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COLUMNS
Advancing the Digital Transformation of Biopharma Manufacturing
Digitalisation can revolutionise the industry and reduce time to market by leveraging powerful tools like data and cloud infrastructure to introduce greater flexibility and efficiency in the manufacturing process. There remain key barriers, however, to industry adoption of digital tools but customisable technology solutions can enable even smaller biotechnology firms to embrace this change.
by Nicolas Pivet

Like other manufacturing industries, biopharma has embarked upon its own digital transformation journey known as Biopharma 4.0. The accelerated pace of drug development driven by the extraordinary demand for therapeutics has made it necessary for the biopharma industry to re-think and modify its manufacturing approaches and processes. The industry’s trajectory, however, is varied—dependent on the size, scale, and stage of maturity of organisations. The challenge remains in ensuring that all players recognise the need and capabilities required for a fundamental shift in digitalising the development and manufacturing processes for the industry to continue its core work of saving lives.

The Need for Digital Transformation

Bioprocessing 4.0, or the digital transformation of biopharmaceutical process development, delivers value across the entire product life cycle—from the manufacturing processes of new product candidates to regulatory compliance matters and market approval. Through the Internet of Things (IoT), biopharma manufacturers can leverage a network of data sources, materials, equipment, and users to develop an integrated manufacturing system that streamlines processes and enables automation. For the development and production of therapies, a digital approach has now become mainstream in response to manufacturing demands for greater reliability, efficiency, and flexibility, amidst regulatory barriers and risks. The industry’s pain points in this regard are understandably numerous—from delivering quality therapeutic products to ensuring the predictability of production batches and reduced time to market. Notably, the success rate of drugs making it to commercial continues to remain low, which therefore requires greater agility in process development and manufacturing.

A variety of innovative technologies are available at the industry’s disposal to address these pain points and data lies at the core of these solutions, which include data lakes, digital twin technology, and virtual and augmented reality, just to name a few. Data lakes are critical storage structures comprising standardised aggregation and contextualised data that form the basis for digital applications in biopharma manufacturing processes.

Digital twins of production assets and processes can harness this data to allow for more efficient operations and flexible, agile process designs through virtual experimentation. A key outcome of digital twin technology is improved predictability of batch processes. By uncovering characteristics of raw materials, such as the cell culture media, the process can be modelled to manage variability in these raw materials, leading to consistent batch outcomes. In silico software simulation models enable industry players to skip the design of experiments and accelerate process optimisation. On the hardware side, “smart” hardware or equipment can maximise what is known as the overall equipment effectiveness or OEE, by determining the requisite equipment re-configuration for revised production.

The diagram above illustrates the application areas for downstream simulation throughout the bioprocessing life cycle.

Industry Preparedness to Adopt Digital Solutions

In spite of the benefits of adopting digitalisation tools and technologies, biopharma, unfortunately, lags behind its industrial counterparts in terms of digital maturity. According to the Digital Plant Maturity Model (DPMM), the industry stands between Level 2 and 3, out of 5, meaning that it has a long way to go to build facilities that are autonomous, self-optimising and allow plug-and-play.1 There is a clear need to accelerate efforts to significantly enhance process workflows and production capabilities of the industry or at the very least, acknowledge and address why the industry finds itself in this position.

Resistance to adopting digital practices is rooted in concerns over cybersecurity standards, which are a particularly sensitive area for biopharmaceutical firms. The COVID-19 pandemic challenged this scepticism and forced many players to open up to digital possibilities by connecting their equipment and machines to a network. With remote monitoring and controlling of machines being strongly encouraged to minimise on-site presence, the pandemic inadvertently managed to nudge companies towards trusting the cloud infrastructure.

For biotech enablers like Cytiva, this became an opportunity to play a part in shifting mindsets, starting with assuaging fears and reassuring its customers about contractual agreements that protect data ownership. Aside from this, there are ways in which process data for generating predictive modelling can remain anonymised or be curated such that it provides hints about the behaviour of cells and the behaviour of the process without betraying any secret of the recipe of making a given drug. In other words, data can be engineered to make it non-sensitive from a competitive standpoint.

Biopharma can take reference from the medical device industry, where even 15-20 years ago, sensitive patient and disease data was being anonymised to allow remote service of critical machines such as MRI scanners in hospital settings. With this experience in data maturity, the medical device sector has been able to, more recently, leverage AI for the advanced detection of breast cancer through radiology imaging. The time is ripe for biopharma to catch up and follow a similar trajectory.

