Pharmaceutical industry 4.0: improve performance through data analysis and digitalisation, and rethink GxP management

To meet these issues, one of the challenges for the pharmaceutical industry is the structuring and aggregation of data to be able to know the detailed history of a production batch at a sufficiently fine scale.

Our tools allow our customers to collect their data directly from their industrial information systems and to combine them with data from business systems (PGI, LIMS, MES, etc.).

In this way, our clients can:

• combine their data to transform them into relevant information (e.g. sterilisation schedule for a production batch automatically calculated from timing data and on-line temperature measurements; calculation of yields per batch, per product, etc.),
• use their data to control their process parameters with statistical control charts and thus control the quality of the finished product and meet the regulatory requirements for monitoring production processes,
• improve their productivity by monitoring the OEE of their lines by capturing a maximum amount of information on the equipment to automatically qualify the causes of stoppages, under-cadence, etc.
• implement monitoring summaries by production batch (EBR, Electronic Batch Record) with all the critical parameters, and a validation process by batch for simplified traceability. Thus, the treatment of a non-conformity or an incident on a batch is drastically accelerated by having all the necessary information on the life of the batch at hand.

From the reception of raw materials to the packaging of finished products, through the transformation processes (fermentation, extraction, purification, synthesis, mixing and formulation…), our solutions make it possible to respond to the various challenges of the plant by simplifying the use of data.

We have worked to develop our solutions so that they can be easily implemented in a GMP/GxP context thanks to functionalities that meet the requirements of Gamp v5 as well as the needs of qualification activities. In particular, the configuration of our solutions has a 100% audit trail, and our data storage systems implement strategies to meet ALCOA+… Our ambition in this area is to make operation in a GxP environment more agile.

To go further, our clients can take the next step thanks to our solutions with an approach that combines the flexibility and agility of a field approach while capitalising on the company’s business, process and data experts:

• A field approach that provides process engineers with powerful yet simple tools to better understand the variability of their processes. They can thus reinforce the level of control over certain parameters that generate non-quality.
• A “data” approach that allows data scientists and data analysts to save time both in the constitution of their datasets, to make their studies and their models, but also to be able to rapidly deploy their models thanks to the Python code execution capabilities of our solutions.