Pioneering Design of Resistance-Resilient Drugs
Adding a New Dimension to Drug Design
Gavilán Biodesign combines state of the art physics-based modeling with our unique high accuracy AI platform to computationally screen trillions of molecules in order to find therapeutics that can overcome resistance. Gavilán is the first to add the dimension of evolution and time in our screens! We do this through our proprietary design software suite called Sylph that can design both biologics and small molecules for specificity and resistance resilience.
Our algorithms are based on rigorous mathematical guarantees allowing us to make confident predictions about our chemical space and continuously improve our predictions through improvements to our entropy-aware, continuously flexible, high accuracy biophysical models that are already the most sophisticated models of their kind for combinatorial drug design.
Up top, we see a video of PRIARM, our proprietary technology to predict and overcome resistance. You can see the gameplay between drug optimization and exploration of resistance mutations. The results are therapeutics: biologics or small molecules that are resilient to resistance mutations.
About Us
Explore Beyond, Leave Nothing Unseen
Gavilán Biodesign uses its proprietary computational chemistry approach to develop novel antineoplastic therapeutics that are resilient to the emergence of drug resistance. The ability of cancer to develop resistance to therapeutics is the number one contributing force to mortality. Gavilan is building on the success of the OSPREY software package developed in the Donald lab at Duke University, expanding it to not only predict but also design new molecules capable of overcoming drug resistance.
On the left, we can see our proprietary scaffold redesign and hopping technology SOCCER. SOCCER generates scaffold diversity while maintaining important interactions and avoiding clashes with the binding pocket or interface.
Our Science
Gavilán is a results-oriented company that believes that accuracy of predictions is paramount. Therefore, Gavilán utilizes state-of-the-art algorithms that are guaranteed to find the best results within our chemical space despite our screens routinely having trillions of molecules. Nothing is left unseen: our algorithms guarantee no good compound is left behind and no resistance mutation gets through. As our accuracy is only limited by our physical models, Gavilán builds the most sophisticated models of any group performing combinatorial computational chemistry by taking into account entropy and continuous flexibility. Above, you can see how our unique continuous flexibility can accurately distinguish a good VdW interaction from a clash.
Resistance Prediction
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A collaboration between the Donald lab at Duke and labs at the University of Connecticut used our technology to show for the first time that antibiotic resistance could be prospectively predicted.
A study from the Institute of Cancer Research in London used our technology to show prospective prediction of resistance to osimertinib.
Antibody Redesign
A collaboration between the Donald lab at Duke and the Vaccine Research Center, the Donald lab used our technology to redesign VRC07 to become more potent and broad by resisting HIV resistance mutations. The antibody is currently is multiple phase 1 and phase 2 clinical trials.
We Can Help
At Gavilán we are passionate about making better drugs. Let our team help you design more potent, specific and resistance-resilient drugs.
Structure-to-Lead
Let us help you develop PPI inhibitors from a crystal structure of your target bound to an endogenous ligand.
Hit-to-Lead
Let us help you improve your therapeutics--be they biologics or small molecules--for affinity, specificity, and resilience to resistance!
Our Team
Partners
Duke University
IndieBio
