Using a Material Library to Understand the Impacts of Raw Material Properties on Ribbon Quality in Roll Compaction

• Published in: Pharmaceutics Vol. 11; no. 12; p. 662
• Main Authors: Yu, Jiaqi, Xu, Bing, Zhang, Kunfeng, Shi, Chenfeng, Zhang, Zhiqiang, Fu, Jing, Qiao, Yanjiang
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 07.12.2019; MDPI
• Subjects: Calcium phosphates; Cellulose; Density; Hydraulics; Lactose; Libraries; Lignin; Pharmaceuticals; Physical properties; Polyvinyl alcohol; Process controls; Sodium; Tensile strength; Beijing China; China; ribbon quality; latent variable modeling; roll compaction; material library; design space; roll compaction behavior classification system (RCBCS)
• ISSN: 1999-4923; 1999-4923
• DOI: 10.3390/pharmaceutics11120662

The purpose of this study is to use a material library to investigate the effect of raw material properties on ribbon tensile strength (TS) and solid fraction (SF) in the roll compaction (RC) process. A total of 81 pharmaceutical materials, including 53 excipients and 28 natural product powders (NPPs), were characterized by 22 material descriptors and were compacted under five different hydraulic pressures. The transversal and longitudinal splitting behaviors of the ribbons were summarized. The TS-porosity and TS-pressure relationships were used to explain the roll compaction behavior of powdered materials. Through defining the target ribbon quality (i.e., 0.6 ≤ SF ≤ 0.8 and TS ≥ 1 MPa), the roll compaction behavior classification system (RCBCS) was built and 81 materials were classified into three categories. A total of 24 excipients and five NPPs were classified as Category I materials, which fulfilled the target ribbon quality and had less occurrence of transversal splitting. Moreover, the multivariate relationships between raw material descriptors, the hydraulic pressure and ribbon quality attributes were obtained by PLS regression. Four density-related material descriptors and the cohesion index were identified as critical material attributes (CMAs). The multi-objective design space summarizing the feasible material properties and operational region for the RC process were visualized. The RCBCS presented in this paper enables a formulator to perform the initial risk assessment of any new materials, and the data modeling method helps to predict the impact of formulation ingredients on strength and porosity of compacts.