Harvard spinout lands $40 million to bring in vivo drug discovery to cancer
The marriage of biology with technology is on the rise as companies look for new ways to bring computational techniques to drug research. The goal is to make iterative drug discovery processes scalable, making the whole effort faster and more efficient. But no matter how much of that work is done with software and mouse clicks, at some point a new molecule must eventually find its way into a real, living mouse. And this is where the startup Manifold Bio wants to stand out.
The first traditional drug discovery work consisted of a series of laboratory tests. The results become more predictive of how well a drug works, but each successive test also becomes more expensive, said Manifold co-founder and CEO Gleb Kuznetsov. The difficult question is what does a molecule do inside a mammal? Companies generally select their best molecules for animal testing: one molecule per mouse. Manifold’s technology allows many molecules, potentially hundreds, to be tested on a single mouse.
“In vivo tests are usually done later,” Kuznetsov said. “If we can try several [molecules] earlier, in vivo, this could be a breakthrough strategy.
Investors agree. On Thursday, Manifold unveiled $40 million in fundinga Series A round led by Triatomic Capital.
Boston-based Manifold was born out of Harvard University, where Kuznetsov and company co-founder Pierce Ogden were graduate students in geneticist George Church’s lab. This lab has formed many biotech startups over the years, and Kuznetsov said a common theme among them is combining cutting-edge molecular biology with other technologies. More than developing new drugs, these companies are trying to challenge traditional drug discovery paradigms, he said.
Manifold develops protein drugs. The technology that allows the startup to test several drugs on a single mouse is a protein “barcode”, a marker placed on an experimental molecule, allowing it to be tracked. Using this capability, Manifold scientists can determine where molecules are going in the animal and which are having an effect. Scientists can also identify molecules that are not targeted and could trigger toxic effects. Kuznetsov said this technology can find promising molecules much earlier and at a lower cost than traditional drug discovery methods.
Manifold first unveiled its approach in 2020, when it raised $5.4 million in a seed funding led by Playground Global. This company also participated in the Series A round, which added new investors Section 32, FPV Ventures, Horizons Ventures and Tencent. Previous investors Fifty Years and FAST by GETTYLAB also participated.
Jory Bell, General Partner of Playground Global, said he immediately recognized the potential of the Manifold technology. What Manifold learns about his molecules with a dozen mice would require hundreds of mice using traditional methods, he said. Testing animals earlier also gives drug hunters more options. By the time a startup reaches animal testing, it’s usually locked into one or two molecules, Bell explained. Obtaining animal data from more molecules means Manifold can take what it learns about them and apply that information to its drug candidates much earlier.
“So the odds of success in the clinic increase dramatically because you can choose the best drugs early on,” Bell said.
Manifold’s technology can be applied to many indications. Cancer is the company’s initial focus, an area chosen because it offers plenty of opportunities to quickly reach clinical trials to show that the company’s technology works, Kuznetsov said. The research has already led to some drug programs, but he said the company was not ready to provide details about them or say when they might reach human testing.
Kuznetsov described Manifold’s drugs as antibody-like molecules. The company designs them to address two challenges of cancer antibody drugs: specificity and toxicity. In addition to building its internal pipeline, Kuznetsov said Manifold is now looking to partner with other companies interested in applying barcode technology to their own drug research.
Several new companies have emerged with funding over the past year to support computational approaches to protein drug discovery. One startup, Creyon Bio, specializing in oligonucleotides, says the ability of its artificial intelligence-based technology to predict how a drug will work in humans could allow the company to avoid animal testing altogether.
Bell said computers can be a powerful tool in early drug design. But he added that this research is quickly reverting to traditional testing of a molecule’s pharmacokinetics and pharmacodynamics – what the drug does to the body and what the body does to the drug. This requires animal testing, he said. Kuznetsov sees limits to what computers can achieve. The tests most predictive of how a candidate drug will work in a patient are those performed on a living mammal, not in a computer simulation, he said.
“Philosophically, we believe the best testing environment is reality,” Kuznetsov said.