One of the goals of industry 4.0 is to achieve end-to-end digital process integration. In this post we’ll talk about the KASA Initiative and how it enables knowledge. And then, how that knowledge supports process monitoring, control and understanding.
This can be achieved through a complete data knowledge dimension, from the early development phase towards a mature product. And when we speak of complete data knowledge dimension, we’re talking about two concepts:
- Tacit knowledge – acquired from the people working on the process daily, during its lifecycle.
- Explicit knowledge – data that is generated from the process itself.
Managing the knowledge
We store knowledge in databases. And in database terms, you can manage two data types in this situation: structured and unstructured formats of data.
In database terms two data types must be managed in this situation: structured and unstructured formats of data.
Structured data is the tabular and relational data that is standard in a SQL database. On the other hand, unstructured data may come in other formats of data such as: images, logs to shop floor communications or notes.
As you can imagine, connecting these two data categories is not easy. But the benefits of doing so are huge because it leverages product and process understanding and, consequently, corresponding knowledge.
Scalability is the goal
Digitalisation is growing in the pharma and biopharma industries. And with it, the topic of how to get the most out of the stored data is back under the spotlight. And both regulators and companies are very interested in it!
As you can imagine, there’s the need for a unified way to gather and analyse the process and product information. Why? Because it would be systematic. And that would translate into a very much desired scalability.
And, of course, it would make it easier to provide information to regulators.
The KASA Initiative
This brings us to 2019, the year the FDA launched the “Knowledge-aided Assessment & Structured Application” initiative, also known as KASA.
The purpose? To establish a common ground for the essential requirements that a computerized platform should have to assess the regulatory submission information and a way to connect similar processes and products.
As such, KASA goals are to:
- Capture and manage information and data during a product’s life cycle.
- Establish rules and algorithms for risk assessment, control, and communication.
- Perform computer-aided analyses of applications that compare regulatory standards and quality risks across applications and facilities.
How does KASA Initiative work?
The point of KASA is to go from the available data to its full understanding and added value. And how does that happen? It uses a structured approach for the assessment of regulatory applications.
The knowledge base is the base of the house, the roof is the Knowledge Aided Assessment. We get from one to the other using the pillars, the structured application of knowledge management.
Fulfilling the KASA Initiative
KASA is an FDA internal initiative. That said, KASA principles can also be applied to the industry.
For that, there are four requirements that you should follow:
- Digitalisation. You need to acquire and store all the information in a digital format.
- Structure. You need to structure and map all the digitalised information. You should know the backbone of the data: Centre it around the process itself so that you can map the variables and information connected to it. This is especially important when we talk about unstructured data. If you generate the data in daily process routines, all information gathered must have a clear connection to a timestamp, a place and a responsible.
- Infrastructure. You need to gather the different types of data in a centralized place with all their interconnections defined. So, all types of data must have a defined relationship between them. In this section data lakes and its design can take a leading position on the added value it can undertake.
- Approach. You need to build a set of workflows to anchor and guide the analysis of your data. Those workflows will support the decisions that you make. This is valid for data acquisition and storage and for decision making based on the available data. This point is the most important because, if you have all the previously mentioned points but you are missing out this set of rules, you might not be able to turn the structured data into knowledge consistently.
Driving Full Integration
This complete, structured, and integrated information allows you to drive horizontal integration (process mapping and analysis from end-to-end) and vertical integration (history aggregation for life cycle management).
This approach gains a third dimension when gathering the same information across the product portfolio, facilities, and companies.
You can take the most out of the KASA concept for industry side as well. This by, not only bringing industry and regulators to a closer communication in terms of data storage workflow (including its application on risk assessment activities), but also potentiate an enhanced knowledge management within the company portfolio.
Bringing Risk and Data together to generate Knowledge
4TE is ready to support your digital transformation by helping you build the data structures that help you take the most knowledge out of your Data.
We recommend that you check our Custom-made Software services. If you think we may be able to help you out, don’t hesitate to book a call, we’ll do our absolute best to help.
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