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PHARMACEUTICAL AUTOMATION Numerical simulations for continuous manufacturing of active pharma ingredients

Mar 4, 2019

Multi-physics numerical simulation is emerging as game-changing technology to help continuous manufacturing for Active Pharmaceutical Ingredients (APIs) become a reality through virtual prototyping, optimisation and modelling of the complete system.

The pharmaceutical industry is encountering a decline in productivity, and outdated “tried-and-true” batch processes are at the root of the problem. The batch-based systems currently in place are inefficient due to segmented steps involving multiple facilities and requiring start-and-stop of the batch, site-to-site transfer and warehouse storage. Performed through sampling and in post-production, quality assessment of the product is also cumbersome, causing long lead times and waste.

Continuous manufacturing, a non-stop end-to-end manufacturing process, could modernise the industry and solve its productivity crisis. At a recent MIT conference, Josef Jimenez, CEO of Novartis, stated that changing production from batch to continuous will transform the way medicines are made around the world and could cut the time from development to marketentry in half. Implementation of these processes will result in smaller production plants, lower inventory costs, reduction in carbon footprint and higher quality products. The regulatory agencies are also starting to lay the groundwork for continuous manufacturing with several initiatives and regulatory frameworks such as the Process Analytical Technology (PAT) and Quality by Design (QbD). Each of these encourages the development of new manufacturing technologies by building quality into the process and using a science-based quantified risk approach.

Both the chemical and food processing industries have been improving their productivity by successfully integrating continuous manufacturing into their plants. It is clear that regulatory hurdles and conservative thinking by the pharmaceutical industry can no longer be used as an excuse to avoid taking pharmaceutical manufacturing into the 21st century.

Numerical simulations & continuous manufacturing

Before continuous manufacturing can become main-stream, potentially suitable candidate processes must be identified and designed, and risks must be analysed and mitigated. This will help manage regulatory compliance and make a business case for implementation. Multi-physics Computational Fluid Dynamics (CFD), a numerical method for predicting the coupled behavior of fluid, gas and particulate flows including heat and mass transport, offers a solution for the enhanced understanding and design of these novel processes.

Virtual prototyping

Traditional manufacturing processes are based on the “design-build-test” principle in which the effects of design changes are quantified by experimental tests on physical prototypes. There are currently very few suppliers who are developing integrated systems for continuous manufacturing and, as a result, physical prototyping is anticipated to be very costly. Numerical simulations enable the engineer to build a virtual laboratory, providing insight into the performance of a product before tests are carried out. This means that the uncertainty resulting from major process and equipment changes can be evaluated up front, leading to a significant risk reduction and cost savings.

Multi-physics CFD and state-of-the-art visualisation tools also offer a wealth of detailed information, not always readily available from laboratory or experimental tests. This not only results in an increased level of insight into the details of what is going on inside the processes, it also enables innovation. For example, multi-physics CFD can help explore new reactions and molecules for drugs manufactured with a continuous process.

Design exploration and optimisation

In recent years, the phenomenal increase in computing power and the maturing of robust simulation tools have paved the way for using numerical design optimisation in production environments. Parameter studies and optimisation will be vitally important for designing and tuning of the new (often smaller) equipment required for continuous manufacturing while ensuring that the operation can efficiently handle fast reactions and remains flexible. In addition, the CFD-generated responses - obtained through design of experiments over a range of operating conditions and equipment design parameters - can be combined with statistical models to identify risk and implement robust realtime process control. This will ultimately result in reduced variability and consistent, repeatable processes.

Optimate (a module in STAR-CCM+ using Red Cedar Technology’s HEEDS software) is an example of a tool that enables intelligent design exploration to easily consider “what if” scenarios and identify the critical manufacturing points that define quality. For example, feeding devices for continuous manufacturing influence all downstream operations and design exploration of parameters such as feed rate will help identify their impact on final blend uniformity.

