Pharma - Case Histories

Process and Product Optimization case Histories in Pharma

Case Study: Knowledge Acceleration

Knowledge Acceleration Case History

CLIENT:
GLOBAL PHARMACEUTICAL COMPANY
PRODUCT:
DEVELOPMENT OF NEW ASSEMBLY PROCESS FOR A NEW DRUG DELIVERY SYSTEM
Needs:

  • Transfer the existing technology to a new CMO
  • Develop a second generation of the process in order to increase the manufacturing volume and increase the product quality
Actions:

  • Process mapping and modeling
  • Process knowledge generation and deployment

Situation

A global pharmaceutical company needed to transfer a semi-automated production line for a new drug delivery device to a new CMO, and meanwhile scale-up the process to a fully automated manufacturing line in order to increase yields and reduce risk of failure.

A preliminary assessment showed that all the necessary information was scattered in different departments at different levels of quality and detail.
There were weaknesses in documented design and process development which impacted their ability to extract information from the data. Due to this cumbersome process, it was not uncommon that knowledge would be lost during this unstructured approach. The client used many resources and man hours when trying to analyze information and needed a better way to review their data in order to accomplish their goals.

Actions

PTM Consulting used the Knowledge Acceleration service in order to increase the efficacy of information analysis. Using this approach, the client had the capacity to map the process on different levels of information (related to process itself, business objectives, etc.) and to validate this information in order to identify which was essential, significant and consistent. This service was extremely useful when different processes and activities with shared,
common information had to be considered and analyzed. The constructed solutions were reusable with future applicability as it allowed the Client to optimize other future processes and reduce costs.

Process mapping activities, conducted with our proprietary software, were used as a basis for the next phases of analysis and implementation which lead to
1) Better understanding of the involved processes;
2) Structured analysis of complex and multi-levels systems;
3) Identification of related risks.

Each macro-process was divided in phases and sub-phases, assigning inputs, outputs (e.g. product specifications), process/control parameters and mechanisms. Each element was codified allowing a complete traceability within the process mapping activity and for all the future use of information.
This traceability allowed us to identify:

  • Which information was related to which effect during the risk management process;
  • How this information was further related to the user requirements and validation test.

Process mapping was completed with the help of process modeling where information was linked through quali and quantitative connection using
statistical or risk management tools.

Use of the Knowledge Accelerator service allowed us to classify information according to different contexts. This allowed us to distinguish the
information as related to the process and product, or related to the quality system which was fundamental for the optimization of process transfer. For example:

Risks and mitigation actions related to the company quality system were identified classifying which were important for the new CMO. In this way the process transfer was simplified, transferring only the necessary information and avoiding redundancy. The same approach was applied on URs definition of the new optimized process, using a classification of quail-quantitative information related to the product/process in order to reduce the development time.

Results

We helped the Client transfer the existing technology to the new CMO and scaled-up the process to increase manufacturing volume and product quality. By collecting and mapping information, PTM Consulting was also able to help the Client minimize time for the following activities:

  • Quali-quantitative process risk analysis
  • Definition of parameters necessary for the development of Design of Experiments (DoE)
  • Identification of product / process /system requirements
  • Traceability of information through the risk documentation and URs