Unraveling the Mystery of Axitinib's Crystal Structure: A Breakthrough in Pharmaceutical Research
The quest for a reliable crystal structure prediction method has finally borne fruit, and it's set to revolutionize the world of organic materials.
Gregory Beran, a researcher at the University of California Riverside, has developed a strategy that combines hybrid density functional theory modeling with intramolecular energy correction. This innovative approach has successfully predicted the intricate crystal structures of axitinib, a targeted anti-cancer drug, and distinguished between salt and co-crystals in multi-component crystals.
Axitinib, a tyrosine kinase inhibitor, has been a challenging compound to develop due to its polymorphism, the ability to crystallize in multiple forms. With five known non-solvated crystalline structures, each with unique properties affecting solubility and bioavailability, the selection of the most suitable form for development has been a complex journey.
"It's a story of chemists having to rethink their choices twice," Beran explains. "Crystal structure prediction could have prevented these setbacks."
Beran's method has produced remarkable results. By optimizing known crystal structures and predicting new ones, he has aligned his predictions closely with experimental data. He has also successfully predicted the most thermodynamically stable form, form XLI, which received FDA approval in 2012.
"The study offers a potential roadmap for predicting whether two molecules will crystallize as a salt or co-crystal," says Sarah Price, a theoretical chemist at University College London. "It opens up a whole new realm of experimental possibilities to explore through computer modeling."
But here's where it gets controversial: Beran's approach, while groundbreaking, is not without its challenges. Density-driven delocalization errors in many systems can lead to incorrect predictions of salt formation. However, by combining density functional theory with intramolecular energy correction, these issues can be addressed.
And this is the part most people miss: Beran's work has implications beyond axitinib. It paves the way for a more efficient and accurate development process for other pharmaceutical compounds, potentially saving time, resources, and, most importantly, lives.
"Crystal structure prediction is not yet perfect," Beran acknowledges. "But it's a powerful tool that can significantly impact what we can achieve in pharmaceutical research."
What do you think? Is this a game-changer for the industry? Share your thoughts in the comments!
