Pharma manufacturing going digital in bid for quality and efficiency22 Feb 2021
Digitalisation is finally coming to pharma with more drug manufacturers using industry 4.0 tech to monitor, model and control production processes.
The term industry 4.0 – the fourth industrial revolution - was coined in 2011 (1) by German researchers to describe the impact digital technologies are having on the manufacturing sector.
In the 4.0 model the internet of things (IOT) connects separate unit operations within a wider process, enabling data exchange, modelling and automation of control mechanisms.
The automobile and aviation industries embraced industry 4.0 early on, with Airbus’ (2) Skywise fleet management platform and Bosch’s (3) automatic braking system (ABS) production line being some of the earliest examples.
More recently pharma has started to adopt the approach, according to Simon Sprague from BCG, who says the sector has reached a digital tipping point as firms that have gone digital start to see return on investment.
“Companies have shown varying appetite to invest in Industry 4.0 technologies; our perception is that the vast majority are either in the process of piloting or scaling up successful pilots which have already been completed,” he says. “In many cases, the payback period for investments can be a few months to a year, so the right prioritised early investments can help to fund subsequent investments.”
Biopharmaceutical companies have shown a particular interest in digital manufacturing and industry 4.0 ideas, says Peter Crane, corporate strategy manager at bioprocess innovation specialist Synthace.
“Within bioprocess development there are a number of examples of companies developing strategies around data capture including on the vendor side and on the company side,” he says. “On the vendor side companies such as Insilico Biotechnology, Benchling, Riffyn, ExpuTec and Synthace all have solutions for the capture of data in bioprocess development environments.”
Crane cites his firm’s collaboration (4) with Oxford Biomedica – which used data to optimize a lentiviral vector transfection and transduction system for cell line development - as an example.
The perceived wisdom (5) is that pharma is slower to adopt manufacturing innovation than other industries.
The usual argument is that the rules governing drug production, pressure to cut time to-market as well as the potential negative impact of quality issues related to modified production processes have made the industry risk averse. In short, until recently, drug firms would only change when they had to.
So what has changed? Why are an increasing number of drug companies in both the small and large molecule space willing to invest in digital manufacturing?
One factor is increased governmental and regulatory support. In 2016, for example, a European Parliament (6) review team looking at industry 4.0 trends suggested “industries with a focus on high quality such as semiconductors and pharmaceuticals may benefit from reduced error rates.”
The reviewers also predicted competitive benefits, using the drug industry as an example. They wrote “manufacturers based in high labour cost countries can enhance their competitiveness by transforming their currently capital-intensive assembly lines into smart systems that can react to external and internal changes in product requirements.”
And on the other side of the Atlantic, 4.0 is also viewed as a positive. In January (7) then FDA Commissioner Stephen Hahn wrote about the agency’s efforts to foster innovation in pharmaceutical manufacturing.
He highlighted efforts to set “research and regulatory programs for advanced manufacturing, computational modelling, and other emerging technologies” citing industry 4.0 in manufacturing as an example.
Regulatory enthusiasm is certainly fuelling industry adoption of 4.0 ideas, according to Sprague, who also cites the emergence of dedicated process development and technology testing centres as a factor.
“When it comes to new approaches and new technologies, many pharma companies wait for clear signals from regulators before investing to any great extent, which shows the value of ‘digital demonstrators’ such as BCG’s collaboration with Dublin-based NIBRT, which provide safe environments in which to experiment with new technologies without risk to ongoing commercial production,” he says.
Drug quality is a related factor that is also increasing pharma use of 4.0 approaches.
Regulatory demand for data proving drugs are made in line with quality requirements have increased markedly in recent years. For example, in 2015 (8) the FDA set up its Office of Pharmaceutical Quality (OPQ) to standardize drug quality oversight. Much of the office’s subsequent work has focused on how industry can use innovative approaches to meet quality and supply consistency goals. (9)
This has encouraged pharma adoption of industry 4.0, Sprague says: “Digital manufacturing can bring great transparency to potential quality issues, helping to identify potential root causes on the basis of historical process data and accelerating the pace with which colleagues can be trained to ensure that quality issues are avoided.
“These improvements can invariably contribute to better quality outcomes which can only be a good thing for patients and regulators.”
Sprague cites the experience of BCG’s clients as an example, explaining “we have worked with a number of companies to identify, prioritise and deploy technologies in their operations across manufacturing, quality, engineering, and the end-to-end supply chain more broadly.”
Examples include IOT sensors that monitor operations that can predict process outcomes in real-time and even prescribe interventions to change and improve them. Sprague also highlights the use of RFID to track samples and equipment within the plant, use of advanced robotics and autonomous guided vehicles to reduce manual work, and use of AR / VR to accelerate training of operators as examples.
Industry’s ever-present desire to make production more efficient is also increasing interest in digital and 4.0 ideas in manufacturing.
Sprague argues that many types of new manufacturing technologies have been targeted at improving scalability and flexibility, including new modular technologies which allow for rapid scale-up of processes either through pre-fabricated units which can be constructed and validated offsite, and modular equipment which can be rapidly reconfigured in a rather empty ‘ballroom’ space.
He adds that many companies are deploying such technologies because they offer clear benefits in some cases.
In addition, drug companies thinking of switching from batch to continuous mode manufacturing are increasingly looking to digital technologies, according to Sprague.
“Another new trend is the move towards implementing continuous manufacturing, but this takes time and considerable investment given the need to qualify equipment, validate processes and upskill colleagues, so in practice it is being focussed on large scale products,” he says.
Peter Crane from Synthace has also seen interest in digital manufacturing increase as a result of the desire for efficiency. He highlights In Silico Biotechnology’s (10) use of its biological digital twin technology – digital models of production processes that can be used to test ideas - as an example, and Synthace’s use of digital twins (11) for high-throughput process development as another novel application of the approach.
Whether the companies investing in digital technologies will be able to take full advantage remains to be seen; however, those doing so need to ensure they take a holistic view of the process, Sprague says.
“It’s important to remember that just investing in the hardware, software and algorithms associated with digital technologies is not enough – to realise value, about 70% of the effort needs to go into change management and capability building.”
But for those that do go digital successfully, the potential benefits are huge throughout the supply chain and from manufacturing facility to pharmacy shelf, Sprague says.
“In terms of digital technologies, we see a number of potential avenues, particularly the use of advanced analytics to predict issues in one manufacturing area and the impact on other areas – in this way, adjustments can be made to mitigate and allow flexible actions to be taken.,” he says. “We have also seen some nice examples of the use of digital twins to model processes during scale-up, which can help to accelerate the move from clinical to commercial production.”
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