INTRODUCTION

Quality by design is a systematic approach for the development of pharmaceutical products, to enhance process understanding and finally, a better product quality. The understanding of the process, based on sound science and quality risk management makes a decisive contribution to a successful process capability and validation. According to the International Council for Harmonization (ICH), the Quality by Design (QbD) principle requires an analysis of the functional relationships between the material properties, the process parameters, and the critical quality features of the final product.
Implementing QbD often requires investment in resources such as time, expertise, and technology. Individuals or organizations with limited resources may find it challenging to adopt QbD practices, especially if they perceive the initial costs and effort as prohibitive. Establishing QbD may require significant changes to existing practices. The presented Automated process development refers to the use of automation and advanced technologies to streamline and accelerate the development of manufacturing processes. It offers numerous benefits, including speed, efficiency, data accuracy, resource optimization, complexity handling, iterative optimization, risk reduction, scalability, adaptability and flexibility.

Automated Process development

When a new formulation, capsule filling or tablet compression process has to go into operation, the primary goal in the development should not be only, to find the appropriate process parameters that enable filling within the specified process limits. Rather, it is crucial to investigate the entire range of process parameters globally in order to understand their influences and to operate the process at a robust and optimized operating point. This ensures safe and stable production.

Various influences can affect the result of a powder formulation, tablet compression or capsule filling process. These are, among others, the directly adjustable process parameters on the machine like the machine speed. Other process parameters are associated with a machine conversion and take a greater effort to change (e.g., the change between 2- and 3-paddle-feeder).

Finally, the material properties must be mentioned: Experience has shown that these have the greatest influence on the process. Each pharmaceutical substance has different chemical and physical properties that have a considerable influence on filling behavior.

A capsule filling or compression process can be described as a black box (Fig. 1). On the input side are the process parameters and the material properties that are fed into the capsule filling or compression process. On the output side is the result of the solid dosage form, described from the target values for the final product, also called Critical Quality Attributes (CQAs). For a capsule filling process, these include e.g., the average weight, the uniformity of the dimensions and the composition.

The decisive factor is now what happens inside the black box during the process, determined by the critical material attributes (CMAs) and the critical process parameters (CPPs). For the process commissioning, it is important to analyze all influences and interactions on the critical quality attributes.

There is no doubt that the performance of machine tests is associated with a prominent level of effort: Product is required for each test run, the tests must be conducted and then evaluated. To reduce this effort, the automated process development (APD) method can be used. Automated testing starts with statistically optimized test plans and carries them out automatically with reduced powder consumption on the corresponding system or machine.

Based on the experiments and the results, a model of the process can be created. This model describes the effects and interactions that are required for understanding the process and allows a prediction of the CQAs. The execution with the material on the real machine will later offer the advantage that the production process behaves in the same way as in the analysis. The process becomes transparent and can be validated, also better control strategies can be established.

The use of statistical design of experiments (DoE) offers significant added value compared to classical design of experiments. Here, the number of necessary experiments is considerably reduced in order to achieve the same informative value compared to an empirical experimental design. Furthermore, the effort required to set the process parameters on the machine is reduced. A high degree of automation during all processes enables the required settings to be made within a few seconds without manual handling steps and material loss. A higher-level controller automatically takes over the tests from the test plan and sets the process parameters automatically.

Automated Blending and fluid bed Granulation process

R&D equipment designed for semi-continuous manufacturing can be used to conduct fully automated and DOE-planned development of a solid dosage form with variation of critical process parameters in powder dosing, blending and fluidized bed granulation. Beside variation of API-content, different grades of excipients and content process parameters with major impact like mixing speed and time, inlet air temperature, inlet air volume rate, spray rate and spray air pressure are investigated in a short period of time.

Capsule Filling process

In the presentation a capsule filler with the automated adjustment of al critical process parameters, an advanced sensor technology to control material and process conditions and process monitoring and the automated change-over to the next parameter set will be presented (fig.2).

Automated process development can be used in process optimization. Combined with lower material consumption, the correlation of process efficiency and quality can be evaluated in 2 hours, compared to 2 weeks of standard manual work.

Interactions of process parameters make it often complex to optimize machine processes. In different tests we show, that different and sometimes totally, opposite process parameters can lead to a robust process. Examples of typical results are shown in figure 2.

Automated Process Development in tablet compression

The feeder of a rotary tablet press is usually operated with either 2 paddles (2-paddle feeder) or 3 paddles (3-paddle feeder). The studies in this article show that the mode of operation is a decisive and statistically significant influencing factor in the determination of parameters with the aim of reducing scatter in tablet weight and tablet hardness. A new automation solution for tablet presses will be presented, which enables a changeover from 2-paddle operation (2-paddle feeder) to 3-paddle operation (3-paddle feeder) as well as between diverse types of paddle shapes without manual intervention and machine stops. The comparison of the time required to a manual changeover provides an overview of the potential of the automated feeder for prompt and meaningful predictions for the optimal parameter settings on the tablet press. Different studies with poor flowing materials, identification of over-lubrication and capping effects will be shown.

Fully Automated and DoE-Based Development of an Oral Solid Dosage Form

The aim of this study is to demonstrate the potential of fully automated and DoE-based development of oral solid dosage forms (tablets). The combination of design-of-experiments and automated execution of the individual process steps offers a new potential to accelerate the development process and to integrate more Quality-by-Design.

• Planning of all trials using Design-of-Experiments
• Automated execution of all experiments and analysis of the results

By automating all development steps (granulation, compression and quality analysis) a high throughput and short development time were achieved. 26 different fluid bed granulation experiments were performed, more than 260 tablet batches were prepared, each containing more than 400 tablets. All tablets were evaluated on a new tablet analysis tool, measuring weight, dimension and API content. Also, the sophisticated investigation of interactions between formulation process parameters with the quality attributes of the compression step drives the understanding of the final manufacturing process and quality to a new level. The complete development process, from the powder to the final tablet, including determination and analysis of Critical Process Parameters and Critical Quality Attributes was performed in 7 days.

By combining DoE and automation it is possible to screen a larger parameter space, detect interactions of parameters, and optimize tablet quality (Quality by Design). Due to automation, the amount of material required is less than with manual testing and the intermediate change of the various modules such as 2- and 3-paddle-feeder. The method is transferrable to all kinds of oral solid dosage processes and products. It also can be used in the development of batch and continuous manufacturing products.

Conclusion

Automated process development combines Design of Experiments, automated execution of tests with the integrated measurement of quality attributes. Lower material consumption, more efficient process optimization and identification of critical process parameters make a pronounced contribution to reducing costs, improving quality and efficiency.