Ajay
Kshatriya

In November 2024, a small company in San Diego stopped being a secret. Aizen Therapeutics announced itself with $13 million, a Caltech pedigree, and a claim that sounds like science fiction read backwards: it wants to make medicines out of mirror-image molecules.

Ajay Kshatriya runs it. The idea at the center of Aizen is deceptively simple and stubbornly hard. Almost every protein and peptide in living things is built from L-amino acids - "left-handed" building blocks. Their mirror images, the "right-handed" D-amino acids, are chemically real but biologically rare. Bodies don't make them, and crucially, the enzymes that chew up ordinary peptides don't recognize them either. That last part is the prize. A peptide drug that survives longer, provokes less of an immune response, and binds its target with precision.

Aizen calls these Mirror Peptides, and they are pitched not as a tweak but as a new drug class. The catch has always been design. You can't simply copy what nature already optimized over a few billion years, because nature never bothered with the mirror world. So Aizen built a tool to explore it: a platform named DaX, short for D-amino acid eXplorer, that fuses generative AI with structural biology to design full D-amino acid therapeutics from scratch. It is, in the company's telling, a capability the industry simply did not have before.

Aizen spun out of the Caltech laboratory of David Van Valen, the scientific founder, a professor whose work sits at the seam of machine learning and biology. Van Valen brought the science. Kshatriya brought something harder to fund and harder to fake: the experience of turning a fragile academic idea into a company that ships.

From the bench at Genentech to the back of a seed fund

Kshatriya did not start as a founder. He started as a chemical engineer. A B.S. from UC Berkeley, an M.S. in engineering from Stanford, and later an MBA back at Berkeley's Haas School - three degrees that read like a deliberate refusal to specialize. His first serious chapter was Genentech, the company that more or less invented the biotech industry. He worked in product operations and sat on two early-stage oncology product core teams, close enough to the science to respect it and close enough to the business to see how drugs actually reach people.

Then a detour that turned out to be the point. Before he built anything, he learned how things get built by joining XSeed Capital, a $100 million seed fund spun out of Mohr Davidow Ventures whose entire job was forming companies out of raw science. Watching founders from the investor's chair is an unusual apprenticeship. You see the wreckage and the wins, the pitch that lands and the one that should have. Kshatriya absorbed the pattern, and then went and did it himself.

Biota: the company that saved a billion gallons of water

In 2013 he co-founded Biota Technology with Joel Moxley and the microbiome scientist Rob Knight. Biota was a strange and wonderful bet - environmental genomics, the idea that you could sequence the microscopic life living in rock and water to understand what was happening thousands of feet underground. Oil and gas operators wanted to know where their wells were actually producing. Biota told them by reading DNA.

It worked. Over roughly eight years, Kshatriya scaled Biota from a university microbiome data platform into a commercial genomics business. The numbers are the kind founders dream about and rarely get to say out loud: around $400 million in economic value created, and 1.2 billion gallons of water saved for more than twenty industrial companies. In 2021, the industrial biotech giant Novozymes acquired it. A first company, a real exit, and a thesis proven - that genomic data, read at scale, is worth money.

That thesis is the through-line. Biota read nature's data to find value underground. Aizen uses AI to write new molecular data nature never produced. Same instinct, opposite direction. One excavates what exists; the other manufactures what doesn't.

Why the mirror, and why now

Peptide drugs are having a moment - think of the blockbuster metabolic medicines reshaping medicine cabinets. But peptides have an old, well-known weakness. The body's proteases treat them as food, so they degrade fast, and some trigger unwanted immune attention. For decades, chemists knew that D-amino acid peptides could dodge those problems. The trouble was designing one that still did its job. Binding a target requires exquisite three-dimensional fit, and the mirror world had no playbook.

What changed is the same thing that changed everything else: computation got good enough. Generative models that can reason about protein structure, paired with lab processes that produce training data at industrial scale, turned the undesignable into the merely difficult. That combination - AI plus a wet lab that feeds it - is exactly the bet Aizen's investors made. Madrona led the round, joined by Wilson Hill and Cercano, drawn to a company sitting precisely where machine learning and biology now overlap.

Aizen's stated targets are not small: oncology, neurodegenerative disease, genetic disease - the places where conventional drugs keep hitting walls. Transmembrane receptors that have frustrated drug hunters for years. The pitch is that an entirely new chemical space, designed rather than discovered, might reach what the old toolkit could not.

The investor who still picks up the pager

Kshatriya didn't stop building when he started writing checks. He is a partner at Wilson Hill Ventures, an early-stage firm where he invests in science-based startups emerging from Caltech - the same ecosystem that produced Aizen. It is a tidy loop. He scouts the science, backs the founders, and in Aizen's case, decided one idea was good enough to run himself rather than just fund.

There's a temperament in all of this. He is drawn to problems where the science is real but the commercial path is unproven, the kind most people call too early. Environmental genomics was too early until it wasn't. Mirror-image drugs are too early right up until the moment a molecule works. Kshatriya keeps planting his flag a few years before the conventional wisdom catches up, which is either the riskiest possible strategy or the only one that produces a genuinely new drug class.

A portfolio of bets, not a single one

Aizen is the headline, but it isn't the whole resume. Kshatriya has kept a hand in the wider world of science startups - listed over the years as a managing director at Artisan Bio and active across the early-stage biotech ecosystem he both invests in and operates within. He is also a member of YPO, the global network of chief executives, where he has served on the board of the Coastal San Diego chapter. The pattern is consistent: he likes company-building enough to do several versions of it at once, and he keeps the company of other operators rather than retreating into a single title.

It matters for Aizen because mirror-image drug design is not a one-person sport. The company's pitch leans on having assembled, alongside Van Valen, a team with deep biopharma expertise - the people who know how a molecule becomes a clinical candidate becomes a filing becomes a medicine. Kshatriya's job is less to invent the chemistry than to make sure the chemistry has somewhere to go. He has done the full arc once already, from a university data platform to an acquired company, and that lived experience is its own kind of credential in a field crowded with promising platforms that never found the exit.

The conjugate angle

One detail in Kshatriya's own words is easy to skim past and worth slowing down for. He describes Mirror Peptides not only as standalone drugs but as a "targeting moiety or drug conjugate" - the precise guidance system that steers a more aggressive payload to exactly the right cell. That framing is a tell. It positions Aizen not as a maker of one hero molecule but as a supplier of a new building block, something other drug programs could bolt on. A stable, low-immunogenicity, AI-designed binder is useful far beyond a single indication, which is why the company has spoken openly about biopharma collaboration discussions even at launch.

What he is building now will take years to prove. Mirror Peptides are still early pipeline programs, not approved medicines, and the graveyard of biotech is full of elegant platforms that never produced a pill. But the question Aizen is asking is a good one, and rare. Most drug companies search the space nature already mapped. Kshatriya is funding an expedition into the half of chemistry that life forgot to use.

If it works, the mirror won't just reflect biology. It will rewrite the catalog of what a medicine can be made of.