Simulation of Production of Pharmaceuticals

A look into how to move from batch production to continuous production.

Compressed powder tablet.

In the growing competition of the Pharmaceutical world, batch production of Active Pharmaceutical Ingredients (APIs) is starting to make way for continuous manufacturing. With fewer shutdowns and reduced waste and energy consumption, continuous production has clear advantages compared to batch processes. Controlling a continuous reaction does have its set of challenges, but multiphysics numerical simulations can do much to help prototype, optimize and model the system.

Simulations can allow engineers to optimize the system and the varied (often small) equipment associated with a continuous process. Using design of experiments (DOE), this optimization can ensure fast throughput, reduce risk, set up real time control processes, reduce variability, increase repeatability and produce a fine tuned design. One option for such a design is STAR-CCM+ Optimate, which allows for various “what-if” scenarios for your DOE.

STAR-CCM+ is a CFD multiphysics simulation program capable of discrete element modeling (DEM) and Eulerian multiphase modeling (EMP).

Discrete Element Modeling

DEM is a method used to calculate the interactions of many small particles. “The Lagrange approach  is  used to assess how particles bump into neighbours and walls. It is a  particle interaction problem. We can now see how the fluid flows around the particles and how they interact. This method also involves a lot of empirical data. For instance the program must be told if particles will stick together like with a blood clot, or have elastic properties,” said Dr. Kristian Debus, Life Sciences Industry Sector Manager at CD-Adapco.

Fluidized Bed Reactor.

Debus goes on to say, “To simulate the process you must create the computational domain as you would do for an aerodynamics simulation. You then define the origin or source location or the distribution of the particles. Beyond the particle and flow interactions, one can also for instance model a continuous fluidized bed reactor. In the old days you would model a packed bed as a porous medium but now with DEM we can look into the microstructure of the system. This is useful in the pharma industry. In general, modeling and simulation can save a lot of money with lab scale and pilot plants. But you of course can’t cut those out completely.”

“It can be hard to track all of the particles and see all the interactions, depending on the amount of particles in the model.  And we provide ‘best practices’ to guide our users to setup realistic and accurate models.  Recently we also added passive scalars to the DEM software. These allow for the particles to be tracked more easily,” expressed Debus.

Eulerian Multiphase Modeling

EMP analysis no longer looks at the specific particles, but at the continuum of a system instead. “Where DEM works with Lagrange particles which have a specific size, mass and density etc., the Eulerian perspective is more how traditional CFD models work,” explains Debus. “. These methods are usually applied for fluid/fluid or fluid/gas mixtures, but have been extended to granular models which allow for modeling an infinite number of particles through a continuous model.  Each of these models have their specific applications, space and range to answer questions like: Will the reactor be well mixed? This is an important question to answer when dosages are involved.”

“With EMP, you can look into multiphase models like say bubbling gas through water. You can see the phase changes, the liquid flow, or even cavitation bubbles. These can all be tracked in the same model and the user can analyse the interactions,” adds Debus.


To help regulatory bodies and business managers sign off on the process, simulations can be used to design the process, determine initial problems and risks, and design and test solutions. The simulation will typically consist of multiphysics including chemical reaction, mass/heat transport, and fluid/gas/particulate CFD analysis.

Physical testing of a manufacturing process in a laboratory can be rather expensive. Simulations can produce a digital lab to allow for the initial testing to be performed even before a lab coat is taken off the rack.

Batch systems typically consist of sub-processes of the steps needed to produce a product. Often these sub-processes take place at different facilities. Therefore, each sub process will require energy to clean, start-up, shutdown, transport and store the intermediate products and equipment. This transfer can also lead to increased waste as sticky or chalky products resist transport. For each sub process there may be a quality assurance and post production processes too that can otherwise be consolidated within a continuous process.

Continuous manufacturing is a nonstop process for converting raw materials to final products. This constitutes a leaner, faster, cleaner, greener, higher quality and often safer production process. Furthermore, it can allow manufacturers to cut down on inventory, which is a clear winner for Goldratt fans. In fact, continuous manufacturing makes so much sense that even the pharmaceutical regulatory boards are beginning to reverse their conservative views. All of which makes continuous manufacturing not just a safe and efficient process, but a potentially strong player in the future of the pharmaceutical industry.

Simulation of the Coating Tumbler Batch Process.


Images and video courtesy of CD-adapco.

Written by

Shawn Wasserman

For over 10 years, Shawn Wasserman has informed, inspired and engaged the engineering community through online content. As a senior writer at WTWH media, he produces branded content to help engineers streamline their operations via new tools, technologies and software. While a senior editor at, Shawn wrote stories about CAE, simulation, PLM, CAD, IoT, AI and more. During his time as the blog manager at Ansys, Shawn produced content featuring stories, tips, tricks and interesting use cases for CAE technologies. Shawn holds a master’s degree in Bioengineering from the University of Guelph and an undergraduate degree in Chemical Engineering from the University of Waterloo.