In the years after structure prediction stopped being an open problem, two things changed. The first was philosophical: protein form, dynamics, and interaction had become objects you could predict, not just measure. The second was practical: the cost of generating, modelling, and learning from biological data fell faster than almost any other input in drug discovery.
That created an opportunity to build a different kind of biotech — one whose first asset is not a single molecule, but a platform for designing many of them. We founded Rylivo to take that opportunity seriously, and to do so at the pace patients deserve.
Where we're headed
The platform is the product, but the patients are the point. Over the next several years we will continue to deepen the foundations of our models, expand our wet-lab capabilities, and advance an internal portfolio of programs. We will partner where partners make us faster — and we will publish what we can to keep the field honest.