample. IDentif.AI pinpointed the optimal combination as remdesivir, ritonavir, and lopinavir, which was experimentally validated to mediate a 6.5‐fold enhanced efficacy over remdesivir alone. Additionally, it showed hydroxychloroquine and azithromycin to be relatively ineffective. The study was completed within 2 weeks, with a three‐order of magnitude reduction in the number of tests needed. IDentif.AI independently mirrored clinical trial outcomes to date without any data from these trials. The robustness of this digital drug development approach paired with in vitro experimentation and AI‐driven optimization suggests that IDentif.AI may be clinically actionable toward current and future outbreaks.

中文翻译：

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IDentif.AI：通过数字药物开发快速优化针对严重急性呼吸综合征冠状病毒2（SARS-Cov-2）的联合治疗设计

严重的急性呼吸系统综合症冠状病毒2（SARS-CoV-2）的出现导致了针对多种药物的具有临床意义的临床试验，这些试验产生的结果很大程度上不确定。为了克服这一挑战，我们使用了IDentif.AI，该平台将实验验证与人工智能（AI）和数字药物开发相结合，以快速查明不可预测的药物相互作用，并优化具有临床相关剂量的传染病联合治疗设计。IDentif.AI与12种药物候选疗法配对，代表针对从患者样品中收集的SARS-CoV-2活病毒的530,000多种药物组合。IDentif.AI指出最佳组合为瑞德昔韦，利托那韦和洛匹那韦，经实验验证，与单独使用瑞德昔韦相比，该药介导的疗效提高了6.5倍。另外，它表明羟氯喹和阿奇霉素相对无效。该研究在2周内完成，所需测试数量减少了三个数量级。迄今为止，IDentif.AI均独立反映了临床试验结果，而这些试验没有任何数据。这种数字药物开发方法的强大功能与体外实验和AI驱动的优化相结合，表明IDentif.AI在临床上可应对当前和未来的暴发。