Is Quality Management redundant?

What are the influences on Quality Management today? And what does the future hold for Quality in the era of smart automation? Late last year, James Kelleher, CEO of Generis, chaired a discussion of experts from Merck, Syneos Health and Accenture.

Taking part were:

• Dr. Heiner Niessen, Head of Application Technology Quality & Compliance at Merck
• Peter Brandstetter, Quality and Regulatory expert at Accenture
• James Man, Quality subject expert and R&D Advisory Managing Director at Syneos Health.

Here are the edited highlights.

Is the era of Quality Management over?

The panel first looked at where Quality is heading in the life sciences sector. James Man of Syneos Health said the activity could now be more embedded within everyday operations and improved incrementally, and Peter Brandstetter of Accenture agreed. “I think companies will reach a point where they don't need Quality Management or people working in Quality,” he suggested. “When everything is digital and automated, Quality Management loses its relevance.”

At the coalface, the situation looks more complex, however. Merck’s Heiner Niessen said he believed Quality demands were actually increasing, as more parameters are measured and the responsibility for Quality extends along the supply chain.

Yet this, in turn, increases the urgency to address the manual burden. “There’s an opportunity here,” Brandstetter said. “The more we learn about the manufacturing process from all of the data being collected the better we can predict it.”

Here, the smart use of technology offers considerable potential – for example in managing information from different sources. As Merck’s Niessen put it: “With improving digitalisation, it’s much easier to capture and track this information, right out into the real world.”

Humans lead, informed by technology

The idea of smarter technology use and automation can make teams fear being sidelined, or concerned about whether they can trust technology enough to let it take over from human vigilance.

But James Man at Syneos Health said it is still people who make the decisions and if those decisions can be informed by rich data the outcomes are likely to be better.

It would be better to involve Quality experts more, he suggested. “Right now, there isn't typically a role of Chief Quality Officer – but perhaps there should be,” he said. “For Compliance to add value to the business, there will need to be structural changes - beginning with representation.”

Train the human, or train the algorithm

Machine intelligence already plays a role in Quality management at Merck, albeit in limited areas, and Niessen suggested that with AI, Quality considerations are similar to those already in place.

“Either you train the human being, or you train the algorithm,” he said. The critical requirement, though, would be that the algorithm’s own decision-making process is transparent.

Syneos’s Man suggested that AI/machine learning might offer potential in the context of individualised/personalised medicine and Quality Management – to keep track of oversight and do this more cheaply/less manually.

“If AI can be applied as a learning tool, I see potential for collectively improving capability by identifying near misses and so on,” he said.

Niessen noted that when very low quantities of a product are involved, the need for greater efficiency with quality management grows, given that there will be as many quality control measures as there are personalised products.

The cost of Quality

So, should companies just accept that Quality costs will rise as data and parameters increase, or should they become better at reducing effort and containing cost, asked Generis’s Kelleher?

With huge pressure on the industry to reduce the cost of drugs, companies need to contain costs wherever possible, the panel agreed. Also, from a health insurance perspective, as outcome-based reimbursement becomes more established, the cost of Quality does become a factor, Accenture’s Brandstetter added.

What does the future hold?

To wrap up, Kelleher asked what concrete steps companies could take between now and 2025 to move closer to their goals.

Merck’s Niessen pointed to the corporate imperative to connect individual quality systems across the value chain to enable seamless data transfer. “So you would have your CAPA system, your RIM system, your supplier RIM system all acting more or less as one system,” he suggested.

Accenture’s Brandstetter concurred that there needs to be more structured data that’s exchangeable across company borders. Blockchain could help here, he suggested - enabling a trusted chain of data.

However, the panel were uncertain whether the role of static ‘documents’ would diminish.

“The way we access and interact with documents is here to stay,” said James Man. “But we should connect Quality systems, and a Chief Quality Officer function will be important. Embedding Quality people in the key R&D teams will happen. Achieve that, and you might be piloting more real-time data exchange with the regulators by 2025.”