Multi-Omics & Physics-Informed AI De Novo Drug Candidate Automated Design Core Patent Licensing Proposal

The Structural Crisis in Traditional HTS and 1st-Generation Computational Screening Bringing a novel drug to market currently demands 10–15 years and exceeds $2.6 billion, yet Phase II/III clinical failure rates remain stubbornly above 90%. Traditional High-Throughput Screening (HTS) and early machine learning models have failed to resolve fundamental thermodynamic and biological barriers. Tink Innovation respectfully submits this Technology Transfer Proposal to global pharmaceutical leaders for out-licensing, patent buyout, or collaborative development of our proprietary invention: "System and Method for Automatically Designing De Novo Drug Candidates Using Generative Artificial Intelligence Based on Multi-Omics Mutational Profiles and Physicochemical Potential Feedback." The core patent has been officially filed with the Korean Intellectual Property Office (KIPO), establishing our global priority date. We are currently preparing the PCT international patent application, offering an extraordinary ground-floor entry window for global biotech partners. KEY VALUE PROPOSITIONS Compression of Discovery Cycles: Reduces target-tolead discovery timelines from 4–6 years to just 3–6 months while slashing early R&D costs by over 80%. Elimination of Steric Clashes: Solves AI unphysical artifacts by dynamically injecting physicochemical force gradients into every reverse denoising step. Multi-Objective Co-Optimization: Simultaneously optimizes target affinity, conformational stability, and membrane/BBB permeability in a single pipeline. DEVELOPMENT STAGE & DEAL SCOPE Current Readiness: In Silico algorithm architecture,thermodynamic potential formulation, and computational PoC completed (Pre-Wet Lab Stage). Flexible Partnership Models: ① Global Patent Buyout / Full Assignment ② Field-Exclusive Licensing (e.g., Oncology, CNS) ③ Co-Development with Big Pharma Wet-Lab Validation.