We’re at the dawn of a new era in discovering transformative medicines. At Psivant Therapeutics, we believe that the future of drug discovery hinges on the integration of leading-edge predictive science with excellence in experimental approaches.
Our capabilities are driven by our industry-leading QUAISAR computational platform, which combines preeminent physics-based simulation tools with machine learning to generate unprecedented predictive power that can tackle previously intractable challenges. The tight integration of the QUAISAR platform with our broad experimental capabilities and deep drug discovery experience enables the rapid design and optimization of new drugs to address a wide range of targets for diseases with high unmet need.
Psivant’s name and logo originate from the penultimate Greek letter ᴪ (spelled Psi and pronounced “sī”), which represents the wave function in quantum physics. Psi fully describes matter at the atomic level. The conceptual and mathematical underpinnings of the wave function revolutionized our understanding of the physical world. Psi is the foundation for how we design better drugs at Psivant, atom by atom. Watch “A Better Way To Picture Atoms” on YouTube to learn more about Psi.
Designing Better Medicines: Atom-by-Atom
Psivant tackles today’s vast chemical space and challenging disease targets with our proprietary quantum physics-based simulations, bespoke AI/ML methods, in-house high-performance supercomputing and advanced biophysical methods to perform accurate, all-atom, highly predictive simulations at scale.
By combining computational breakthroughs with project-specific experimental data, our integrated team of chemists, biologists, physicists, biophysicists, computational scientists, software engineers and parallel computing can produce the most accurate three-dimensional dynamic atomistic model simulations to break through historical bottlenecks that have prevented the effective discovery of therapeutics.
We believe our end-to-end expertise, spanning the critical dimensions of both computation and lab-based experiments, will lead to the rapid design and discovery of new medicines that will improve the lives of patients.