Aganitha.ai

AI powered in silico solutions for BioPharma R&D. Multi-disciplinary team spanning multi-scale systems biology, computational chemistry & generative AI.

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The common thread across these applications is purpose-built computational approaches grounded in chemistry, physics, and biology that help reduce experimentation and improve decision-making.
Read the full blog here: https://t.co/EkWcrabZGn

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📖 New blog: "Beyond the Hype: How AI and Computational Chemistry Are Reshaping Formulation and Manufacturing"
Formulation, catalysis, crystallization, & manufacturing are among the most complex stages of Pharma R&D; AI and comp chem are beginning to deliver measurable value.

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• Predicting pKa, solubility, nitrosation risk & peptide permeability
• Speeding catalysis/biocatalysis via AI-guided enzyme engineering & reaction optimization
• Supporting formulation with API surrogate search, CSP & ASD models
• Building digital twins & forecasting model

[Aganitha.ai @AganithaAI]

📖 New blog: "Beyond the Hype: How AI and Computational Chemistry Are Reshaping Formulation and Manufacturing"
Formulation, catalysis, crystallization, & manufacturing are among the most complex stages of Pharma R&D; AI and comp chem are beginning to deliver measurable value.

[Aganitha.ai @AganithaAI]

📣 Krishna Harsha Adusumilli will present at the @3D_cellculture Hands-On Training Workshop on Alternatives to Animal Models.
"Beyond the Hype: Real-World Uses of #AI in Organoid Research" explores practical applications of #AgenticAI across the #organoid research workflow.

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📣 @AntaripHalder is presenting a poster at ACS National Medicinal Chemistry Symposium in Atlanta.

“Agentic #AI Integrated with #MD Reveals the Mechanistic Basis of Siponimod Selectivity for S1P Receptors,” explores subtype selectivity across highly homologous GPCRs.

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IgnivaLab™ is part of Igniva™, Aganitha's #AgenticAI workflows for Biopharma R&D.

Know more at:
https://t.co/Kj13epLgqZ

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Our vision is simple:

Build an AI collaborator that works alongside scientists, integrating tools, methods, literature, scientific reasoning, and experimental design into a seamless workflow.

#DrugDiscovery #AI #AgenticAI #BioPharma #LaboratoryAutomation #ScientificResearch

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To know more about IgnivaLab™, visit:

https://t.co/6Ie7kt7rs6

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And we're just getting started.

🤖 Coming next: Lab automation through PyLabRobot integration, helping bridge protocol design and experimental execution.

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More differentiators:
📊 Human-in-the-loop refinement for iterative protocol development
🤝 Collaborative and eLN-ready workflows designed for modern R&D teams

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What makes IgnivaLab™ different?

🔬 Citation-backed protocols linked directly to experimental rationale
🧭 Experimental design with controls, timelines, & editable plate layouts
🧬 Integrated scientific tools embedded within workflows
...

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IgnivaLab™ is built for scientific teams with:

✅ Version tracking
✅ Metadata management
✅ Peer validation
✅ Collaborative discussions
✅ Integrations with lab systems, computational & data analysis tools

Making protocols living scientific assets.

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Once a protocol is tested on the bench, it can be saved into a IgnivaLab™ Protocol Library.

This creates an institutional knowledge layer where scientific context stays attached to the workflow instead of being lost across notebooks, emails, and disconnected files.

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IgnivaLab™ doesn't just generate protocols.

It helps scientists connect:
• Literature evidence
• Scientific reasoning
• Experimental design
• Computational design of primers, guide RNAs, ...
• Workflow documentation

All within a unified environment.

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Bench Scientists spend countless hours before experiments even begin:

📚 Reviewing literature
🧪 Comparing protocols
🎯 Designing experiments
🔍 Refining controls
📝 Documenting scientific rationale

IgnivaLab™ is designed to support scientists throughout this process.

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From protocol generation and critique to plate design and citation-backed experimental workflows, IgnivaLab™ helps researchers design, rationalize, and refine experiments across the drug discovery value chain.

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🧪 Introducing IgnivaLab™: An #AI Collaborator for Bench Scientists

A new addition to Aganitha's Igniva™ #AgenticAI ecosystem. 🧵👇

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Under the hood:
• explicit ionisation-site identification
• dual-graph cross-attention
• solute–solvent interaction modelling
• Kamlet–Taft solvent descriptors

Together, these enable a unified multi-solvent prediction workflow.

#AI #CompChem

[Aganitha.ai @AganithaAI]

🤖 SitepKa predicts not just whether a molecule gains or loses protons, but also where within the molecule this happens — and how that behaviour changes across solvents.

The goal: faster and earlier molecular evaluation with reduced dependence on slow experimental testing.

[Aganitha.ai @AganithaAI]

🧠 SitepKa is a graph neural network for site-specific pKa prediction across water + 34 industrial organic solvents.

Rather than treating pKa as a single molecular property, SitepKa explicitly identifies ionisable sites & models their solvent-dependent behaviour.

#AI #CompChem