Comparison of Univariate and Multivariate Models of 13C SSNMR and XRPD Techniques for Quantification of Nimodipine Polymorphs

Abstract

Abstract. The focus of the present investigation was to explore the use of solid-state nuclear magnetic resonance ( 13 C ssNMR) and X-ray powder diffraction (XRPD) for quantification of nimodipine polymorphs (form I and form II) crystallized in a cosolvent formulation. The cosolvent formulation composed of polyethylene glycol 400, glycerin, water, and 2.5% drug, and was stored at 5°C for the drug crystallization. The 13 C ssNMR and XRPD data of the sample matrices containing varying percentages of nimodipine form I and form II were collected. Univariate and multivariate models were developed using the data. Least square method was used for the univariate model generation. Partial least square and principle component regressions were used for the multivariate models development. The univariate models of the 13 C ssNMR were better than the XRPD as indicated by statistical parameters such as correlation coefficient, R 2 , root mean square error, and standard error. On the other hand, the XRPD multivariate models were better than the 13 C ssNMR as indicated by precision and accuracy parameters. Similar values were predicted by the univariate and multivariate models for independent samples. In conclusion, the univariate and multivariate models of 13 C ssNMR and XRPD can be used to quantitate nimodipine polymorphs.

A Novel Rheological Method to Assess Drug-Polymer Interactions Regarding Miscibility and Crystallization of Drug in Amorphous Solid Dispersions for Oral Drug Delivery

“…Despite the common use of XRPD and DSC to detect crystalline drug [69], one should keep in mind the analytical limitations. DSC temperature ramps may cause recrystallization of amorphous materials or, alternatively, increased temperature may lead to dissolution of crystalline drug in the polymer matrix, so the result may not necessarily reflect otherwise isothermal stability conditions over time [69,70]. In addition, the presence of excipients can introduce further limitations in the detection of the thermal behavior of the API due to overlapping signals [71,72].…”

“…In addition, the presence of excipients can introduce further limitations in the detection of the thermal behavior of the API due to overlapping signals [71,72]. On the other hand, XRPD has limitations concerning preferred crystal orientation due to morphology and/or processing parameters such as compression [69,73], and overall sensitivity of common laboratory equipment does not match the sensitivity in detecting crystalline material by using a synchrotron radiation. Despite these limitations, XRPD and DSC are still widely used to monitor amorphous formulations, as the analytical sensitivity is often good enough for most practical purposes and because of their simplicity in acquiring and interpreting data.…”

Quantifying API polymorphs in formulations using X-ray powder diffraction and multivariate standard addition method combined with net analyte signal analysis

“…M A N U S C R I P T 4 2008) requires the full sample composition to be known, and its accuracy is adversely influenced by the amorphous fraction; when univariate calibration is attempted (Rahman et al, 2015), the analyst must choose one specific diffraction angle to measure the response (peak-area or peak-height): at least one specific diffraction angle is required (no interfering species). Even when specific angles are available, the effect of the matrix on the signal should be controlled: this is not easy when polymorphic and amorphous forms are involved.…”