Aurigene showcases explainable AI and physics-based molecular design at Discovery and Development EU 2025
New Delhi/Basel: Dr. Sunil Kumar Panigrahi, Associate Vice President – CADD & Informatics, recently delivered a talk titled “Intelligent Molecular Design: Bridging AI, Explainability, and Physics-based Simulation,” at Discovery and Development EU 2025 held in Basel, Switzerland; highlighting how the company’s proprietary platform Aurigene.AI accelerates design cycles while maintaining scientific rigor and interpretability.
At the core of the presentation was a case study on RIPK1 inhibitors, where the integrated use of Explainable AI (XAI), multiparameter optimization (MPO), and physics-based simulations (including molecular dynamics and free energy perturbation) led to the identification of five diverse hit series within a 3-month timeline. Twenty-one compounds were synthesized, and their activity confirmed using NanoBRET and kinase assays, with several hits achieving nanomolar potency.
Aurigene.AI: A Platform Built for Scientific Transparency
The platform integrates Generative and predictive AI models for de novo design, potency, ADMET, and synthetic feasibility. Its Graph Neural Network (GNN) architectures with interpretable layer structures and self-explaining chemistry models. Its Physics-based simulation including FEP, MD, and MM-GBSA for accurate prioritization of hits. It has ccess to 180M+ compounds, 12B+ virtual screening compounds, and 10+ chemistry-centric workflows
Aurigene.AI places a strong emphasis on model interpretability and experimental validation, creating a seamless loop between computational predictions and medicinal chemistry. “Our platform is purpose-built to demystify AI decision-making and enable data-driven compound progression with confidence,” said Dr. Panigrahi.
He mentioned about a project in his presentation. The project aimed to optimize solubility, permeability, metabolic stability, and hERG-related properties for a kinase-targeted drug discovery program while maintaining potency and selectivity. The challenge involved compounds with low solubility and permeability and high clearance. A holistic approach combining CADD, physics-based simulations, and AI/ML tools was employed for multiparameter optimization. Permeability improvements were accurately predicted using membrane insertion energy and Log Perm RRCK models (77% accuracy). Metabolic hotspots were identified to design compounds with enhanced stability, supported by AI/ML-driven local ADMET models addressing series-specific metabolism. Additionally, predictive models for hERG binding were implemented to mitigate cardiac safety risks.
Scaling New Heights in Bispecific Antibody Development
In another significant development, Aurigene has also achieved a significant milestone in its biologics journey with the successful development, regulatory approval, and patient dosing of a bispecific antibody candidate — all achieved within a year. This success underscores Aurigene’s growing capabilities in the development and manufacturing of complex biological molecules.
The company’s state-of-the-art biologics facility supports end-to-end services from cell line development through clinical manufacturing. Aurigene’s expertise spans mAbs, recombinant proteins and bispecific formats, powered by advanced technologies such as N-1 perfusion for high-density cell cultures, optimized filtration, and purification strategies. Aurigene’s analytical development team combines cutting-edge HPLC, UPLC and Orbitrap LC-MS platforms with advanced mass spectrometry to deliver comprehensive characterization of biologics.
“We are truly excited about the progress we’ve made in bispecific antibody development. The speed and scientific rigor with which we moved from development to IND clearance and patient dosing is a testament to our integrated platform and talented teams,” said Akhil Ravi, CEO of Aurigene Pharmaceutical Services. “This is just the beginning — we are committed to expanding our work in the bi-specifics space and partnering with innovators globally to bring these next-gen therapeutics to patients faster.”
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