The Macro: Autoimmune Diseases Are Getting Worse and Current Drugs Are Not Good Enough
Autoimmune diseases affect over 50 million Americans. Rheumatoid arthritis, inflammatory bowel disease, multiple sclerosis, type 1 diabetes, lupus, and dozens of other conditions where the immune system attacks the body’s own tissues. The market for autoimmune treatments exceeds $100 billion annually.
The current standard of care relies heavily on broad immunosuppressants and biologics like Humira, Remicade, and Keytruda. These drugs work for many patients but have significant drawbacks: they suppress the entire immune system rather than targeting the specific dysfunction, they require ongoing treatment, they lose effectiveness over time, and they increase susceptibility to infections and cancers.
The fundamental problem is that suppressing the immune system is a blunt instrument. What you actually want is to reprogram the immune system to stop attacking specific tissues while maintaining its ability to fight infections and tumors. This kind of precision immunomodulation has been the holy grail of autoimmune research for decades.
Ditto Bio, backed by Y Combinator, has a counterintuitive insight: parasites have already solved this problem. Millions of years of evolution have produced organisms that expertly manipulate the human immune system. The company uses AI to find those mechanisms and turn them into drugs.
The Micro: Three PhDs Mining Millions of Years of Evolution
Dennis Sun (CEO, UC Berkeley PhD), Adair Borges (Chief Science Officer, UCSF PhD with 50+ publications), and Emily Weiss (CTO, UCSD PhD) bring deep expertise in evolutionary biology, parasitology, and computational biology. This is not a team of software engineers applying AI to biology. These are biologists who understand both the science and the computational tools.
The thesis is elegant. Viruses, ticks, and worms have spent millions of years evolving proteins that suppress or redirect human immune responses. They need to do this to survive inside a host. These immunomodulatory proteins have been refined by natural selection far longer than any drug development program could run.
Ditto Bio uses AI to identify these proteins from across the parasite kingdom, then engineers them into potential therapeutics for autoimmune conditions. The target conditions include rheumatoid arthritis, inflammatory bowel disease, multiple sclerosis, and type 1 diabetes.
The approach has scientific precedent. The “hygiene hypothesis” suggests that reduced parasite exposure in developed countries contributes to rising autoimmune disease rates. Clinical trials with helminth (worm) therapy have shown some efficacy but are impractical as treatments. Ditto Bio’s innovation is isolating the specific proteins responsible for immune modulation rather than using whole organisms.
Competitors include traditional pharma companies developing next-generation immunomodulators (like Janssen, AbbVie) and biotech startups using AI for drug discovery (like Recursion, Insilico Medicine). The parasite biology angle is genuinely unique in the space.
The Verdict
Ditto Bio has a compelling scientific thesis backed by evolutionary biology and a strong founding team. The question, as with all drug discovery, is whether the science translates to effective therapeutics.
At 30 days: how many candidate proteins has the AI platform identified, and how many are progressing through validation?
At 60 days: do the lead candidates show selective immunomodulation (suppressing autoimmune responses without broad immunosuppression) in preclinical models?
At 90 days: is the platform generating novel candidates that were not previously known from parasitology research? AI finding what human researchers missed would be the strongest validation.
I think Ditto Bio’s approach is one of the most scientifically interesting in the current YC batch. Evolution is the original drug discovery engine, and parasites are its most sophisticated immunologists. If Ditto Bio can turn parasitic immune manipulation into human therapeutics, they are tapping into a drug discovery library that no competitor can replicate.