(404f) Real Time Process Management in a Continuous Pharmaceutical Manufacturing Process | AIChE

(404f) Real Time Process Management in a Continuous Pharmaceutical Manufacturing Process


Gupta, A. - Presenter, Purdue University
Austin, J. S. III, Purdue University
Nagy, Z. K., Purdue University
Reklaitis, G. V., Purdue University

The pharmaceutical industry has traditionally been batch-manufacturing industry but with the advent of Process Analytical Technology (PAT) by FDA, the industry has moved towards continuous manufacturing. The FDA is currently in process of implementing Quality by Design (QbD). Successful implementation of QbD concepts requires understanding of variability in raw materials and the relationship between a process and product's critical quality attributes (CQAs). Under the concept of QbD, when designing and developing a product there is a need to define desired product performance and identify CQAs for the process. The final product attributes could be set on the basis of this information. Therefore, there is a need to understand the impact of raw material and process parameters on the CQAs and identification and control of sources of variability. A process can be continuously monitored and product quality can be ensured, once all these information are acquired.

In this work, a complete plant-wide control framework has been developed for the integrated continuous pharmaceutical tablet manufacturing process. The framework identifies process and product CQAs and defines a set of allowable range of values for each CQAs based on the design space, which is created either using process model or empirically through experiments. Various sensing scheme has been developed to measure different CQAs online that in turn help in real time monitoring of the process.  NIR spectroscopy along with Microwave sensing is used to monitor content uniformity of the blend and ribbon density and moisture content of the ribbons. A partial least square model is developed for the measurement of these properties through NIR and a resonance model is developed for microwave sensor. Online measurement of particle size distribution is done through the use of Eyecon imaging technique.

The framework is applied on pilot scale continuous pharmaceutical tablet manufacturing plant consisting of feeders, blenders, roller compacter, granulator and tablet-press. CQA variables were continuously monitored and the framework was able to detect and diagnose various faults, including those involving a single process unit, multiple units as well as controller faults. The framework was able to prevent the process to move into Emergency Shut Down (ESD) and was able to bring it back to Normal Operating Condition (NOC) through the implementation of mitigation strategy.


A. Gupta, A. Giridhar, G.V. Reklaitis and V. Venkatasubramanian, Intelligent Alarm Systems applied to Continuous Pharmaceutical Manufacturing, ESCAPE 23 proceedings, Lappeenranta, Finland, June 2013

A. Gupta, A. Giridhar, V. Venkatasubramanian and G.V. Reklaitis, Intelligent Alarm Systems applied to Continuous Pharmaceutical Manufacturing – an integrated approach, Industrial and Engineering Chemistry Research, DOI: 10.1021/ie3035042, March 2013

J. Austin, A. Gupta, R. McDonnell, G. V. Reklaitis, M. T. Harris, The Use of Near Infrared and Microwave Resonance Sensing to Monitor a Continuous Roller Compaction Process, Journal of Pharmaceutical Sciences, DOI: 10.1002/jps.23536, March 2013