Appendix 1 (§ 5.4) further specifies that any cleaning process must be validated to effectively remove residues that could impair the effectiveness of disinfectants and compromise batch quality. Sections 6.1 to 6.4 extend this requirement to critical utilities (water, steam, filtered air), which must be designed and monitored in a manner proportionate to the identified risks.

In this context, automated GMP cleaning is no longer just a technical operation: it is a strategic link in contamination control, contributing directly to the robustness of the CCS and the quality of the products manufactured. Unlike manual cleaning, which is more difficult to standardize and validate, automated cleaning reduces human variability, documents each cycle, and ensures proven reproducibility.

This article presents the keys to success for implementing a GMP cleaning solution project, based on the experience of strategic projects carried out at VIRBAC. From the drafting of the URS to the final qualification, we will show how methodological rigor, a scientific approach, and project governance guarantee success.

1. Methodological rigor

1.1 From the URS to the contract: the cornerstone of the project

Drafting the URS is a key step. According to ISPE and ICH Q8 recommendations, it must convert user needs into clear, measurable, and objectifiable requirements. All too often, overly general specifications (“machine capable of washing production parts”) lead to discrepancies during qualification because acceptance criteria were not defined in advance.

VIRBAC has implemented a very precise and rigorous approach to defining its requirements:

• Precise specifications with an exhaustive list of requirements in table form, one line per requirement, and the expectation of a clear response from the supplier to each requirement
• The definition of quantified criteria: Water temperature up to 70°C +/- 5°C; detergent concentration between 0% and 5%
• Demonstration of coverage of surfaces to be cleaned using a riboflavin test
• Parts must be visually dry, identification of parts that are difficult to dry (made of polymer or with external retention areas such as Nalgene bottles)
• Consideration of regulatory constraints: 21 CFR Part 11, GAMP 5, Annex 1 of EU GMP.
• A clear list of parts to be cleaned
• Definition of document traceability requirements.

Result: solid contractual alignment, less risk of vague interpretations or deviations in qualification. The URS is a key element of the project, facilitating qualification and then validation from the design stage onwards.

From design to qualification. Each stage of the GMP project cycle is marked by qualification milestones:

• DQ: design qualification based on the URS and risk analyses (QRM)
• FAT: dynamic factory tests with actual loads when parts can be made available during the FAT period. Providing complete documentation from the FAT stage allows certain tests to be capitalized on in SAT, or even in IQ/OQ.
• SAT: on-site testing with actual utilities
• IQ/OQ/PQ: complete system qualification with documentation at each stage.

Capitalizing on the results of FAT and SAT testing in IQ/OQ or even PQ saves a significant amount of time in the entire cleaning validation process. This is possible when quality assurance teams are present from the validation of FAT/SAT protocols through to the completion of testing.

For VIRBAC, the FATs, carried out in the presence of quality assurance, included static and dynamic tests with loaded baskets, and the SATs made it possible to adapt the recipes to the characteristics of the site’s water.

VIRBAC ensured documentary traceability from the drafting stage onwards, thanks to protocols validated by quality assurance, thus avoiding late modifications.

1.2 Adaptation to production contexts

Cleaning requirements are adapted to production contexts. In all cases, the aim is to remove traces of product and detergent and to dry the loads to control the risk of cross-contamination.

The risk analysis carried out prior to the cleaning validation process will enable acceptance criteria and therefore requirements to be defined. This has an immediate impact on the design strategy for cleaning baskets in particular.

The URSs for VIRBAC projects have incorporated this data to design a versatile system, notably through baskets that can be adapted to several families of parts.

1.2 Adaptation to production contexts

Cleaning requirements are adapted to production contexts. In all cases, the aim is to remove traces of product, remove traces of detergent, and dry the loads to control the risk of cross-contamination.

The risk analysis carried out prior to the cleaning validation process will enable acceptance criteria and therefore requirements to be defined. This has an immediate impact on the design strategy for cleaning baskets in particular.

The URSs for VIRBAC projects have incorporated this data to design a versatile system, notably through baskets that can be adapted to several families of parts.

2. Scientific approach

2.1 Recipe development: the TACT logic

The development of cleaning recipes is based on the evaluation of the combined action of the four cleaning parameters, represented in the form of the SINNER circle (Fig. 1).

The simultaneous action of chemical agents and temperature loosens dirt from the surface to be cleaned, while mechanical action removes the products (dirt or detergent) until they are evacuated from the building.

