Aganitha Igniva™ for Chemistry: GenAI and Agentic AI Workflows for Molecular & Material Discovery

Science has always advanced at the intersection of disciplines. Today, we stand at the convergence of computational chemistry, artificial intelligence, and domain expertise to create molecular and material discovery opportunities.

It seamlessly integrates with existing R&D workflows, replacing one-size-fits-all solutions with a customizable suite of interconnected tools contextualized to specific R&D needs. By combining AI/ML with Physics-first methodologies, Igniva™ accelerates discovery while respecting scientific rigor and augmenting scientific intelligence.

Introducing Aganitha Igniva™ for Chemistry—a comprehensive suite of solutions designed to accelerate structural biology, molecule, and material discovery, and Chemistry, Manufacturing, and Controls (CMC). By integrating Generative AI, Large Language Models (LLMs), and Physics-first methodologies such as Quantum Mechanics (QM) and Molecular Dynamics (MD), Igniva™ delivers tailored solutions across industries.

Structural Biology: Addressing Challenges Beyond AlphaFold

Predicting protein structures has seen significant advances. However, many real-world problems remain unsolved. Igniva™ tackles complex scenarios beyond homology modeling, such as:

1. Structure modeling of novel targets with low or no homology, including polymers and biological interfaces such as hair-polymer interactions and skin permeation modeling.
2. Antibody stability and degradation predictions across various solvent environments.
3. AAV design for gene therapy, optimizing vectors for crossing the Blood-Brain Barrier (BBB).

Molecule & Material Discovery: Balancing Novelty with Synthesizability

Identifying new therapies and materials requires balancing innovation with real-world feasibility. Igniva™ enables:

1. New Chemical Entities (NCEs): Small molecules (SMOLs), covalent binders, monoclonal antibodies (mAbs), and PROTACs.
2. De novo Material Discovery: Surfactants, fragrance molecules for personal care, photoactivators for detergents, and biopolymers.
3. Optimization Across Properties: Drug binding affinity, ADMET profiling, mildness, skin sensitization, and emulsification.

CMC: Accelerating Formulation and Enabling Digital Twins

In CMC, modeling demands accuracy balanced with computational cost. Igniva™ streamlines:

1. Reaction modeling: Yield prediction, catalyst selection.
2. Formulation design: pKa prediction, stability of Amorphous Solid Dispersions (ASDs), Lipid nanoparticle (LNP) screening, Ionic Liquids (ILs), and Crystal Structure Prediction (CSP).
3. Digital twins for bioprocessing: Simulating unit operations such as fed-batch & perfusion bioreactors and continuous chromatography.

Navigating the Complexities of Modern R&D

By combining AI/ML with physics-first methodologies, Igniva™ accelerates discovery while respecting scientific rigor.
Key advantages of Aganitha Igniva™ for Chemistry that empower researchers towards informed decision-making:

• Seamless workflow integration: Customizable tools tailored to specific R&D workflows, ensuring compatibility and adoption.
• AI/ML and physics-driven discovery: A hybrid approach leveraging classical AI/ML with first-principles methods for robust scientific insights.
• GenAI-powered chemical exploration: Enhanced ability to compare analogs, assess counterfactuals, and explore diverse chemical neighborhoods.

Experience the Future of Chemistry Today

Discover how Aganitha Igniva™ for Chemistry can transform your R&D processes through the powerful combination of Agentic AI, GenAI, physics, and domain expertise.
Ready to transform your R&D processes? Contact us today to request a demo and see Igniva™ for Chemistry in action.