De-risking Pharmaceutical Tablet Manufacture Through Process Understanding, Latent Variable Modeling, and Optimization Technologies

• Published in: AAPS PharmSciTech Vol. 12; no. 4; pp. 1324 - 1334
• Main Authors: Muteki, Koji, Swaminathan, Vidya, Sekulic, Sonja S., Reid, George L.
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.12.2011
• Subjects: Biochemistry; Biomedical and Life Sciences; Biomedicine; Biotechnology; Chemistry, Pharmaceutical; Computer Simulation; Drug Compounding; Hardness; Indexing in process; Kinetics; Least-Squares Analysis; Models, Chemical; Pharmaceutical Preparations - chemistry; Pharmaceutical Preparations - standards; Pharmacology/Toxicology; Pharmacy; Quality Control; Research Article; Solubility; Tablets; Technology, Pharmaceutical - methods; Technology, Pharmaceutical - standards; latent variable modeling; quality by design; process optimization; partial least squares; design space
• ISSN: 1530-9932; 1530-9932
• DOI: 10.1208/s12249-011-9700-4

In pharmaceutical tablet manufacturing processes, a major source of disturbance affecting drug product quality is the (lot-to-lot) variability of the incoming raw materials. A novel modeling and process optimization strategy that compensates for raw material variability is presented. The approach involves building partial least squares models that combine raw material attributes and tablet process parameters and relate these to final tablet attributes. The resulting models are used in an optimization framework to then find optimal process parameters which can satisfy all the desired requirements for the final tablet attributes, subject to the incoming raw material lots. In order to de-risk the potential (lot-to-lot) variability of raw materials on the drug product quality, the effect of raw material lot variability on the final tablet attributes was investigated using a raw material database containing a large number of lots. In this way, the raw material variability, optimal process parameter space and tablet attributes are correlated with each other and offer the opportunity of simulating a variety of changes in silico without actually performing experiments. The connectivity obtained between the three sources of variability (materials, parameters, attributes) can be considered a design space consistent with Quality by Design principles, which is defined by the ICH-Q8 guidance (USDA 2006 ). The effectiveness of the methodologies is illustrated through a common industrial tablet manufacturing case study.