Enhancing pharmaceutical process design with simulation

How digitalization is transforming pharmaceutical scale-up from lab to production

This blog explains how pharmaceutical companies use simulation and Executable Digital Twins (xDT) to accelerate drug development, optimize manufacturing scale-up and reduce time-to-market while addressing the unique challenges faced by process engineers, research and development (R&D) leaders and manufacturing teams.

The primary aim of pharmaceuticals is to provide medical treatment for chronically or acutely sick patients; however, with its long incubation and high R&D costs, the competitive pressure to discover, develop and scale newer drug types has never been higher.

Scientists and researchers ultimately have the same goals: deliver the breakthrough treatments that improve or save patients’ lives. New drugs and therapies often take 10 years to bring to market and the demand for innovative personalized therapies add another layer of complexity.

Technological advances such as computer modeling, AI and initiatives like Quality by Design (QbD) enable the discovery of new therapies and delivery platforms, but these often require intricate manufacturing techniques which make it difficult to bring them to the market quickly and cost effectively. And, as if this wasn’t enough, pharmaceutical companies must deal with scale-up challenges and the pressure to make businesses fully sustainable as well as profitable. To overcome these barriers, pharmaceutical companies need to adopt development approaches that push the boundaries of medicine without compromising cost-effectiveness or development timelines.

The hidden risk of working in silos

Simulation is a vital tool for the pharmaceutical industry because it provides unique and detailed information about fluids, particles and solid mechanics, often beyond what is either experimentally possible using sensors and traditional empirical guides to make data-driven development decisions However, an extra complication of simulation in the pharmaceutical industry is the different length-scales, time-scales, and multiphysics involved in the drug manufacturing process. Multiple tools are needed to simulate these which, if used separately, lead to the creation of data silos. 

Each new pharmaceutical product that’s developed requires increasingly complex and costly physical experiments. These experiments generate large volumes of fragmented data that must be contextualized and analyzed to produce results—no easy task when teams are siloed with very limited means to share knowledge or collaborate seamlessly. Moreover, disconnected data slows down not only drug discovery and development, but it can compromise timely regulatory submission.

Leveraging simulation to optimize the entire product lifecycle

How can you rapidly design a robust manufacturing process that enables more efficient scale-up from lab to production?

The key is the digitalization of the entire product lifecycle, from drug discovery to commercial manufacturing, enabling a continuous optimization loop that feeds data and insights from clinical trials and manufacturing back into future research and development. By leveraging simulation solutions, pharmaceutical companies are better positioned to accelerate recipe development and enhance collaboration and drug manufacturability, reducing time-to-market and saving money.

Bridging the gaps to address pharmaceutical complexity

Building a Digital Twin of products and processes allows companies to combine real-world data with simulated data to design predictive and prescriptive models. Designing and scaling recipes from laboratory to clinical trials and commercial manufacturing with an ISA-88 guided Enterprise Recipe Management (ERM) approach enables knowledge-driven digital recipe transformation.

In this way, manufacturers can increase the robustness, cost efficiency and sustainability of production by reducing the use of raw materials and optimizing equipment usage.

But, simulation alone is not the answer to meeting the modern challenges faced by the pharmaceutical industry. Pharma manufacturers need to derive insights from simulation quickly and capture this data in an efficient way to make informed decisions in real time. This is why products within the Simcenter portfolio are built to combine multiscale and multiphysics simulation. This helps bridge the gaps between the different development stages that make up the complete pharmaceutical product lifecycle.

The value of the Executable Digital Twin

Pharmaceutical production is rarely static. A facility might produce multiple products over its lifetime, requiring adaptability in design. This is where an Executable Digital Twin can make physics-based modeling simple enough to be run in near real time, while still accurately representing the process. It uses state-of-the-art mathematical techniques to analyze and optimize process design or operation at any time. Once the production line is built, if it’s needed for different products across the lifetime, data-driven optimization can deliver enormous savings.

GSK, a global biopharmaceutical company utilized Simcenter solutions to develop the first virtual replica of a vaccine process which reduced the development time of its vaccine by 25%.

The xDT empowered them to virtually test production processes at every stage of development, collecting real-time data with virtual sensors that delivered vital insights. As well as getting the vaccines to market sooner, simulation saved significant numbers of batches that would otherwise have been wasted.

Secure market positions with the most comprehensive AI-powered design and simulation portfolio

Modeling the complexity of modern pharmaceutical development and production is essential to understanding the geometry, physics and anything else at play that may influence performance. Simulation enables the exploration of all the possibilities with virtual models, allowing engineers to experiment with more freedom and without the constraints imposed by physical testing. 

Simulation insights will also benefit both process optimization and faster design-space exploration in an increasingly competitive market.

Simcenter is the most complete simulation portfolio. Using integrated data and AI-powered performance engineering, pharmaceutical companies can equip their organizations with the latest digital technology to achieve faster cycles, smarter decisions, better performance and stronger competitiveness.

How does the Simcenter portfolio transform development?

• Comprehensive: Assess all aspects of multiphysics performance and apply it to all phases of development and usage.
• Intelligent: Rapidly generate and evaluate concepts with AI and streamline and automate complex workflows.
• Adaptive: Scale and evolve resources to maximize agility and integrate simulation into the digital thread.

To learn more about how Simcenter is transforming the pharmaceutical industry, read the white paper here: The power of simulation in designing a pharmaceutical manufacturing process

FAQs about enhancing pharmaceutical processes with simulation

1. What challenges do pharmaceutical companies face in bringing new drugs to market, and how can digitalization help? 
   Pharmaceutical companies face significant challenges, including long incubation periods, high R&D costs, the need for intricate manufacturing techniques, scale-up complexities and pressure for sustainability. Digitalization, through simulation and AI, helps by enabling rapid process design, efficient scale-up from lab to production and continuous optimization throughout the product lifecycle. 

2. How does simulation address the issue of data silos in pharmaceutical development? 
   The pharmaceutical industry often deals with multiple length-scales, time-scales and multiphysics, requiring various simulation tools. When used separately, these tools can create data silos, hindering knowledge sharing and collaboration. Simulation solutions help bridge these gaps by integrating data and insights across different development stages. 

3. What is an Executable Digital Twin, and how does it benefit pharmaceutical manufacturing? 
   An Executable Digital Twin (xDT) is a simplified, physics-based model that can run in near real-time while accurately representing a process. It uses advanced mathematical techniques to analyze and optimize process design and operation. For pharmaceutical manufacturing, xDTs enable virtual testing of production processes, real-time data collection with virtual sensors and significant reductions in development time and wasted batches.