Insight into the Formation of Cocrystal and Salt of Tenoxicam from the Isomer and Conformation.

Tenoxicam (TNX) is a new non-steroidal anti-inflammatory drug that shows a superior anti-inflammatory effect and has the advantages of a long half-life period, a fast onset of action, a small dose, complete metabolism, and good tolerance. Some compounds often have tautomerism, and different tautomers exist in different crystalline forms. TNX is such a compound and has three tautomers. TNX always exists as the zwitterionic form in cocrystals. When the salt is formed, TNX exists in the enol form, which exhibits two conformations depending on whether a proton is gained or lost. Currently, the crystal structure of the keto form is not in the Cambridge Structural Database (CSD). Based on the analysis of existing crystal structures, we derived a simple rule for what form of TNX exists according to the pKa value of the cocrystal coformer (CCF) and carried out validation tests using three CCFs with different pKa values, including p-aminosalicylic acid (PAS), 3,5-dinitrobenzoic acid (DNB), and 2,6-dihydroxybenzoic acid (DHB). The molecular surface electrostatic potential (MEPS) was combined with the pKa rule to predict the interaction sites. Finally, two new cocrystals (TNX-PAS and TNX-DNB) and one salt (TNX-DHB) of TNX were obtained as expected. The differences between the cocrystals and salt were distinguished by X-ray diffraction, vibration spectra, thermal analysis, and dissolution measurements. To further understand the intermolecular interactions in these cocrystals and salt, the lattice energy and energy decomposition analysis (EDA) were used to explain them from the perspective of energy. The results suggest that the melting point of the CCF determines that of the cocrystal or salt, the solubility of the CCF itself plays an important role, and the improvement of the solubility after salt formation is not necessarily better than that of API or its cocrystals.

Progress in Research on Artificial Intelligence Applied to Polymorphism and Cocrystal Prediction.

Artificial intelligence (AI) is a technology that builds an artificial system with certain intelligence and uses computer software and hardware to simulate intelligent human behavior. When combined with drug research and development, AI can considerably shorten this cycle, improve research efficiency, and minimize costs. The use of machine learning to discover novel materials and predict material properties has become a new research direction. On the basis of the current status of worldwide research on the combination of AI and crystal form and cocrystal, this mini-review analyzes and explores the application of AI in polymorphism prediction, crystal structure analysis, crystal property prediction, cocrystal former (CCF) screening, cocrystal composition prediction, and cocrystal formation prediction. This study provides insights into the future applications of AI in related fields.