A risk-based statistical investigation of the quantification of polymorphic purity of a pharmaceutical candidate by solid-state 19F NMR.

The DMAIC (Define, Measure, Analyse, Improve and Control) framework and associated statistical tools have been applied to both identify and reduce variability observed in a quantitative (19)F solid-state NMR (SSNMR) analytical method. The method had been developed to quantify levels of an additional polymorph (Form 3) in batches of an active pharmaceutical ingredient (API), where Form 1 is the predominant polymorph. In order to validate analyses of the polymorphic form, a single batch of API was used as a standard each time the method was used. The level of Form 3 in this standard was observed to gradually increase over time, the effect not being immediately apparent due to method variability. In order to determine the cause of this unexpected increase and to reduce method variability, a risk-based statistical investigation was performed to identify potential factors which could be responsible for these effects. Factors identified by the risk assessment were investigated using a series of designed experiments to gain a greater understanding of the method. The increase of the level of Form 3 in the standard was primarily found to correlate with the number of repeat analyses, an effect not previously reported in SSNMR literature. Differences in data processing (phasing and linewidth) were found to be responsible for the variability in the method. After implementing corrective actions the variability was reduced such that the level of Form 3 was within an acceptable range of ±1% ww(-1) in fresh samples of API.

Detection of low-level PTFE contamination: An application of solid-state NMR to structure elucidation in the pharmaceutical industry.

We report a novel use of solid-state ¹9F nuclear magnetic resonance to detect and quantify polytetrafluoroethylene contamination from laboratory equipment, which due to low quantity (up to 1% w/w) and insolubility remained undetected by standard analytical techniques. Solid-state ¹9F NMR is shown to be highly sensitive to such fluoropolymers (detection limit 0.02% w/w), and is demonstrated as a useful analytical tool for structure elucidation of unknown solid materials.

Analysis of amorphous solid dispersions using 2D solid-state NMR and (1)H T(1) relaxation measurements.

Solid-state NMR (SSNMR) can provide detailed structural information about amorphous solid dispersions of pharmaceutical small molecules. In this study, the ability of SSNMR experiments based on dipolar correlation, spin diffusion, and relaxation measurements to characterize the structure of solid dispersions is explored. Observation of spin diffusion effects using the 2D (1)H-(13)C cross-polarization heteronuclear correlation (CP-HETCOR) experiment is shown to be a useful probe of association between the amorphous drug and polymer that is capable of directly proving glass solution formation. Dispersions of acetaminophen and indomethacin in different polymers are examined using this approach, as well as (1)H double-quantum correlation experiments to probe additional structural features. (1)H-(19)F CP-HETCOR serves a similar role for fluorinated drug molecules such as diflunisal in dispersions, providing a rapid means to prove the formation of a glass solution. Phase separation is detected using (13)C, (19)F, and (23)Na-detected (1)H T(1) experiments in crystalline and amorphous solid dispersions that contain small domains. (1)H T(1) measurements of amorphous nanosuspensions of trehalose and dextran illustrate the ability of SSNMR to detect domain size effects in dispersions that are not glass solutions via spin diffusion effects. Two previously unreported amorphous solid dispersions involving up to three components and containing voriconazole and telithromycin are analyzed using these experiments to demonstrate the general applicability of the approach.