RenaissThera

RenaissThera is an Indian biotechnology startup focused on developing affordable, AI-powered small-molecule therapies for cardio-metabolic diseases with high unmet medical needs. Founded in 2023 and headquartered in Bengaluru, the company leverages artificial intelligence, machine learning, and computational drug discovery to accelerate the identification and optimization of novel therapeutic molecules. Its mission is to bridge the gap in access to innovative medicines by developing cost-effective oral therapies for underserved populations worldwide, particularly in the areas of obesity and Type 2 diabetes. At the core of RenaissThera's innovation is its AI-enabled drug discovery platform, which integrates Generative AI, machine learning, and translational biology to design and optimize small-molecule drug candidates targeting validated metabolic pathways, including GLP-1 and GIP receptors. Unlike injectable peptide therapies, the company's pipeline focuses on oral small-molecule medicines that are easier to manufacture, distribute, and administer, enabling broader patient access while reducing treatment costs. This approach aims to improve therapeutic outcomes and expand access to next-generation treatments for chronic metabolic diseases. RenaissThera collaborates with research organizations, AI technology partners, CROs, and biotechnology institutions to accelerate preclinical development and advance its drug pipeline toward clinical trials. The company also leverages India's contract research ecosystem to optimize R&D efficiency while maintaining global quality standards. Supported by seed funding, incubation at C-CAMP, and strategic industry collaborations, RenaissThera is building a scalable innovation platform for drug discovery. Through the integration of artificial intelligence, precision chemistry, and translational research, the company aims to deliver affordable, globally relevant therapies while strengthening India's position in AI-driven pharmaceutical innovation and addressing the growing burden of metabolic diseases.