High-throughput blend segregation evaluation using automated powder dispensing technology.

Due to the complexity in the interactions of variables and mechanisms leading to blend segregation, quantifying the segregation propensity of an Active Pharmaceutical Ingredient (API) has been challenging. A high-throughput segregation risk prediction workflow for early drug product development has been developed based on the dispensing mechanism of automated powder dispensing technology. The workflow utilized liquid handling robots and high-performance liquid chromatography (HPLC) with a well-plate autosampler for sample preparation and analysis. Blends containing three different APIs of varying concentrations and particle sizes of different constituents were evaluated through this automated workflow. The workflow enabled segregation evaluation of different API blends in very small quantities (~7g) compared to other common segregation testers that consume hundreds of grams. Segregation patterns obtained were well explained with vibration induced percolation-based segregation phenomena. Segregation risk was translated quantitatively using relative standard deviation (RSD) calculations, and the results matched well with large-scale segregation studies. The applied approach increased the throughput, introduced a simple and clean walk-up method with minimized equipment space and API exposures to conduct segregation studies. Results obtained can provide insights about optimizing particle size distributions, as well as selecting appropriate formulation constituents and secondary processing steps in early drug product development when the amount of available API is very limited.