Prioritising Areas for Transformation

To match the level of industry preparedness, companies can determine their own priority areas for which aspects of digitalisation to adopt. When it comes to information technology, setting up a manufacturing execution system is key as part of the production cycle to capture and digitally record batch data. For automation, additional operational technology is required through sequencing end enabling data stored in the cloud infrastructure to run smart analytics and predictive models using statistical tools. This would be a recommended priority area to explore for the industry in terms of enhancing manufacturing capabilities and outcomes. Predictive modelling tools, in particular, are essential for companies to scale up, enabling them to redesign the process parameters for larger vessels of bioreactors.

The Asia-Pacific region has been particularly receptive to digitalisation in the industry. In Japan, for example, biopharma companies are seeking support to fully digitise their manufacturing records and intend to make use of data to help them optimise the yield on their cell culture batch. In virtual and physical trade shows in Asia, biopharma companies across the industry have shown great interest in digital and automation tools and technologies, and countries such as Singapore and South Korea have been ahead of the curve in terms of adoption.

China has been an exemplary case study for embracing remote technologies during the strict COVID-19 lockdown measures. This was made possible through the adoption of augmented and virtual reality tools and platforms (AR/VR technology). Advancement in AR/VR technology has led to its use in a number of application areas—from product training to sophisticated remote customer service. VR is becoming an increasingly integral part of product training during the handover phase. Traditionally, training was conducted face-to-face with the equipment and required different types of logistics and associated costs. VR tools can create a prototype virtually for users to interact with equipment that is life-size and can be designed to accuracy.

One of the more successful applications of AR technology is evidenced through Cytiva’s AR Online Centre in China. The technology, which includes an AR headset, was trialled in conjunction with a proprietary AR platform called OptiRun View to troubleshoot equipment malfunction or issues remotely at a time when on-site service was not possible during the pandemic. Through this technology, customers can be empowered to fix technical issues by themselves under supervision. In the event that the issue cannot be resolved, field service engineers will be deployed to troubleshoot on-site.

Beyond AR, more advanced solutions for remote services exist as part of Cytiva’s offering which involves IoT. The OptiRun Connect platform is linked to the customer’s machine such that it allows access and data transfer to address software or hardware failures through deep diagnostics. This solution is possible through cloud infrastructure by third-party provider Amazon Web Services (AWS), through which OptiRun Connect can link with data remotely to assess metrics and parameters to resolve maintenance issues. The time and cost savings arising from digitally enabled remote services for biopharma companies are significant, and for this reason alone, the industry should seriously consider actionable steps towards transformation.

Developing Capabilities Across the Industry

To take full advantage of all there is to offer in terms of digital solutions, biopharma companies would need to chart their own trajectory. There will be segmentation in the industry in terms of the types of technologies and products that the industry can adopt. Smaller biotechnology firms may not have anything digitised and may still be working on paper records and manual processes, whereas larger pharmaceutical companies are likely to already have strong cloud infrastructure and automated processes in place. The good news is that digital solutions can be customised and tailored to biopharma companies upon conducting an assessment of the digital baseline, where again the DPMM would be a good instrument of measure.

There is expectedly also a disparity in the manpower and skillset across the industry. Larger, multinational companies will have a dedicated automation team and a kind of role known as an automation engineer, whose skill is quite unique and specific to the sector. There is an issue, however, with the retention of such talent as career opportunities within the field in the given company are limited. This is where contract partners and Original Equipment Manufacturers (OEM) vendors come in especially for smaller companies, to offer technical and digital expertise for their manufacturing processes. For software solutions, the industry offers ample opportunity for experts such as software developers and engineers in the technology sector to become a part of innovation and the digital space to grow biopharma. The attraction and retention of talent for the industry, therefore, is very much tied to the pace of its digital transformation.

The biopharma industry is truly remarkable in what it has achieved over decades and the future is even more exciting as it strives to deliver therapeutics to improve patient well-being. Automation and digital transformation will only serve to propel the industry forward by ensuring more reliable and more efficient manufacturing processes which means that therapeutics reach patients faster, and at lower costs. In order to maximise its potential, the industry can and must be open to making space for digital solutions across the value chain, and partners across the value chain can work together to make this a reality.

References:

  1. BioPhorum. (2018, May). A Best Practice Guide to Using the Biophorum Digital Plant Maturity Model and Assessment Tool. Retrieved October 6, 2022, from https://www.biophorum.com/wp-content/uploads/bp_downloads/BPOG-DPMM-Best-Practice-for-Plant-Assessments-May-2018.pdf

Nicolas Pivet About the Author

Nicolas Pivet, VP, Global Services, Cytiva

Nicolas Pivet has been leading Global Services at Cytiva since 2017, driving sales and delivery operational excellence, digitisation of infrastructures and offerings, development of outcome-based customer solutions and strategic growth opportunities.

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