From the test tube to the reactor: this short definition illustrates what scale up is about—the scaling-up of manufacturing processes for chemical and pharmaceutical products from the laboratory or pilot scale to industrial production. It is crucial to adjust operating parameters so that product quality and safety are maintained while ensuring that the plant operates stably and economically. The goal of the scale-up process is to create robust and efficient large-scale production lines.
Good to know: During upscaling, downstream process steps, such as aseptic filling, often become relevant. A modern solution for this is the Blow-Fill-Seal (BFS) systems from Rommelag. In these systems, containers are formed from sterilized polymer granulate, immediately filled with the product, and hermetically sealed—all in a single, fully automated aseptic process. BFS containers are shatterproof, lighter than glass, and can be produced in many different formats—from ampoules to bottles. Storage, cleaning, or sterilization of preformed containers is unnecessary, simplifying logistics and costs.
Importance of Scale up in Process Engineering
The transfer of technology to large-scale production is so fundamental in the chemical and pharmaceutical industries that it is one of the core tasks of chemical engineering—a discipline responsible for the development, design, and scale-up of process engineering operations.
Typically, production processes begin in the laboratory, where synthetic routes are developed on a small scale, for example, to produce active ingredients. The major challenge is then to scale up these methods—initially performed successfully in test tubes and flasks—so that products can be manufactured industrially.
In chemistry and pharmacy, upscaling usually involves multi-step processes: from the laboratory to the technical center, then to pilot plants, and finally to a fully designed production facility or large reactor. The goal is to transfer knowledge gained from all individual steps—such as reaction times, heat transfer, flow behavior, and product quality—to the industrial solution, aiming to design a stable and economically viable plant.
A typical example from the pharmaceutical field is the production of an infusion solution. In the lab, sample volumes are usually limited to up to 500 ml, while industrial production targets 1,000 liters or more per day. As part of the scale-up process, the production of several liters is first tested under controlled conditions. The team gains key insights into filtration, viscosity, heat dissipation, and other process parameters. Based on this, a large-scale plant is developed to ensure identical product quality and reproducible parameters.
Challenges in Upscaling
What seems simple on paper can be highly challenging in practice. In reality, mixtures behave differently in large reactors because the ratios of surface area to volume, heat quantities, and flows differ significantly.
The following are generally the main challenges in chemical upscaling, though others may occur:
- Heat and mass transfer: Mixing and cooling often work much better in small reactors than in large apparatuses.
- Flow conditions: Turbulence, stirring speed, or gas bubble distribution change during scale-up.
- Safety aspects: Exothermic reactions, pressure buildup, or explosion hazards must be reassessed.
- Product quality: Even in large quantities, consistent product quality is essential—parameters like purity, particle size, and solvent matrix play a role.
These challenges lead to specific considerations for plant design. By adjusting geometry, one can influence contact times, mixing efficiency, and sterility. Furthermore, most manufacturers today aim to automate processes as much as possible, which creates additional requirements, such as sensor integration. Lastly, the choice of raw materials can impose technical constraints on pumpability and dosing.
Methods and Approaches in Scale up
As described, there are numerous challenges in large-scale upscaling. At the same time, it is essential to produce safe, stable, and cost-efficient products. Therefore, a wide range of methods and approaches have been developed.
Dimensionless Numbers
In technical chemistry, it is common to work with dimensionless numbers. The Reynolds number (indicating whether flow is laminar or turbulent), the Péclet number (predicting temperature and concentration gradients), and the Damköhler number (estimating whether processes are reaction- or mixing-limited) help transfer processes from the lab to industrial scale.
Computer Simulations
Computer simulations play an increasingly important role in predicting reactions. Using digital twins of existing or planned systems, detailed, data-based scenarios can be simulated and evaluated for factors such as heat transfer, flow, and reaction times—provided that the underlying models are validated and supported with sufficient process data.
Other Methods
There are also many other ways to solve specific problems, such as the scale-down method, where users take the reverse approach by modeling critical parts of the plant to gain further insights. Traditional approaches like Design of Experiments (DoE) are also still used, where scalable parameters are systematically varied to find an optimum.