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Schrödinger

by Schrödinger, Inc.schrodinger.com
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OVERVIEW

Physics-based computational platform for drug discovery with advanced molecular modeling and simulation

Schrödinger is a leading physics-based computational platform that transforms the way therapeutics and materials are discovered. Founded in 1990, the company has pioneered advanced molecular modeling and simulation technologies used by the world's top pharmaceutical and biotech companies.

The platform integrates differentiated solutions for predictive modeling, data analytics, and collaboration across two main domains:

Life Science Solutions: Schrödinger's drug discovery platform includes industry-leading tools such as Maestro (molecular modeling interface), Glide (molecular docking with 98% pose accuracy), FEP+ (free energy calculations), LiveDesign (collaborative design platform), and BioLuminate (biologics tools). These solutions enable structure prediction, target validation, hit identification, lead optimization, and accelerated drug discovery cycles through simulation-driven approaches.

Materials Science Solutions: The materials science platform features MS Maestro, Desmond (molecular dynamics), Jaguar (quantum chemistry), and MS LiveDesign for polymer research, electronics development, and catalyst design.

Key Capabilities:

  • In silico molecular property predictions with physics-based accuracy
  • Chemical space exploration across extensive molecular libraries
  • Molecular dynamics simulations for biologics and small molecules
  • AI-powered next best action recommendations
  • Collaborative design workflows with LiveDesign platform
  • Python API for custom workflow integration

Schrödinger serves the top 20 pharmaceutical companies by revenue, numerous biotech startups, academic institutions, and government laboratories across more than 70 countries. The company employs approximately 900 people across 12 global offices and has received recognition as America's #1 Most Loved Workplace in Pharma/Biotech by Newsweek (2022).

The platform is trusted by leading organizations including Bayer, Takeda, Merck, and Agios Pharmaceuticals for developing FDA-approved medicines enabled by computational design. Schrödinger also co-founded Nimbus Therapeutics, demonstrating the platform's effectiveness in accelerating drug discovery from concept to clinic.

RATING & STATS

Customers
1,000+
Founded
1990

KEY FEATURES

  • Maestro molecular modeling interface
  • Glide molecular docking (98% pose accuracy)
  • FEP+ free energy calculations
  • LiveDesign collaborative platform
  • BioLuminate for biologics design
  • Desmond molecular dynamics
  • Jaguar quantum chemistry
  • Python API for integration
  • Physics-based predictive modeling
  • AI/ML-powered insights

PRICING

Model: enterprise
Starting at: USD 7500.00
Custom enterprise pricing based on modules, cores/nodes, and license term. Academic pricing starts at $7,500/year for Premium package with 30 tokens. Contact for customized commercial quote.

TECHNICAL DETAILS

Deployment: cloud, on_premise, saas
Platforms: web, windows, mac, linux
🔌 API Available

USE CASES

Small molecule drug discoveryAntibody and biologics designLead optimizationVirtual screeningMolecular dynamics simulationMaterials science researchPeptide discoveryEnzyme engineering

INTEGRATIONS

Google Cloud PlatformPython APILIMS systemsCustom API integrations

COMPLIANCE & SECURITY

Security Features:
  • 🔒Enterprise-grade cloud security via Google Cloud
  • 🔒Data encryption on cloud
  • 🔒Private instance hosting
  • 🔒Vendor security baseline assessment

SUPPORT & IMPLEMENTATION

Support: email, phone, dedicated account manager, knowledge base, Application scientist support
Implementation Time: 1-3 months
Target Company Size: medium, enterprise
TRAINING AVAILABLE

PROS & CONS

✓ Pros:
  • +Industry-leading physics-based accuracy
  • +Comprehensive feature set for drug discovery
  • +Excellent customer support with application scientists
  • +Trusted by top 20 pharma companies
  • +Python API for customization
✗ Cons:
  • -Expensive for small organizations
  • -Steep learning curve for advanced features
  • -Requires significant computational resources
  • -Limited student support options

ABOUT SCHRÖDINGER, INC.