Ersilia Book
  • 🤗Welcome to Ersilia!
    • The Ersilia Open Source Initiative
    • Ten principles
    • Ersilia's ecosystem
  • 🚀Ersilia Model Hub
    • Getting started
    • Online inference
    • Local inference
    • Model contribution
      • Model template
      • Model incorporation workflow
      • Troubleshooting models
      • BioModels annotation
    • For developers
      • Command line interface
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      • Test command
      • Testing playground
      • Model packaging
      • Inputs
      • Codebase quality and consistency
      • Results caching
  • 💊Chemistry tools
    • Automated activity prediction models
      • Light-weight AutoML with LazyQSAR
      • Accurate AutoML with ZairaChem
      • Model distillation with Olinda
    • Sampling the chemical space
    • Encryption of AI/ML models
  • AMR chemical collections
  • 🙌Contributors
    • Communication channels
    • Tech stack
    • Internships
      • Outreachy Summer 2025
      • Outreachy Winter 2024
      • Outreachy Summer 2024
      • Outreachy Winter 2023
      • Outreachy Summer 2023
      • Outreachy Winter 2022
      • Outreachy Summer 2022
  • 📑Training materials
    • AI2050 intro workshop
    • AI2050 AI for Drug Discovery
    • Introduction to ML for Drug Discovery
    • Python 101
    • External resources
  • 🎨Styles
    • Brand guidelines
    • Slide and document templates
    • Scientific figures with Stylia
    • Coding style
  • 🌍About Us
    • Where to find us?
    • Diversity and inclusion statement
    • Code of conduct
    • Open standards and best practices
    • Ersilia privacy notice
    • Strategic Plan 2025-2027
    • Ersilia, the Invisible City
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2025, Ersilia Open Source Initiative

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  1. Welcome to Ersilia!

Ten principles

Ersilia’s 10 Principles guide our decision-making and roadmap

  1. Science is a driver of socioeconomic development. It must be done everywhere, including in the poorest regions.

  2. Modern science is rooted in colonialist practices. This should be acknowledged and reversed.

  3. Research agendas must be dictated by the needs of the people worldwide, not by a privileged minority or to satisfy private interests.

  4. Scientific knowledge should be immediately free and accessible to all.

  5. AI and digital technologies have become a fundamental part of experimental sciences.

  6. Open source software, if properly funded and maintained, promotes reproducibility and reusability of scientific outputs.

  7. Community building is at the root of scientific innovation and ensures participation of the global majority.

  8. Training and mentoring are integral to scientific development and the only path to sustainability.

  9. AI requires vast amounts of data. Also in science, data providers should be credited and data extractivism avoided.

  10. AI is transforming our world — at the risk of deepening existing inequalities. Science is one aspect of society where AI can bear undisputable good.

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