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Software solutions

With our Werum PAS-X MES - on premise or cloud-based - and our software solutions for analysis, track & trace, networked factories, and intelligent packaging, we are the world's leading supplier and partner to the pharmaceutical and biotech industries.

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Handling systems

Handling systems

We are specialists for complete handling systems for pharmaceutical and medical products. Our solutions are decisive in the field of contactless and safe transport of e.g. glass syringes.

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Inspection machines


As the world's leading inspection expert, we develop solutions for the pharmaceutical and biotech industries. Our range of products extends from high-performance machines and semi-automatic machines to laboratory units and inspection applications for in-process control.

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Packaging machines

Packaging machines

We are a leading supplier of packaging machines for liquid and solid pharmaceutical and medical products. With our blister, sachet and stick packaging machines we offer solutions for primary packaging. Our side and topload cartoners set standards worldwide for secondary packaging.

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K.Pak Topload Case Packer

Introducing our latest solution from Körber; the K.Pak Topload Case Packer! Created specifically for the pharmaceutical industry, the K.Pak solution provides operator-friendly machines to complete any production line. Our solution focuses on innovative technology, high-quality design and expert handling and packaging of your product. It’s time to start connecting the dots with Körber!

Packaging solutions

Packaging solutions

As long-standing specialists, we develop packaging solutions for innovative and high-quality secondary pharmaceutical packaging made of cardboard. We offer you solutions for counterfeit protection, standard folding boxes and much more.

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Our experts will advise you during the analysis of your requirements, show you optimisation potential and support you during the implementation of projects in all areas of the pharmaceutical, biotech and medical device industry.

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How to develop your data management and data analytics strategy

During the past years, lab digitalization has increased, and sensor technology has improved tremendously. Through data management and an efficient data analytics strategy, you gain process knowledge and are able to continuously improve your process industry. But how do you develop your data management and a data analysis strategy which suits your needs? Read more in our blogpost and check out our step-by-step roadmaps.


  • What’s the role of data management and a data analytics strategy for the process industry?
  • Roadmap: How to develop your data management
  • Roadmap: How to develop your data analytics strategy
  • How to validate your software system in compliance with Part 11
  • Good to know: Intravacc

What’s the role of data management and a data analytics strategy for the process industry?

The management and analysis of accumulated data from R&D, Manufacturing, and Quality Control (QC) have an immense potential to speed up time-to-market and optimize your manufacturing processes in terms of quality and economics.
However, only well-prepared and analyzed data leads to process knowledge and, finally, to process control and continuous improvement. Thus, a robust and efficient data management/data analytics strategy is one of the most valuable concepts for the process industry. The data analytics strategy defines how to:

  • conduct data management for process development and manufacturing
  • efficiently analyze the relation between process parameters and product quality as well as key performance indicators
  • develop platform knowledge by data analytics and mathematical modeling to continuously improve manufacturing platforms

Roadmap: How to develop your data management

Step 1: Stakeholders and User Requirements Specifications

Poorly handled evaluation efforts create serious issues during every step of your implementation. Proper conceptual preparation is key since ill-defined requirements may lead to delayed completion. Get input from all stakeholders: from IT, process development, manufacturing science to quality and operations. You should carefully check all legacy systems to be integrated and which data analytics functionality is required. Systems interfacing to bioprocess data management and analytics platforms should also be examined. These systems include:

  • Process Control Software
  • Laboratory Information Management Systems (LIMS)
  • Electronic Lab Notebooks
  • Historians

The right implementation strategy ensures that you are better prepared by maintaining focus on the original scope of your project and guarantees that your employees are properly trained and prepared. Designing a user requirement specification involves mining relevant data streams and classification in relevant and nonrelevant data streams regarding your company's KPIs. But don't forget that data management is not an end in itself: Carefully evaluate your data analytics requirements that you envision to reach your goals.

Step 2: Executing Implementation

Implementation can be executed as a single-step implementation or step-by-step implementation. The single-step Software Implementation can be ideal for smaller operations and businesses with up to 100 users. All users are required to migrate to the new system at once. This allows you to focus on your project scope and implementation parameters by offering simple and straightforward handling of your processes.

Migrating to a new system step-by-step allows you to implement certain key features earlier while ensuring that possible complications are isolated from working processes. While this approach is more flexible than the single-step implementation, it may take longer. You can find more on data management and analytics implementation strategies here

Step 3: Data Migration

The proper handling of data migration is another important aspect to consider. Evaluate data migration from all sources (legacy databases, spreadsheets, paper-based recordings, etc.). For paper-based documents, evaluate technologies such as optical character recognition (OCR) and document crawling. Migrating all available data into the new system leads to immediate user acceptance after successful data management and ensures working efficacy.

Roadmap: How to develop your data analytics strategy

The main workflow for process data analytics can be summarized in the following steps:

  • Data alignment
    make all relevant data sources available for data analytics
  • Data mining
    mine relevant information to achieve your specific analytics goals
  • Data consistency testing
    test for consistency in the data set
  • Identify a hypothesis
    identify correlations/models using univariate- and multivariate statistics and build a hypothesis
  • Implement change or design an experiment
    dare to prove your hypothesis by implementing a change or design an experiment to prove your hypothesis

How to validate your software system in compliance with Part 11

The guideline of the U.S. Food and Drug Administration (FDA) regarding Electronic Records, Electronic Signatures, and Electronic Copies of Electronic Records is 21 CFR Part 11. The scope of Part 11 is limited to records that are maintained in an electronic format instead of a paper format.

Part 11 is necessary if you would like to use data management and data analytics software in a GMP environment, e.g. a (bio-) pharmaceutical quality department and especially for drug discovery.

Below you find the 7 main receivables for an FDA Part 11 audit:

  1. Validation
    All GMP relevant computerized systems have to be validated to ensure system accuracy, reliability, integrity, availability, and authenticity of required records and signatures.
  2. Audit Trail
    All electronic record changes, adaptions, events, or modifications have to be monitored.
  3. Access Protection
    System access must be controlled. It is mandatory to define the kind of system (open or closed system).
  4. Copies of Records
    The system provides a method to copy the audit trail in a human-readable format.
  5. Record Retention
    Electronic records should be stored, protected, archived, and provided by the system
  6. Electronic Signature
    The system has to provide the possibility to perform electronic signing just by trained and authorized users
  7. FDA Voucher
    A written voucher has to be provided to the regional FDA-office, to ensure the validity of the electronic signature

About Intravacc

Intravacc is a not-for-profit R&D organization. They develop and optimize vaccines, vaccine processes, and vaccine technologies. They aim to substantially reduce the development risks and costs of new vaccines to contribute to global health and equity in access to vaccines worldwide. They achieve their aim by developing and improving vaccine design, production processes, analytics, and technologies. In their state-of-the-art facilities, their experienced R&D institute takes your discovery up to Phase I/II clinical trials. Furthermore, they share and transfer their knowledge and technologies to public and private partners worldwide and work on collaborative R&D. Read more about their work here.

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