When business reputations are at stake and customer health is on the line, reports Greg Hookings, Head of Business Development – EMEA, Stratus Technologies, pharmaceutical manufacturers (and the governing bodies that oversee them) look to validation protocols to ensure a safe production. So, what are the four types of validation for life sciences?
First proposed in the US by the Food and Drug Administration (FDA) in the mid-1970s, and now regulated in the UK by the Medicines and Healthcare products Regulatory Agency (MHRA), validation is the process of testing if something works as intended and proving that to the powers that be, whether they were there to witness it or not.
By collecting and analysing data from the design stage all the way to production, companies can establish evidence that their products — and the process used to create them — are of consistent quality. The result is compared against the expected outcome, which was decided before the validation process took place. Validation ensures that the product can be trusted by proving that every step along the way has been completed in the exact same (approved) way each time.
To achieve this, companies have to complete multiple types of validation that cover everything in a facility from the equipment itself right the way down to each component on a machine. Each form of validation is essential and can be brokjen down into four areas.
Prospective: Taking place during the development process and usually when a new product is being added, a manufacturer by this point has qualified all the equipment, has the right onsite expertise and has at least one batch completed.
This level of validation looks at each separate step of the manufacturing process and analyses any potential critical points, such as if the mixing stage takes longer under different temperature conditions.
Completing this stage of the validation process means that a manufacturer is now ready and approved to begin mass production … but not quite ready to sell to customers.
Concurrent: This validation level takes place during normal production to get an in-depth understanding of the process under normal working conditions. As with the prospective stage, each and every step of the process is closely monitored until at least three full, production-size batches have been completed.
Criteria for concurrent validation might include pH level monitoring, weight variation, dissolution time and colour analysis, for example. Reaching this stage means that the manufacturer has proven the process and can now start producing pharmaceuticals for customers.
Retrospective: Taking place after mass production, retrospective validation looks at the accumulated results from past runs. This only happens after the manufacturer has produced multiple batches under identical conditions. Assessing trends and deviation from normal operation, this type of validation is for established products already in the market. Retrospective validation gathers data from completed batches and historical production information to create a report.
Revalidation: This is an after-the-fact periodic validation protocol. It gives manufacturers another opportunity to check the process is continuing as planned and no unintended changes have occurred. Revalidation covers any changes to raw materials, replacement equipment, facility updates and increasing batch sizes.
These validation protocols are essential and necessary for safe pharmaceutical production, but the process does add extra strain and present challenges to manufacturers. Although these stages of validation will remain, the rules and regulations in the pharmaceutical sector are ever-changing and keeping up is an ongoing issue.
Big data
Pharmaceutical validation protocols produce big data that, when analysed well, can ease the strain on IT infrastructure. Latency associated with sending this data to the cloud can slow a manufacturer’s response time to issues, whether they are challenges associated with validation protocols or other maintenance issues.
There is also the issue of integration. Manufacturing facilities often have legacy hardware that makes it difficult to seamlessly integrate and produce the data necessary for validation protocols. Moreover, there is the challenge of workforce efficiency. Without a sufficient IT infrastructure in place, manufacturers must resort to time-consuming manual reporting, which opens the process up to human error.
Edge computing
A solution to many of the most pressing challenges associated with validation protocols is edge computing. Taking the capabilities of real-time data analysis and putting that computing power at the edge of the network offers huge benefits in pharmaceutical manufacturing.
The right platform will get to work filtering and processing the necessary data for validation protocols and this frees up the IT infrastructure from a big data strain. Analysis that is not time-sensitive is redirected from the edge environment to the huge processing power available in the cloud.
Real-time data analysis means faster decision making for the operators onsite. When running production batches to prove that they adhere to tough compliance regulations, every second counts. If an error occurs during mixing, a temperature warning or a machine maintenance issue occurs, a failed validation can result.
It’s important that an operator is not only alerted immediately but can take action right away, unburdened by having to call for IT expertise. Also, with the right platform in place, every operator can walk up to any machine and instantly get a report on performance and how this relates to validation protocols.
Pharmaceutical manufacturers turning to edge computing have the power to overcome the challenges associated with validation protocols. The real-time data analysis lets every operator on the factory floor stay updated whether they are ending or just starting a shift.
Companies don’t need to rely on laborious and manual reporting processes to sift through the mountain of data associated with validation protocols, edge computing can take that strain from the operator and IT infrastructure.
These benefits come without mentioning the added efficiency that edge computing offers. Even beyond validation challenges, pharmaceutical production can’t afford unplanned IT downtime. Any amount of system downtime can result in a decline in product quality.
This would be a brand damaging issue for many sectors; but, for pharmaceutical manufacturers, it could mean completely shutting down a production line and restarting. The right edge computing solution should offer the requisite 99.999 (five-nines) system availability that ensures the highest possible uptime performance of critical assets.
