The Future of Drug Discovery Should Be Open

Artificial intelligence is transforming biology at an unprecedented pace. From predicting protein structures to designing entirely new therapeutic molecules, AI has become one of the most powerful tools available to modern researchers. Yet, despite these breakthroughs, much of the underlying technology remains inaccessible—locked behind proprietary models, closed datasets, or infrastructure that only a handful of organizations can use.

This raises an important question:

Can scientific progress truly accelerate if the tools behind it remain closed?

At OpenFold, we believe the answer is no.

Why Open Science Matters More Than Ever

Every major breakthrough in science has been built upon collaboration.

The Human Genome Project, open-source software, and public biological databases have demonstrated that when knowledge is shared, innovation accelerates. Researchers spend less time rebuilding existing work and more time discovering what’s next.

AI for biology should follow the same principle.

When models, datasets, and training pipelines are openly available, researchers across universities, startups, pharmaceutical companies, and nonprofit organizations can validate results, improve existing methods, and develop entirely new applications.

The result isn’t just faster research—it is more trustworthy and reproducible science.

The Challenge with Closed AI Models

Modern biomolecular AI systems require enormous computational resources, carefully curated datasets, and sophisticated engineering.

Unfortunately, many state-of-the-art models are released only as black boxes.

Researchers can use them, but they cannot:

• Understand how they were trained
• Verify scientific claims
• Retrain models on new biological data
• Improve model architectures
• Adapt them for specialized research

Without transparency, scientific reproducibility suffers.

Without reproducibility, progress slows.

Building Open Infrastructure for Biology

OpenFold exists to change that.

Our mission is to develop open, retrainable AI infrastructure that empowers the global scientific community.

Instead of treating AI models as finished products, we view them as community infrastructure—tools that anyone can inspect, improve, extend, and build upon.

This includes:

• Open-source model implementations
• Transparent training pipelines
• Community-driven benchmarks
• Reproducible research workflows
• Collaboration across academia, biotechnology, and industry

By making every layer of the technology stack accessible, we enable researchers to focus on solving biological challenges rather than recreating infrastructure from scratch.

Collaboration Drives Better Science

Drug discovery is one of the most complex scientific challenges humanity faces.

No single organization possesses all the expertise required to solve it.

Progress requires collaboration between:

• Computational biologists
• Machine learning researchers
• Structural biologists
• Software engineers
• Pharmaceutical scientists
• Academic institutions
• Nonprofit organizations

Open ecosystems make these collaborations possible by providing common foundations that everyone can contribute to and benefit from.

Transparency Builds Trust

AI is increasingly influencing decisions that affect healthcare and medicine.

As these systems become more capable, transparency becomes just as important as accuracy.

Open models allow researchers to:

• Validate scientific findings independently
• Identify limitations
• Benchmark performance fairly
• Improve safety and reliability
• Build confidence within the scientific community

Trust is earned through openness—not secrecy.

Looking Ahead

The next decade of biological research will be defined by AI.

The question is not whether AI will transform biology.

The question is whether that transformation will be open, collaborative, and accessible to everyone.

At OpenFold, we believe the future belongs to shared knowledge, transparent research, and community-driven innovation.

Together, we can build AI infrastructure that accelerates discovery, empowers researchers everywhere, and helps bring life-changing medicines to the world faster.

Because the future of biology shouldn’t belong to a few organizations.

It should belong to everyone.