For solid-state R&D of small molecule drugs, the XtalPi solution integrates several state-of-the-art technologies for crystal structure prediction, crystal structure determination, virtual screening of salts and cocrystals, as well as an advanced solid-state R&D experimental platform. The company is dedicated to creating the next-generation platform for solid-state R&D for small molecules by combining experimental screening and characterization with theoretical calculations and analyses, and providing novel solutions for the solid-state R&D. At XtalPi, we help our clients improve the quality and efficiency of solid-state R&D and reduce R&D risks and costs.
XtalPi offers accurate prediction of the relative thermodynamic stabilities of different crystal structures through large-scale virtual crystal structure generation and high-precision energy calculation.
XtalPi performs experimental solid-state screening, crystallization process scale-up, and systematic characterization of crystal forms with desired properties, making recommendations to customers based on systematic assessments.
XtalPi's solid-state research and development platform combines experimental data and theoretical analyses to determine the crystal structures of solid forms reliably.
XtalPi uses a wide range of experimental techniques for the characterization of pharmaceutical solid forms, such as XRD, TGA, DSC, DVS, and HSM.
Combining AI and computational chemistry, XtalPi developed a series of innovative methods to address challenging drug discovery and design tasks, including molecular structure generation, bioavailability prediction, and drug property predictions. Based on these AI-empowered capabilities, XtalPi collaborates with its industry partners in small-molecule drug design to further expedite early-stage pharmaceutical R&D, improve research efficiency, reduce costs, and increase the overall success rate of drug discovery.
XtalPi combines AI, quantum mechanics, and cloud computing to develop a variety of intelligent digital drug design solutions for hit identification, hit to lead/lead generation, and lead optimization.
XtalPi combines CADD and AI in antibody research and development to accelerate the R&D process, increase the success rate, and reduce the costs.
XtalPi offers cloud-based AI services and solutions that empower therapeutic research and help pharmaceutical companies address the many challenges in drug discovery. Built upon its ability to deploy and schedule massive amount of cloud computing resources and its expertise in deep learning algorithms, XtalPi enables deep mining of drug R&D databases to provide powerful tools that can increase the efficiency and success rate of pharmaceutical research.
XtalPi team shares the timeline and preliminary results on their research of the new coronavirus.
Combining AI Algorithms with Targeted Experiments to Solve Bottleneck Challenges in Drug Development
Case study on how XtalPi is helping pfizer scientists predict and optimize the crystalline forms of drug candidates.