The business brain behind a math problem
Hiranjith H walked into Algorithmic Biologics in April 2025 with a title - Chief Business Officer - and a pitch that sounds like science fiction read aloud at a dinner party. The company builds molecular computing technology that embeds algorithms directly into test-tube reactions. Instead of running a separate test for every sample, the math compresses many samples into a handful of pooled reactions, then untangles the answers with code. Cheaper. Faster. Quantitative. His task is the hardest part of any deeptech story: turning a beautiful equation into an invoice somebody signs.
The company was founded out of work by Manoj Gopalkrishnan, an IIT Bombay professor, and is headquartered in Bengaluru with a foot planted firmly in San Mateo, California. Hiranjith sits on the commercial side of that bridge. He runs go-to-market, business development, and partnerships, aiming the platform first at the United States, where the buyers and the budgets are.
His read on what he is selling is not modest. He sees the technology reaching well past the clinic.
"The company's innovative molecular computing technology has the potential to transform not just healthcare but also agriculture, animal science, and large-scale population screening."
- Hiranjith H, on joining Algorithmic Biologics
An algorithm in a test tube
Most molecular testing is brute force. One sample, one reaction, one answer, repeated until the machine and the budget give out. Algorithmic Biologics borrows an idea from compressed sensing - the same family of math that lets a phone reconstruct a sharp photo from sparse data - and applies it to biology. Its Tapestry approach pools many samples into a small number of reactions, runs them on the lab's existing qPCR or sequencing machines, and uses algorithms to recover individual, quantitative results.
The headline number that travels with the company is a 60-90% reduction in library-preparation costs for genomics. For Hiranjith, that number is the entire sales conversation. Labs do not buy elegance. They buy lower cost per result and the same answer they trusted yesterday.
The pitch, in one chart: traditional vs. compressed
Illustrative of the stated 60-90% library-prep savings. Same machines, same assays, fewer reactions.
From brand plans to base pairs
Before the test tubes, there were spreadsheets and strategy decks. Hiranjith spent more than fifteen years learning how large life-sciences organizations actually make money. At ZS Associates, the niche pharma consultancy, he advised clients like Janssen Biotech, GE, and MedImmune on commercial strategy. At Novartis he sat with franchise-planning teams, mapping launches for new brands and defending the ones already in market. Accenture Management Consulting filled in the rest of the playbook: marketing analytics, brand planning, commercial operations.
Then came the decade that reshaped him. At MedGenome, the genomics and diagnostics company, he climbed through corporate leadership roles and eventually became Vice President and Site Head of MedGenome USA. There he did the unglamorous, decisive work of standing up a commercial operation in a new country and scaling it. That is the exact muscle Algorithmic Biologics hired him to flex again.
- ConsultingManagement Consultant, ZS Associates - pharma clients incl. Janssen, GE, MedImmune
- PharmaSenior Manager, Novartis - launch and in-market brand strategy
- FoundationConference Manager, SciGenom Research Foundation
- 10+ yearsMultiple leadership roles at MedGenome
- USAVP & Site Head, MedGenome USA - launched and scaled US operations
- 2025Chief Business Officer, Algorithmic Biologics
The fit
When Manoj Gopalkrishnan announced the hire, he did not talk about resumes. He talked about a match between a person and a mission.
"His proven track record of scaling businesses, building global teams and forging strategic partnerships aligns perfectly with our mission."
- Manoj Gopalkrishnan, Founder, Algorithmic Biologics
It is a telling pairing. The founder is the mathematician who proved chemistry can compute. Hiranjith is the operator who knows how to put that proof in front of a buyer in Boston or San Diego without losing the plot. Deeptech companies often die in exactly the gap he is hired to close - the distance between a brilliant lab result and a repeatable commercial contract.
Two things worth knowing
He went back to school for the machine
Mid-career, already an MBA from the Great Lakes Institute of Management, he picked up a machine-learning credential from Stanford. A commercial leader teaching himself the math underneath the products he sells.
He lives on the bridge
Based in the San Francisco Bay Area, working for a Bengaluru-founded company, his whole job is cross-border. He translates Indian deeptech into American buying behavior - and back.