Sbir phase II: an advanced web portal for artificial intelligence (AI)-based comprehensive discovery of repositioning drugs

Sostos Inc., a minority-owned, woman-owned small disadvantaged business, received a $1.24M Cooperative Agreement from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) for the SBIR Phase II project, awarded July 1, 2025, with completion targeted for June 30, 2027. The award funds development of CATOS-AI (Cancer Treatment Optimization Solutions – Artificial Intelligence), an advanced web portal and clinical decision-making tool designed to advance precision oncology through artificial intelligence-based drug discovery and repositioning capabilities. The platform will leverage machine learning and multi-omics analysis to identify clinically relevant biomarkers for non-small cell lung cancer treatment, develop predictive models using de-identified genomic data to assess tumor recurrence and metastasis risks, and simulate nanoparticle-based drug delivery optimization strategies.

The deliverables under this award include a sophisticated cloud-based software platform integrating healthcare-IT systems to support personalized cancer care, accelerate pharmaceutical research and development, and improve patient survival outcomes while reducing treatment time and costs. By building upon Phase I research milestones, the project positions CATOS-AI toward commercialization and aims to enhance global competitiveness in precision oncology while benefiting millions of cancer patients through improved treatment quality and reduced healthcare burden.

Abstract

The broader impact of this small business innovation research (sbir) phase II project lies in advancing the development of catos-AI (cancer treatment optimization solutions ? Artificial intelligence) towards integration with healthcare-IT systems, paving the way for commercialization after completing key milestones in the phase i project. By leveraging a strong collaboration between academia and industry experts, this project aims to enhance the global competitiveness of this innovative technology, addressing a critical need in precision oncology. The anticipated outcomes include substantial improvements in personalized cancer care and accelerated development of new drug options, leading to better survival rates for cancer patients while reducing time and costs. Additionally, the software is expected to benefit millions of cancer patients by improving the quality of care, supporting pharmaceutical research and development, and alleviating the overall healthcare burden. This small business innovation research (sbir) phase II project aims to build a powerful artificial intelligence (AI) based clinical decision-making tool called catos-AI (cancer treatment optimization solutions ? Artificial intelligence) for personalized cancer care. Addressing the need for advanced AI solutions in precision oncology and drug repositioning, the project will utilize machine learning and multi-omics analysis to discover new drugs or repurpose existing ones for treating non-small cell lung cancer (nsclc) by identifying clinically relevant biomarkers. IT will also develop predictive models using DE-identified genomic data to assess tumor recurrence, metastasis risks, and patient responses to both standard treatments and off-label drugs. Additionally, the catos-AI will simulate nanoparticle-based drug delivery methods to optimize administration strategies for new and repurposed therapies. The project further includes the development of a cloud-based clinical software platform with robust data security, privacy protection, and tiered access for users, ensuring its usability in real-world clinical and research settings. This sbir phase II effort will advance catos-AI into a comprehensive AI-powered platform, accelerating drug discovery, improving cancer treatment outcomes, and enhancing accessibility to precision medicine solutions. 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.- subawards are not planned for this award.