Cleaning process validation is often perceived as a technical, demanding, and sometimes laborious exercise... and that is far from wrong.
Among the various strategies available to validation teams, the matrix approach holds a unique place. It intrigues, reassures, and sometimes divides. Some see it as a powerful efficiency driver; others view it as an underestimated methodological risk.
But what truly makes this approach strong — and what makes it fragile?
Understanding the matrix approach
The matrix approach rests on a simple idea: rather than individually validating the cleaning of each product on each piece of equipment, similar entities are grouped together.
Products are organised according to their properties (toxicity, solubility, cleaning difficulty), equipment according to its complexity or its ability to retain residues, and cleaning processes according to their characteristics (although, generally, the prerequisite for grouping equipment and products is the use of the same cleaning process).
Once these groupings are established, a worst-case is identified — that is, the most critical element in the group, whose control guarantees control of all others.
This method does not merely simplify: it structures. It not only reduces the number of validations but also gives meaning to their selection.
The advantages of an intelligent strategy
What first appeals about the matrix approach is its elegance. It transforms a voluminous problem into an organised, readable, coherent system. In multi-product environments, where validations could chain endlessly, it allows efforts to be focused on what truly matters: the hardest-to-clean products, the most critical equipment, and the most unfavourable process parameters.
Time is saved, of course, but so is relevance. The matrix approach fits within a QRM logic: it forces teams to understand what truly makes a product critical, to analyse processes, and to objectively compare toxicological, physicochemical, or operational characteristics. It reinforces scientific thinking rather than diluting it.
Another advantage, often underestimated, lies in the matrix's ability to accommodate new products. When its structure is well defined, the arrival of new elements (product, equipment...) no longer causes a documentary earthquake: it is simply a matter of assessing the element's position in the matrix and ultimately verifying whether it redefines a new worst-case to be validated or not. This stability brings valuable peace of mind in environments where portfolios are constantly evolving.
Limitations — sometimes subtle but very real
While the matrix approach can simplify matters, it can also complicate them when poorly designed. Its first weakness stems from the overconfidence it can inspire. A poorly documented matrix, or one built on questionable criteria, creates an illusion of safety without delivering the reality. The most common case: a poorly chosen worst-case, overly theoretical, that does not reflect field conditions, or that generates conditions to validate which are no longer representative of real-world practice.
Another difficulty arises from the outset. Building a robust matrix requires a significant volume of data and an excellent knowledge of the products, equipment, and manufacturing processes involved. It is a multidisciplinary, demanding effort that mobilises production, quality control, validation, and sometimes even pharmaceutical development. The initial phase is very resource-intensive and requires solid justifications to withstand an inspection.
Finally, the matrix approach is not universal. It adapts very well to environments where products are similar and equipment is reused homogeneously. But with highly toxic products or when product diversity is very broad, its limitations quickly become apparent.
An additional risk must be noted: the frozen matrix. PDE values change, new equipment appears, processes evolve. A matrix that is not reviewed regularly quickly becomes obsolete — and therefore difficult to defend.
A useful approach, provided it is managed over time
The matrix approach is neither a magic solution nor a trap. It is a tool. A powerful approach when used intelligently, documented rigorously, updated regularly, and supported by solid risk analyses. It can transform cleaning validation into an efficient, rational, and defensible process. But in return, it demands continuous vigilance and a thorough understanding of its context.
In a world where regulatory requirements are intensifying and product portfolios are becoming increasingly complex, this approach represents a subtle balance between pragmatism and scientific rigour — a balance that each company must build, maintain... and adapt.
How can the way this approach is managed be redefined?
It is precisely at this intersection of complexity and rigour that the Hally solution finds its purpose.
Building a comprehensive matrix, selecting the right criteria, identifying worst-cases, providing toxicological justification, maintaining continuous updates... all these steps take time, require consistency, and rely on data that is sometimes scattered.
It is worth remembering that adapting strategic choices over time is entirely normal, particularly in response to regulatory developments. In 2015, the introduction of the PDE concept — via the MACO HBEL calculation — rendered most existing strategies obsolete.
And in 2026, a new update to Annex 15 of GMP guidelines is planned, with the objective of delivering a final version incorporating new technologies for facilities, products, and processes, taking into account ARL recommendations, broadening the scope to APIs, and reflecting developments arising from the revision of ICH Q9 R1 on quality risk management.
Hally brings a structured approach to this complexity. By centralising product data, automating calculations, and providing a dynamic view of groupings, it enables the design of robust, defensible, and above all living matrices! Hally does not replace expertise, but makes it more fluid, more reliable — and above all more practical.