End
infectious disease.

Infectious disease is mankind’s original enemy. A large fraction of all humans who ever lived died from bacterial infection. Antibiotics were a miraculous weapon in this fight, but as microbes evolve resistance, the antibiotic era is ending. We owe an unpayable debt to Alexander Fleming and all medical researchers. But the future—a permanent victory over infectious disease—won’t come from new antibiotics.

Microbes are DNA machines. If we can understand and write DNA in the context of an individual human infection, then we can intervene programmatically in that infection. This is the permanent victory over infectious disease. Until recently, fluently writing in-context DNA was beyond human capability. But it is no longer beyond AI capability.

Pathogenic microbes evolve. They find a way around any specific therapy, whether old-school antibiotic or modern biologic. The solution is not a better drug; it’s an algorithm that can design new DNA faster than a microbe can evolve resistance. We have to beat them at evolution itself. This is a learning task well-suited to modern machine learning.

We follow a three-part thesis:

1. Machine learning, not wet-lab research. Human biological expertise can only take us so far. In-context DNA design is an ML problem.

2. Algorithms, not a portfolio of drugs. This is a fundamental challenge to how the pharma industry thinks. We are not developing drugs. We are developing algorithms.

3. Move at software speed. This is really a consequence of part 1 and 2. But we are treating real patients today, six months after starting the company (among the fastest times ever recorded to get to this stage).

Tabula’s mission is to end infectious disease. AI has real downsides: job loss, datacenter power usage, slop content online. But it also has enormous potential. Near the top of any list of AI potential is the end of disease. This is truly possible. And we’re making it happen.