An antibiotic that slips through a bacterial doorway. A business that gets paid to be ready. Shionogi Inc. (U.S.) shows why selling medicine and protecting its usefulness can pull in different directions.
A hepatitis C blockbuster disappeared. A cystic fibrosis franchise took its place. Now Vertex is spending billions to see how often it can repeat the trick.
A blood-disorder pill and a skin cream share an active ingredient. Inside Incyte, that unlikely pairing explains both the business and the hard limits of a good scientific idea.
A laboratory can generate mountains of results and still struggle to answer a simple question. Dotmatics built a business in that gap. Siemens paid $5.1 billion to own it.
Drug-discovery AI needs something less glamorous than another algorithm: scientific results it can actually use. Excelra has built a business around that missing step.
An RNA drug can hit its target and still cause trouble elsewhere. Deep Genomics is building AI that reads both sides of that bargain, with laboratory experiments keeping score.
A gene can tell more than one story. Envisagenics reads the RNA edits that conventional drug discovery can miss - and pharma is paying for a closer look.
The Boston biotech designs drugs for receptors in motion. A Lilly partnership and a coming obesity trial will test how much that extra dimension is worth.
The Boston biotech builds human tissue models on microfluidic chips, then studies their responses with imaging and AI. Its wager: better drug predictions begin with better experiments.
Some proteins resist a drug’s advances. Magnet Biomedicine is recruiting a second protein to help - a molecular matchmaking strategy that has attracted $50 million in venture funding and an oncology agreement with Lilly.
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.
Now called Rezera, NodThera is taking an oral inflammation inhibitor toward a planned Phase 3 trial in peripheral artery disease. Its latest human results offer a useful lesson in what a promising drug actually proves.
Ship the samples. Write the instructions. Emerald Cloud Lab lets researchers run physical experiments from a computer - and exposes how much of science depends on the instructions nobody writes down.
Some proteins are difficult to block. Dewpoint is testing whether changing where they gather inside a cell can change what they do - and its first cancer drug has reached patients.
Hospitals, drugmakers and banks want to learn from one another. Rhino Federated Computing gives them a way to collaborate while keeping sensitive records where they belong.
An AbbVie deal worth up to $1.2 billion bought one Gilgamesh program. The independent company that emerged is pursuing a harder prize: fast depression treatment that fits ordinary life.
A molecule can look magnificent on a screen and disappoint in a flask. TandemAI connects AI, molecular physics and wet labs so the next design can learn from the last experiment.
A cystic-fibrosis lesson became a $100 million biotech bet: help faulty membrane proteins do their jobs. Rectify’s lead liver-disease candidate is now in Phase 1, with a kidney-disease partnership behind it.
ChemDraw taught chemists to draw on a computer. Its owner now wants experiments, collaborators and AI models to speak the same language - and the most revealing case begins with a hunt for old lab notes.
A cardiologist and a cancer biologist found a shared puzzle in cells under stress. Soley Therapeutics is turning that puzzle into a drug pipeline - and a test of how much a living cell can tell us before a medicine reaches a patient.
Strateos put experiments behind a browser. Then its pharmaceutical customers asked for something more particular: the same machinery, inside their own walls.
A cell can look ordinary at noon and turn resistant by night. Cellanome built a machine to keep watching - then read the RNA of the very cells in the film.
The Alameda biotech searches human immune memory for drug candidates, then uses computation to improve them. Its first big test is eczema: two antibodies, $87 million in disclosed funding, and clinical studies planned for 2027.
AI Proteins designs tiny medicines from scratch, then asks its robots whether the molecules can actually do the work. A Bristol Myers Squibb deal shows the appeal; the laboratory still has the last word.
Immunai set out to map the immune system. The harder business was teaching drugmakers what to do with the map - and proving a pattern in cells can survive contact with a patient.
NewLimit wants to make an old cell useful again without making it forget what kind of cell it is. Its first test of that idea is headed from the liver lab toward human trials.
AGY Therapeutics raised millions to turn maps of diseased brains into medicines. Its most revealing experiment came when it licensed a drug it had not invented.
Deep Apple bets that the best drug target may be a fleeting shape of a protein. Its search through billions of virtual molecules has yielded a Novo Nordisk partnership and an early drug candidate - with the hardest tests still ahead.
XWPharma built an investigational sleep drug around a plain inconvenience: treatment should not interrupt the night it is meant to repair. A $20 million upfront license turned that idea into a business deal.
Octant built a way to watch thousands of genetic variants misroute a protein inside living cells. Its first test is an oral drug for inherited blindness - and the wager is that one molecule can help more than one mutation.