A hybrid NIR-soft sensor method for real time in-process control during continuous direct compression manufacturing operations

• Published in: International journal of pharmaceutics 2021-06, Vol.602, p.120620-120620, Article 120620
• Main Authors: Cogoni, Giuseppe, Liu, Yang Angela, Husain, Anas, Alam, Md Anik, Kamyar, Reza
• Format: Article
• Language: English
• Subjects: Continuous pharmaceutical manufacturing; Hybrid modeling; In-process control; NIR; PAT; Soft sensor
• ISSN: 0378-5173; 1873-3476
• DOI: 10.1016/j.ijpharm.2021.120620

[Display omitted] •A hybrid quantitative method combining a PLS and a Soft Sensor potency estimation.•Implemented and applied on continuous direct compression manufacturing.•Improved overall estimation robustness and facilitates cross-site method transfer. Near Infrared (NIR) spectroscopy is commonly utilized for continuous manufacturing as Process Analytical Technology (PAT) tool. This paper focus on a continuous direct compression manufacturing process, in which an NIR PAT probe is integrated into the tablet press feed frame and into the tablet diversion control system to ensure continuous monitoring of the potency and homogeneity of the blend within the process line. The quantification of NIR spectra is achieved through Partial Least-Squares (PLS) modeling, calibrated with offline analyzed tablet cores at different potency levels. Because the NIR measurements are often sensitive to sample physical properties caused by raw materials or process conditions, etc., adopting a data-driven approach will require a large amount of representative data throughout the method lifecycle. During the early stages of process development, whenever new uncaptured source of variability in the model space are encountered, the chemometric predictions can deviate from the offline reference, requiring frequent model updates. These deviations can be reduced by integrating process and physico-chemical knowledge in the on-line potency estimation. This paper presents a novel hybrid method combining the online NIR PLS and a potency soft sensor estimation, enabling a robust potency prediction whilst minimizing maintenance downtimes and facilitating cross-site method transfer.