Multivariate analysis for optimization and validation of the industrial tablet-manufacturing process

This study aimed initially to optimize the industrial tablet-manufacturing process using multivariate analysis, and then to validate the model obtained. The study also provides a comprehensive review of the influence of different factors on relevant biopharmaceutical parameters.

This is the first time multivariate analysis has been applied to such a broad set of industrial data to investigate the influence of starting materials and the tablet-manufacturing processes on drug dissolution.

Partial least squares regression was retrospectively applied to the data obtained from 2 years production, to study the influence of 90 factors on dissolution of tablets that contained two active pharmaceutical ingredients. The model established was verified using the worst-case approach and process validation.

Croscarmellose sodium had the most significant influence on drug dissolution, with the next significant factors as sodium chloride and sodium glycolate content, settling volume, particle size, suspension pH, loss on drying, and maximum temperature during drying. Loss on drying of microcrystalline cellulose and specific surface area of magnesium stearate were also essential factors. Among the process parameters, auger speed during roller compaction, compression speed, and force feeder speed during tablet compression had significant impacts on the tablet dissolution rate. The multivariate model created satisfied the process validation.

This multivariate analysis is a useful tool to predict and optimize critical material attributes and process parameters. The variability of the materials can be successfully compensated for using various process parameters, to ensure consistent approved drug quality, to thus provide better patient care.