The company that emerged from Hewlett-Packard built a business around the unglamorous parts of science: separating samples, keeping instruments running, and making results trustworthy.
A laboratory result is only useful if the right information travels with it. SCC Soft Computer has built its business around that deceptively difficult journey.
A home test kit solved the appointment problem. Then LetsGetChecked started buying the pieces needed to turn a result into care.
The BIOMEDICAN founder builds companies around complicated biology. The revealing detail is how readily he admits that running the company can get in the way of the work he loves.

Before co-founding Illumina, John Stuelpnagel worked with large animals. His second career has been a long exercise in spotting what a promising invention will need next.
J. Craig Venter helped read the human genome, then took a laboratory to sea and helped build a cell with synthetic DNA. Each apparent finish line left him with a more interesting question.
Two biochemists built a laboratory in Brasília. A costly mistake, a patient approach to expansion, and R$90 million in automation explain how it became a national health business.
A plant-evolution researcher took the unfamiliar door into entrepreneurship. At Biotia, Niamh B. O'Hara has spent a decade learning what it takes to turn scientific work into a company.
Hospitals record millions of lives and struggle to learn from them together. Truveta gave those hospitals a stake in the answer - and is now adding genetics to the medical record.
The hard part of genomic research is often getting permission to use what already exists. Lifebit sends the tools to the data, turning institutional boundaries into something a researcher can work across.
A better steak begins long before the butcher. Breedr connects cattle records, genetics and trading so the people raising an animal can learn what happened after it left their ranch.
Discovery gets the applause. Pipetting gets the afternoon. Opentrons builds lab robots that take on the repetition, and its next wager is that AI will need a reliable pair of hands.
Sequencing became cheaper. Making sense of the results remained expensive. DNAnexus built a business in that gap, moving biomedical research into shared cloud workspaces - with all the promise, bills and permissions that entails.
A hospital can have the right patients and still miss the trial. TriNetX makes those patients count before anyone starts recruiting - and turns the same clinical records into a working research network.
The clever move in genomics was to stop moving the data. Seven Bridges built a business bringing researchers, workflows and rented computing power to the same place - and now carries that idea into Velsera.
A physicist and a materials scientist put biology on a chip. Ten years later, Axbio is asking whether the economics of DNA reading can start to look like the economics of computing.

He learned the rules inside global pharma, then chose companies where every arrival matters. At Deep Genomics, Brian O’Callaghan’s job is to turn formidable RNA research into a business that can deliver medicines.
Centrillion borrowed the tools of a semiconductor fab to make biology legible - then discovered that the most useful product might be the manufacturing system behind the chip.
Samba Scientific hires people who can read the paper, question the claim and still build the campaign. The wager is simple: in biotech, fluency is not decoration - it is the shortest route from a complicated product to a credible lead.
The bilingual publisher spent years explaining Asian biotech to the world. Then it packaged the map behind the reporting into BIODND - an AI-assisted database built for the people hunting companies, capital and partners.
Biotech companies can spend years waiting for their next big announcement. Bioscribe has built a communications business around the science, people, and progress in between.
In Trieste, a public research organisation pairs funding with access to microscopes, genomics and computing. Its bet: give difficult ideas the equipment and expertise to prove themselves.
A robot arm was only the beginning. Automata now connects the machines, movements and data that keep laboratories waiting - and gives scientists a chance to leave the bench.
InstaDeep began in Tunis with two laptops, about $2,000 and no tidy business plan. A decade later, its algorithms route circuit boards, read genomes and sit inside BioNTech's bet on AI-designed medicine.
Clinisys sits in the quiet, high-stakes gap between a specimen arriving and an answer going out. Its next act is to turn decades of specialist lab software into one cloud platform - without breaking the workflows that already move billions of tests.

An economist from a Russian science town turned his father’s unfinished research into a decade-long biotech company. The useful lesson is not romance. It is his stubborn method: narrow the question, protect the idea, and keep earning the next experiment.

Before AI became biotech's favorite phrase, Pek Lum was teaching computers to notice what biology hides in plain sight. At Auransa, that long apprenticeship has become a patient-first method for finding the signal inside human complexity.

After helping annotate genomes and guide five Gilead therapies to approval, the physician-scientist left the large-company machine to build OrsoBio - a small team making a careful wager on how cells spend energy.

A mosquito-genomics researcher spotted a stubborn gap between scientific discovery and useful software. He packed up in Oxford, returned to Rome, and began the long work of making inherited risk legible in the clinic.

From Mosaic and web chat to social games and computational biology, Andrew Busey has spent three decades asking an unfashionably useful question: what essential piece is everyone else overlooking?