Abstract
Context: Content uniformity (CU) is a critical quality attribute measured and monitored throughout the development and commercial supply of pharmaceutical products. Traditional high-performance liquid chromatography (HPLC) methods are time-consuming in both sample preparation and analysis. Thus, a rapid, nondestructive and preparation free spectroscopy based method such as Raman is preferred.
Objective: Multiple mathematical algorithms were used to establish robust and directly correlated Raman and ultra-HPLC-mass spectrometry (uHPLC-MS) CU methods for the rapid analysis of blends and agglomerates formulated for dry powder inhalers (DPIs).
Materials and Methods: Model samples included blends of caffeine and lactose; albuterol and lactose; and albuterol and lactose agglomerates. Design of experiments (DoE) was employed to optimize Raman spectra. Multivariate curve resolution (MCR) was leveraged to assess Raman method robustness. Mathematical modeling provided direct method to method correlation by allowing samples to be scanned first for Raman spectra and then dissolved for uHPLC-MS analysis. Several chemometric models were developed and evaluated for the quantitative analysis of CU.
Results: The DoE revealed Raman power and exposure time were negatively correlated when optimizing albuterol and caffeine spectra but positively correlated for lactose. MCR revealed regions in which small changes to power and time resulted in an 8–10% change in concentration predictions. A PCR model worked well for the analysis of caffeine blend samples and a PLS model worked best for both albuterol blends and agglomerates.
Discussion and Conclusion: Utilization of DoE, chemometrics and mathematical modeling provided a robust and directly correlated CU method for DPIs.
Disclosure statement
The authors report no declarations of interest.