The cleaning formula is therefore based on a rational approach centered around the general equation:

Each parameter is optimized through various analyses:

• Laboratory tests to select the type and concentration of chemical agents and the temperature
• Assessment of compatibility between the temperature and the product to be removed, and between the detergents and the materials of the parts to be treated
• Flow rate and pressure levels to ensure mechanical effectiveness
• Optimization of cycle time to balance efficiency and energy consumption.

Optimizing these parameters, and therefore the recipe, makes it possible to control the environmental impact and energy consumption.

At VIRBAC, the recipes were tested in several cycles, with samples taken for physical and chemical analysis with the support of COPHACLEAN to quantify residues. The inclusion of parts deliberately contaminated with the worst-case product demonstrated the robustness of the process. This approach illustrates QbD: the cycle is not defined by trial and error, but designed and optimized based on critical parameters identified upstream.

2.2 Machine + basket design: the key to the success of an integrated system

Efficiency does not depend solely on the machine: the machine and basket are inseparable.

Drawing up a list of parts to be cleaned is the essential starting point for basket design. It must be linked to the URS. This list makes it possible to define the precise requirements. For example, the dimensions of the largest parts influence the choice of washer chamber size.

The basket design must meet several requirements, which are verified in DQ and during the subsequent qualification stages:

• Comply with the loads to be cleaned in the same basket
• Check the 3D plans to ensure that all parts have been taken into account. Detecting any omissions (by the customer or supplier) during DQ has less impact on the project’s cost and schedule than during the subsequent stages.
• Ensure uniform coverage of all critical surfaces (riboflavin tests).
• Take into account the diversity of the parts to be washed (size, geometry, materials).
• Reduce operator fatigue by facilitating handling.
• Optimize hydraulic and air flows to minimize shadow areas.
• Position parts to facilitate water removal, thereby optimizing drying results and duration.

VIRBAC has adopted a proactive approach:

• Use of 3D scans and 3D modeling of the part
• Coverage tests (riboflavin) carried out during FAT with all parts in the load
• Optimized operator ergonomics
• Reduction of hydraulic shadow areas

Result: easier validation during FAT, enhanced reproducibility, and clear demonstration of cleaning control.

2.3 Integration into the CCS strategy

Appendix 1 requires cleaning to be a link in the CCS. Paragraph 2.5 stipulates that sources of contamination include microbial and particulate residues, and that CCS must cover cleaning and disinfection.

Within this framework, VIRBAC has:

• controlled critical cycle parameters (alarms, washer qualification),
• implemented monitoring of critical parameters (cycle report, conductivity, periodic verification of probe calibrations),
• documented risk analyses with traceability,
• integrated alarms and recordings into a Data Integrity approach.

The washer is no longer seen as isolated equipment, but as a central player in contamination control, on a par with air filtration and environmental monitoring. (see tab1)

3. Project governance: a determining factor

3.1 Structured and multidisciplinary governance

A GMP washer project is cross-functional: it involves production, qualification/validation (which is part of quality assurance), engineering, and maintenance. ICH Q9 emphasizes the importance of multidisciplinarity in identifying and prioritizing risks.

VIRBAC has implemented exemplary governance for a strategic project:

• Dedicated project team, including all key functions (production, qualification/validation, maintenance, general services, engineering)
• Regular collaborative workshops
• Documentation of each decision within a QRM framework
• Integration of results into the site’s CCS.

This governance has made it possible to create decision traceability: each technical choice (basket design, cycle parameters, instrumentation) is justified by a risk analysis and documented. During an inspection, this approach demonstrates that the project is part of a QRM-based contamination control process.

Conclusion

GMP cleaning, long perceived as a simple washing operation, is now a strategic issue in contamination control. VIRBAC’s experience shows that by combining methodological rigor, a scientific approach, and efficient project governance, it is possible to achieve a high level of compliance while reducing risks, hidden costs, and inspection discrepancies.

The future of GMP cleaning is built around innovation.

• Digitalization: real-time connectivity, data integrity
• Digital twins: preliminary modeling of flows and baskets
• AI/Machine Learning: predictive cycle optimization, conditional maintenance

These developments will enhance the robustness, traceability, and performance of cleaning systems. The washer then becomes not only a production tool, but a lever for differentiation and integrated quality for the pharmaceutical industry.