10161399Targeted Drug Delivery in EGFR-positive Lung Cancer via Protein Nanoparticles and Artificial IntelligenceActiveFeasibility StudiesInnovate UKLung cancer remains one of the most challenging malignancies due to its complex biology and limited effective therapies. Prosemble addresses this unmet need through an innovative convergence of AI, structural biology, and nanotechnology. Central to this approach is our protein nanoparticle (PNP) technology, developed in partnership with researchers at King's College London. Unlike conventional Antibody-Drug Conjugates, our PNP-based system is highly modular, and does not require expensive and complex manufacturing processes. This allows broader tumour-targeting, fewer off-target effects, and improved scalability. Our AI-powered drug formulation algorithm also permits us to optimize the formulation of drugs being delivered by PNPs, providing enhanced efficacy and reduced off-target toxicity. The project focuses on three core objectives: 1. Protein nanoparticle engineering: We will engineer the PNP protein, to specifically target the epidemial growth factor receptor, a protein found at the surface of ~ half of lung cancers. 2. Drug cocktail optimization: We will use our dedicated algorithm, to obtain an optimal set of compounds to be delivered by the PNP, specifically for lung cancer. 3. Pre-clinical validation: Following the protein engineering and drug cocktail formulation, we will validate the efficacy of our drug-loaded PNPs in cells and in lung cancer models, compared to other treatments available. By integrating cheminformatics, structural biology, and AI, we shorten development cycles, reduce empirical testing, and support regulatory alignment. While lung cancer is the focus of this proposal, our platform is applicable to breast and gynaecological cancers. This initiative aligns with Innovate UK's goal to support transformative, high-potential healthcare innovations. Through AI and protein nanotechnology, Prosemble aims to redefine precision oncology.