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35Cl solid-state NMR of HCl salts of active pharmaceutical ingredients: structural prediction, spectral fingerprinting and polymorph recognition†
Marcel Hildebrand,Hiyam Hamaed,Andrew M. Namespetra,John M. Donohue,Riqiang Fu,Ivan Hung,Zhehong Gan,Robert W. Schurko
CRYSTENGCOMMCRYSTENGCOMM Pub Date : , DOI:10.1039/C4CE00544A
Abstract

A series of HCl salts of active pharmaceutical ingredients (APIs) have been characterized via35Cl solid-state NMR (SSNMR) spectroscopy and first-principles plane-wave density functional theory (DFT) calculations of 35Cl NMR interaction tensors. 35Cl NMR spectra have been acquired at both standard (9.4 T) and high (21.1 T) magnetic field strengths, on stationary samples and under conditions of magic-angle spinning (MAS). The 35Cl electric field gradient (EFG) and chemical shift (CS) tensor parameters are readily extracted from analytical simulations of these spectra. These parameters are distinct for each sample, indicating that these spectra can be used as fingerprints for identifying unique solid phases. It is possible to correlate the 35Cl EFG parameters (the quadrupolar coupling constant, CQ, and the asymmetry parameter, ηQ) to the hydrogen-bonding environments of each chlorine anion, and several simple trends are observed. 35Cl EFG tensors obtained from plane-wave DFT calculations are found to be in good agreement with experiment, and unique structural insights are gained by considering the predicted EFG tensor orientations and the signs of the quadrupolar coupling constants. 35Cl SSNMR can be easily applied for the differentiation of polymorphs of HCl APIs, since the spectra are sensitive to even the subtlest changes in the chlorine anion environments. We discuss the application of this combination of techniques as both standalone and complementary NMR crystallography methodologies for structural characterization and potential high-throughput screening of polymorphs of HCl APIs.

Graphical abstract: 35Cl solid-state NMR of HCl salts of active pharmaceutical ingredients: structural prediction, spectral fingerprinting and polymorph recognition
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