XtalPi was established in 2015 when it developed its first solid state R&D platform. The company’s founding mission was to provide crystal structure prediction for polymorph derisking of pharmaceutical compounds but had parallel efforts in experimental screening for discovery.
Since then, XtalPi have developed their capabilities in experimental screening including polymorph salt screening, and structure determination methods like CryoEM and MicroED. On top of this, the company offers a range of computational services and have recently introduced a range of automated experimental workstations, part of their XtalGazer platform.
XtalGazer is designed to address the issue of polymorphism using high quality screening while at the same time mitigating the risks associated with polymorph transformation. The goal is to use a data-driven methodology to shift away from the traditional trial-and-error approaches.
The platform’s workflow combines automated experimental screening with AI and physics-based models. Experimental screening starts with a powder sample of the compound while the computational side only requires its molecular structure.
First, a solubility assessment is performed to determine whether to develop a co-crystal or salt, which can be done using XtalPi’s AI-based virtual counterion screening. Then experimental polymorph screening is conducted using the Xtal2 platform which is enabled by XtalPi’s automated experimental workstations.
Once the screening is complete, the experimental forms can be characterised using single crystal X-ray diffraction or MicroED depending on crystal size. In parallel, crystal structure prediction is used to obtain the polymorphs in an effort to derisk the experimental forms. This forms a feedback loop to ensure that the most thermodynamically stable form possible is acquired.
This presentation highlights the XtalGazer platform, its technology, along with case studies to demonstrate how it can be used to impact real projects. Bellucci outlines a rapid study on remdesivir, demonstrating the platform's capability to de-risk a compound effectively during the COVID-19 pandemic. Furthermore, Bellucci demonstrates how, collaborating with Merck, the platform successfully predicted the effects of polymer additives on crystal morphology, showcasing its practical applications.