Simulating the System

Solving complex real-world problems demands an accurate, easy-to-use, multi-disciplinary approach to simulating complete systems. CFD-focused multi-physics engineering simulation tools such as STAR-CCM+ can accurately deliver full spectrum engineering results and the pharmaceutical industry should fully leverage these tools in support of the development of continuous manufacturing processes. Up until now, integration of numerical simulations in a production environment has required a great deal of specialised knowledge, but this is no longer a showstopper. Automation and ease-of-use are enabling the deployment of CFD for complex multi-physics applications. For example, STARCCM+ offers state-of-the–art meshing, seamless integration with CAD and easy modeling of complex moving parts, all in a single integrated environment. The net result is more time for an engineer to analyse data instead of preparing and setting up the simulations, resulting in engineering success.

Seeing the “big picture” for continuous manufacturing will require a multi-physics approach to solving problems. Be it mixing, coating or drying, multi-phase flows lie at the core of the pharmaceutical processing industry. Capabilities such as Discrete Element Modeling (DEM), a numerical method for computing the interaction of a large number of small particles, and Eulerian Multiphase Modeling (EMP), a numerical method for simulating several phases in a system, will be invaluable for implementing continuous manufacturing of APIs. Two case studies are presented next to demonstrate these capabilities.

Case Study 1: Direct Element Modeling (DEM) for pill coating

DEM simulates the motion of a large number of interacting particles and tracks them in a numerically efficient manner, modeling contact forces and energy transfer due to collision and heat transfer between particles. DEM will be particularly important in the design and optimisation of continuous coating processes to help identify the important factors for equipment design (e.g. number of spray guns) and to determine optimal equipment operation conditions (e.g. inlet temperature). Figures 3 and 4 show STAR-CCM+ generated solutions for two types of equipment currently used for real-world tablet coating: coating pan (rotating drum) and fluidised bed. In these simulations, DEM is used to analyse the random movement of the particles as layers of coating are applied. Parameters such as particle velocities, residence time and coating thickness are tracked to assess and improve tablet coating uniformity. In addition to tablet coating, DEM can also be used to simulate other steps in manufacturing such as filling, filtering and conveyer processes.

Case Study 2: Eulerian Multiphase (EMP) Modeling for mixing

EMP modeling provides an effective means for studying the interacting streams and randomly dispersed phases in multiphase flows. The EMP model in STAR-CCM+ includes an extensive range of sub-models including break-up and coalescence models for bubbles and droplets and a granular flow model for particles. Figure 2 demonstrates an EMP simulation of a gas-liquid mixer with three rotating impellers. Shown are the effects of increasing gas injection rates on gas. The ability to predict gas hold-up, a parameter that governs mass transfer across the phases and consequently rates of reaction, is a key enabler in the design of such reactors. This approach adds valuable scientific insight into the decision-making criteria to develop practical solutions for mixing and other processes in continuous manufacturing.

Conclusion

In today’s competitive climate, manufacturing must become leaner with a focus on building quality into the process. Continuous manufacturing for the pharmaceutical industry will change the way drugs are made and multi-physics CFD simulations offer a cost-effective way to perform rapid prototyping for design of new equipment and processes. In particular, design optimisation tools and powerful multiphase models such as DEM and EMP will play an important role, and the pharmaceutical industry should fully leverage these stateto- the-art technologies for the design and implementation of continuous manufacturing processes.

Image Gallery

  • Fig: 1 Ultra-lean manufacturing, from start of chemical synthesis to final pharmaceutical dosage form (courtesy of Novartis-MIT Center for Continuous Manufacturing)

  • Fig: 2 Mixer model showing the effects of increasing gas injection rate using STAR-CCM+

  • Fig: 3 DEM simulation for tablet coating with STAR-CCM+
    showing pill coating thickness in a fluidised bed

  • Fig: 4 DEM simulation with STAR-CCM+ showing tablet velocity magnitude as they tumble in a coating pan

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