Pharma 4.0 – Taking pharmaceutical data into the 21st Century
The principles of ALCOA+ and data integrity are embedded within the culture of pharmaceutical manufacturing companies. There is now a shift in focus towards getting more value out of your data: trend analysis and automated systems, bringing the pharmaceutical industry in line with the concept of a smart factory to incorporate advanced digital elements into the industry.
Industry 4.0 encompasses automation and data exchange within manufacturing technologies, from cloud-based technologies to systems utilising automated computing technologies. Pharma 4.0 incorporates the ideals of Industry 4.0 to allow manufacturers to automate systems, and thus utilise this incorporation to advance the industry.
One concept being adopted by Pharma 4.0 is cloud-based technology for the entry and storage of data. Environmental monitoring systems such as SmartControl have adopted digital cloud-based systems to improve data handling. Some innovative pharmaceutical companies have already adopted cloud-based approaches as they allow continuous verification of data, with built-in data integrity systems.
The term “Pharma 4.0” was coined by the International Society for Pharmaceutical Engineers (ISPE), whose mission statement is to “manufacture pharmaceutical products with maximum product and process understanding, data integrity by design, efficiency and optimal resource allocation on the basis of full digital data transparency–to the benefit of the patient.”
Pharma 4.0 embeds regulatory best practices to extend the model provided by Industry 4.0 into the pharmaceutical industry. Put simply, this involves the replacement of manual processes with basic automated processes, and the inclusion of digital technology into the pharmaceutical manufacturing industry.
The aim is to improve the industry through digitalisation of resources, information systems and processes, and to change the culture within companies through better communication and decision making. These concepts can be supported through digital maturity, which allows the review and capture of mistakes and issues in real time. Automation and digitalisation of processes will ultimately decrease process variability, and increase consistency, thus improving product quality.
The Pharma 4.0 model turns digital maturity into what the ISPE call “data integrity by design” – the understanding that data integrity should be embedded in the entire process, from planning to implementation, to retirement of a system.
To help meet the data integrity requirements, guidance is encouraging companies away from handwritten paper-based records towards digital recording methods. This ensures regulatory compliance, aiming to embed data integrity into automated processes, and building bridges between the industry and regulators.
Automation of processes
A key part of Pharma 4.0 is the automation of processes within the pharmaceutical industry. Catching up with the Industry 4.0 ideals, many facilities are undergoing automation, aiming to improve speed, accuracy, and repeatability of processes. There are many procedures which are now being automated, from formulation and filling processes, to automated alarm systems and automated colony counters.
These automated processes require high standards to meet regulatory guidelines and ensure methods are being followed correctly.
Challenges with the introduction of Pharma 4.0
Uptake of digitalisation has been slower within the pharmaceutical industry than those within other industries. There are many reasons for this, but one of the major ones is likely to be the stringent regulatory requirements within the industry.
Introduction of new systems must ensure that compliance is maintained throughout the process, which must be assured through change management procedures. These change management procedures are often still based on legacy systems, providing additional hurdles for pharma companies to jump before digitalisation.
Introduction of new processes must undergo rigorous validation procedures, which are themselves highly regulated. Often the aim to ensure compliance can slow or halt process improvements.
What does this mean for environmental monitoring?
The pharmaceutical manufacturing industry, especially the Quality Control and environmental monitoring sectors, rely heavily upon legacy systems for the recording of results and information.
These systems are prone to data integrity flaws, relying on manual counting, recording and data transcription. Often within these departments there are large quantities of results and data, and the recording and storage of this data in multiple forms can lead to the build-up of data silos – multiple sets of data which may differently describe the same information.
Data silos can occur within the pharmaceutical manufacturing industry with large volumes of data being stored across different locations and tools. For example, results are often recorded on paper-based worksheets and then transcribed into legacy databases or spreadsheets for data analysis. Disparities in data can make the maintenance of data integrity more challenging, and lead to wasteful workflows.
Legacy databases and Excel spreadsheets are commonplace throughout environmental monitoring departments for storage of information and results. Not only are these systems difficult to read and analyse, but they are often not secure, lack thorough audit trails, and thus have significant data integrity issues. It can be challenging to review data and analyse results, making it difficult to have confidence in your data or to make smart decisions from this data. They often fall short of regulatory requirements with poor traceability and security.
Moving data to a digitalised format from the start, and integrating digitalisation into the system as a whole, can improve data integrity by design: data and information can be input into a smart system such as SmartControl contemporaneously, thus improving systems and moving them towards Pharma 4.0.
Get in touch to find out more about how SmartControl can help you meet regulation, improve data integrity, and take better decisions from your data.