How crystal structure prediction can impact small-molecule pharmaceutical development: past examples, success stories, and future prospects
Luca Iuzzolino

TL;DR
Crystal structure prediction helps avoid pharmaceutical problems by identifying stable molecule forms before they cause issues in drug development.
Contribution
The paper highlights how computational methods can predict crystal forms more effectively than experiments, reducing risks in drug development.
Findings
Crystal structure prediction can identify more stable forms of molecules before they appear experimentally.
Unexpected crystal forms can have detrimental effects on drug development and patient safety.
Computational methods overcome experimental limitations like material availability and kinetic constraints.
Abstract
The impact of crystal structure prediction on the development of small-molecule pharmaceutical products cannot be overstated. The choice of a thermodynamically metastable crystal structure as the lead development form, and the unexpected appearance of a lower energy phase, can have extremely detrimental consequences for patients, as well as negative financial and reputational impacts on pharmaceutical companies. Therefore, any technique that can minimize the risk of such an event occurring is extremely valuable. The power of computational crystal structure prediction comes from its ability to explore the crystal form landscape of a molecule without the limitations in terms of material availability, kinetic constraints, and characterization difficulties that experimental screens suffer from. Therefore, they can predict the existence of more thermodynamically stable crystalline forms…
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Taxonomy
TopicsComputational Drug Discovery Methods
