Abstract
Process simulation using mathematical modeling tools is becoming more common in the pharmaceutical industry. A mechanistic model is a mathematical modeling tool that can enhance process understanding, reduce experimentation cost and improve product quality. A commonly used mechanistic modeling approach for powder is the discrete element method (DEM). Most pharmaceutical materials have powder or granular material. Therefore, DEM might be widely applied in the pharmaceutical industry. This review focused on the basic elements of DEM and its implementations in pharmaceutical manufacturing simulation. Contact models and input parameters are essential elements in DEM simulation. Contact models computed contact forces acting on the particle-particle and particle-geometry interactions. Input parameters were divided into two types—material properties and interaction parameters. Various calibration methods were presented to define the interaction parameters of pharmaceutical materials. Several applications of DEM simulation in pharmaceutical manufacturing processes, such as milling, blending, granulation and coating, were categorized and summarized. Based on this review, DEM simulation might provide a systematic process understanding and process control to ensure the quality of a drug product.
Highlights
The pharmaceutical industry faces a number of regulatory and economic challenges that are related to process development [1]
The development of the manufacturing process should be based on systematic process understanding and process control to ensure the quality of the drug product in accordance with the quality by design (QbD) approach defined by an international conference on harmonization guidelines (ICH Q8: pharmaceutical development) [2]
Manufacturing process simulation using mechanistic modeling has become increasingly important to overcome the various regulatory and economic problems associated with manufacturing process development in the pharmaceutical industry
Summary
The pharmaceutical industry faces a number of regulatory and economic challenges that are related to process development [1]. The development of the manufacturing process may require considerable time and resources from an economic perspective These challenges may result from the lack of cost-effective and reliable modeling tools of unit operation development in the pharmaceutical industry, in contrast to other chemical industries [3]. It is necessary to apply the modeling tools to the process, to overcome the challenges of regulatory and economic aspects and to develop a more efficient and robust process [1] In response to this necessity, the modeling of the manufacturing process has been become increasingly important, as it can be applied to equipment design, improving process efficiency, scale-up and unit operation development in the pharmaceutical industry [4]
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