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IGC Pharma, Inc. ("IGC Pharma," "IGC," or the "Company") (NYSE:IGC), a clinical-stage biotechnology company leveraging AI to develop innovative treatments for Alzheimer's disease, today announced an expansion of its AI-powered in-Silico drug discovery platform. The company is now integrating more methodologies, including retrosynthetic analysis, molecular docking, toxicology and genotoxic assessments, and predictive bioactivity modeling, to accelerate the identification and optimization of therapeutic candidates for Alzheimer's disease (AD) and related disorders.
This strategic enhancement aims to optimize the drug development process, reducing the time and resources traditionally required for compound screening and lead optimization. By leveraging AI-driven tools, IGC Pharma seeks to identify promising molecular structures within its patent portfolio more efficiently, predict their interactions with biological targets, and assess their potential efficacy and safety profiles early in the development cycle.
"The incorporation of these advanced in-silico techniques marks an important advancement in our drug discovery efforts," said Ram Mukunda, CEO of IGC Pharma. "By simulating and analyzing molecular interactions computationally, we can prioritize the most promising candidates for synthesis and experimental validation, thereby accelerating our pipeline. This integration underscores our commitment to utilizing cutting-edge technologies, including our AI-driven MINT-AD model, to transform the discovery and development of novel therapeutics for neurodegenerative diseases. Our goal is to bring effective treatments to patients sooner and address the urgent unmet needs of patients and caregivers affected by Alzheimer's disease."
IGC Pharma's expanded platform includes:
Toxicology and genotoxic assessments: Predict potential adverse effects of compounds, enabling early identification of toxicity risks and reducing reliance on animal testing.
Predictive Bioactivity Modeling: Forecast the biological activity of compounds across various targets, including CB1, CB2, dopamine, serotonin, muscarinic, GLP-1, and GIP receptors.
Molecular Docking Simulations: Predict the binding affinity and orientation of small molecules within target protein sites, aiding in the assessment of therapeutic potential.
Retrosynthetic Analysis: Decomposing complex molecules into simpler precursors facilitates the design of feasible synthetic pathways.
These enhancements complement IGC Pharma's ongoing efforts to develop innovative treatments for AD. The company's lead candidate, IGC-AD1, is currently in Phase 2 clinical trials targeting agitation in Alzheimer's patients and has shown potential to inhibit amyloid-beta aggregation, prevent neurofibrillary tangle formation, and enhance mitochondrial function. The TGR‑63 program focuses on amyloid plaque reduction, with preclinical studies demonstrating significant plaque clearance in the cortex and hippocampus. Additional programs include IGC‑1C, a dual-action candidate targeting tau proteins and the GLP‑1 receptor, and IGC‑1A, an AI‑identified GLP‑1 receptor agonist offering promise for both metabolic and neurological disorders. Together, these initiatives reflect IGC Pharma's commitment to leveraging advanced in‑silico methods and novel molecular approaches to accelerate the discovery and development of transformative therapies for neurodegenerative diseases.
Posted In: IGC
