SBIR Phase I: Rapid repurposing and translation of COVID-19 therapeutics using a AI-based biosimulation platform: application to ACE2 and Ca2+ multi-target therapies (COVID-19)

SBIR一期项目的更广泛影响是为COVID-19治疗提供即时的积极结果。该平台将使用人工智能（AI）开发模型，描述并最终预测特定个体对各种治疗组合的反应。这个过程可以扩展到其他疾病和条件。该SBIR一期项目将利用基于人工智能/机器学习的芯片平台，优化已批准药物的组合和剂量策略，作为针对COVID-19的重新定位的多靶点方法，以最大限度地减少特定组织中的病毒载量、感染和复制。提出的工作的一个关键目标是靶向COVID-19复制传播并有效降低净病毒载量，从而提高临床疗效和患者生存率。该项目将开发一个药物-靶标相互作用的多尺度机制模型，包括表达水平和治疗与信号通路的相互作用动力学，以防止病毒感染和炎症，从而导致广泛的组织损伤和死亡率增加。该技术将能够以高预测准确性选择个体和拟议药物组合，以优化剂量方案，从而实现最大的治疗效果。这将进一步使医生能够在短期内迅速在COVID-19患者中重新部署这些标签外疗法。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact of this SBIR Phase I project is to provide immediate positive outcomes in the COVID-19 therapeutics. The platform will use artificial intelligence (AI) to develop models describing and ultimately predicting how specific individuals respond to various therapeutic combinations. This process can be extended to other diseases and conditions. This SBIR Phase I project will utilize an artificial intelligence/machine learning-based in silico platform for optimizing combinations and dosing strategies of approved drugs as a repurposed, multi-target approach against COVID-19 to minimize the viral load, infection and replication in specific tissues. A key objective of the proposed work is to target COVID-19 replication transmission and effectively lower the net viral load, subsequently increasing clinical efficacy and patient survival. This project will develop a multiscale mechanistic model of drug-target interaction, encompassing expression levels, and interaction kinetics of therapies with signaling pathways to prevent viral infection and inflammation that can result in widespread tissue damage and increased mortality. The technology will enable, with high predictive accuracy, the selection of individuals and combinations of proposed drugs to optimize the dosage regimen that leads to a maximum therapeutic efficacy. This will further enable physicians to rapidly redeploy these therapies off-label in COVID-19 patients in the immediate term.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.