Powder mixing in continuous manufacturing: understanding of mixture properties, mixing dynamics and homogeneity
Creators: name: Tao, Yi
Publisher: name: No Publisher Supplied
Year: 2024

description: Continuous manufacturing of pharmaceutical oral-dose drug products has seen substantial progress over the last two decades, driven by collaborations among academic institutions, industries, and regulatory agencies. Advancements in the design of new equipment and integrated processes, along with the implementation and integration of process analytical technology with process control, and the incorporation of digitalization, have facilitated enhancements in process efficiency, improved product quality, and increased process understanding. The work in this dissertation provides deep understanding of powder mixing in continuous pharmaceutical manufacturing using multivariate analysis tools and mathematical models, which can be applied to process and formulation development with material sparing approach. It is also highlighted that the accomplishment of the work can provide new insights for manufacturing tablets without using a blender, which could significantly reduce the cost of manufacturing. In this work, mixture models were developed to predict mixture properties from ingredients. Two methods were proposed: Particle Least Squared method and mixing-rule-based method. Non-linear relationships between mixture properties and compositions were revealed, and packing mechanism with different size ratio category can provide theoretical explanation. It was found out that the Partial Least Squares (PLS) method is suitable for properties with roughly linear relations, and the mixing-rule-based method can capture non-linearities with minimal experimental effort. The second aim focuses on the powder characterization and process development in feeding-blending system and demonstrates the suitability of a continuous manufacturing route for micronized and granular drug products. Due to scarcity and potency of the API, a surrogate that has similar bulk properties to the API’s was selected based on statistical analysis of the Rutgers material database. Importantly, for the continuous blender, process parameters such as blender speed and throughput were varied to characterize mixing behavior for six cohesive blends, that each contained different grades of excipients, and one granular blend. The residence time distribution (RTD) of the material in the continuous blender was performed using a pulse of a second surrogate, which was similar to the API and easily detectible by spectroscopic methods and characterizing the profile of the material as it exited the blender. Multivariate analysis was used to analyze the relationships between process parameters, mixture properties and mixing performances. By performing each of these steps, operators were able to identify the suitability and characteristics of blends based on the performances in the unit operations.The third aim works on expansion of standardized methods for characterizing RTD by assessing tracer materials and quantities effect on RTD of a continuous manufacturing line. Statistical method such as analysis of variance and multivariate analysis of variance were utilized to test the statistical significance across different tracers and masses. This work facilitates broader selection criteria for tracers in RTD studies and also demonstrates the mixing ability of the feed frame to disperse the disruptions caused by the tracer. Along with the findings, the fourth aim was inspired to investigate the necessity of using a physical blender to manufacture drug products. Three mixing scenarios were evaluated and compared including batch mixing, continuous mixing, and feed frame mixing only. It was exciting to find that, for an easy-flowing high-dose formulation, blending solely within feed frame can achieve excellent blend homogeneity. Additionally, harder tablet properties can be acquired compared to the conventional manufacturing approach, which offers a lower-shear alternative for manufacturing shear-sensitive formulations. The findings from this work, a potential “no blender” manufacturing route, can reduce significant amount of time for pharmaceutical product development and costs for manufacturing.