Can computed crystal energy landscapes help understand pharmaceutical solids?

Area of Science:

• Solid-state chemistry
• Computational materials science
• Pharmaceutical development

Background:

• Computational crystal structure prediction (CSP) is increasingly applicable to smaller pharmaceutical molecules.
• Understanding solid forms is critical for drug development and formulation.

Purpose of the Study:

• To review the application of computed crystal energy landscapes for pharmaceuticals.
• To highlight the synergy between computational methods and experimental solid form screening.

Main Methods:

• Review of recent literature on computed crystal energy landscapes for drug molecules.
• Case studies of collaboration between computational prediction and industrial experimental screening.

Main Results:

• Computed energy landscapes complement experimental screening in identifying practical solid forms.
• Computational methods enhance the understanding of the solid form landscape for pharmaceuticals.

Conclusions:

• The integration of computational crystal structure prediction and experimental screening is a powerful approach for pharmaceutical solid form discovery.
• This combined strategy aids in characterizing important solid forms and elucidating the complexity of the solid-state landscape.