AI drug discovery Leverage Aria’s AI-driven approach and preclinical focus to position as a partner for early-stage asset generation, computational screening, and rapid lead identification in oncology, ophthalmology, immunology, and metabolic indications.

Strategic partnerships Capitalize on historical collaborations (e.g., SK Biopharmaceuticals, Adynxx) to propose co-development, research alliances, or milestone-driven deals that accelerate NSCLC and endometriosis discovery programs and diversify pipeline risk.

Markets & programs Target opportunities in hard-to-treat diseases with proof-of-concept potential, highlighting nine disease areas previously expanded; offer services or joint development for preclinical-to-clinical transition support.

Funding signals Address potential readiness for non-dilutive or early-stage funding collaboration by aligning proposals with prior SBIR-type awards and NIH/NCI interest in AI-enabled oncology and pancreatic cancer programs.

Geographic & tech fit Emphasize Palo Alto location and cloud-native tech stack (AWS, S3, data visualization) to propose remote or hybrid collaboration models, scalable data-driven discovery platforms, and secure data handling for partners globally.