Identifying aspirin polymorphs from combined DFT‐based crystal structure prediction and solid‐state NMR. (21st January 2020) - Mathew, Renny; Uchman, Karolina A.; Gkoura, Lydia; Pickard, Chris J.; Baias, Maria
Abstract: A combined experimental and computational approach was used to distinguish between different polymorphs of the pharmaceutical drug aspirin. This method involves the use of ab initio random structure searching (AIRSS), a density functional theory (DFT)‐based crystal structure prediction method for the high‐accuracy prediction of polymorphic structures, with DFT calculations of nuclear magnetic resonance (NMR) parameters and solid‐state NMR experiments at natural abundance. AIRSS was used to predict the crystal structures of form‐I and form‐II of aspirin. The root‐mean‐square deviation between experimental and calculated 1 H chemical shifts was used to identify form‐I as the polymorph present in the experimental sample, the selection being successful despite the large similarities between the molecular environments in the crystals of the two polymorphs. Abstract : The bioavailability of pharmaceuticals is highly correlated to their crystal structures, and one drug can have many possible crystal forms called polymorphs. Solid‐state nuclear magnetic resonance (NMR) combined with computational crystal structure prediction and density functional theory calculation of NMR chemical shifts was used to distinguish between very similar polymorphs of aspirin and to identify the polymorph present in the experimental sample.