Next Generation Dual Targeting ADCs for SCLC Empowered by Generative AI.

Small cell lung cancer (SCLC) is a rare, aggressive, and hard-to-treat cancer with limited therapeutic options, often marked by tumor heterogeneity and resistance to existing treatments. Current Antibody-Drug Conjugates (ADCs), such as single-target therapies, face challenges in effectively addressing these issues. This proposal aims to overcome these limitations by developing a dual-targeting next-generation ADC that targets both TROP2 and EGFR, leveraging advanced AI technologies and proprietary conjugation methods to treat SCLC. Our state-of-the-art Generative AI workflow will design and optimize antibody designs for improved binding affinity, stability, and cysteine insertion sites while ensuring efficient site-specific conjugation. 20-25 antibody candidates will be screened, conjugated with a proprietary derivative, and thoroughly characterized for drug-to-antibody ratio, homogeneity, and stability to identify lead ADCs for further. This Generative AI-driven, dual-targeting approach is designed to enhance therapeutic precision, reduce resistance, and improve efficacy in SCLC treatments, offering a promising solution for this difficult-to-treat cancer. The proposed Generative AI-driven workflow and its scalability allow for future adaptation to other rare and pediatric cancers, thereby enabling the expansion of MarWell Bio’s drug pipeline. Project Number: 75N91025C00040-0-9999-1 | Fiscal Year: 2025 | NIH Institute/Center: National Cancer Institute (NCI) | Institution: MARWELL BIO INC., SOUTH SAN FRANCISCO, CA | Award Amount: $355,000 | Activity Code: N43 View on NIH RePORTER: https://reporter.nih.gov/project-details/11416390