DivyaIQ

Revolutionizing Drug Discovery with AI

DivyaIQ simulates molecular interactions and predicts drug efficacy using advanced generative AI, accelerating pharmaceutical research and development.

Demo Auto Login: koradiya@divyaiq.ai / Password: 123456

AI & ML in Clinical Trials infographic showing various applications including regulatory submission, study design, data analysis, and trial management
Use Cases

Transforming Pharmaceutical Research

Discover how DivyaIQ is revolutionizing drug discovery and development across various applications.

Molecular Simulation
Accurate prediction of molecular interactions

DivyaIQ provides detailed molecular dynamics simulations to predict how drug candidates interact with target proteins. Our platform offers:

  • High-fidelity 3D visualization of molecular structures
  • Real-time binding affinity calculations
  • Detailed interaction maps with target proteins
  • Simulation of various environmental conditions
  • Identification of key binding site residues
ADMET Prediction
Comprehensive pharmacokinetic analysis

Our AI models accurately predict Absorption, Distribution, Metabolism, Excretion, and Toxicity properties of drug candidates:

  • Early identification of potential toxicity issues
  • Bioavailability and solubility predictions
  • Blood-brain barrier penetration assessment
  • Metabolic stability and half-life estimation
  • Comprehensive drug-drug interaction analysis
Molecule Optimization
AI-driven compound enhancement

DivyaIQ's generative AI models suggest structural modifications to improve drug candidates' properties:

  • Target-specific binding affinity enhancement
  • Reduction of potential side effects
  • Improvement of pharmacokinetic properties
  • Generation of novel molecular scaffolds
  • Structure-activity relationship (SAR) analysis
Testimonials

Trusted by Leading Researchers

See what pharmaceutical researchers and companies are saying about DivyaIQ.

"DivyaIQ has transformed our drug discovery pipeline. The molecular simulations are incredibly accurate, and we've reduced our lead optimization time by 40%. A game-changer for our research team."

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Dr. Sarah Chen
Research Director, PharmaTech Inc.

"The ADMET prediction capabilities are remarkably precise. We've been able to identify potential toxicity issues early in the development process, saving us millions in development costs."

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Prof. James Wilson
Lead Researcher, BioAdvance Labs

"The molecule optimization suggestions from DivyaIQ have been invaluable. We've improved binding affinity by 30% on our lead compound while maintaining excellent pharmacokinetic properties."

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Dr. Maria Rodriguez
VP of Research, NovaCure Pharmaceuticals

"As a small biotech startup, DivyaIQ has given us access to computational capabilities that were previously only available to large pharmaceutical companies. The platform is intuitive and the results are outstanding."

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Dr. Alex Thompson
Founder & CEO, MoleculeX Therapeutics

"The integration of DivyaIQ into our academic research has accelerated our publication output significantly. Students can quickly test hypotheses and generate compelling visualizations for their research papers."

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Prof. Emily Nakamura
Department Chair, Molecular Biology, Stanford University

Ready to Transform Your Drug Discovery Process?

Experience the power of AI-driven molecular simulation and drug efficacy prediction.

Demo Auto Login: koradiya@divyaiq.ai / Password: 123456