Setting the Stage for Digital Biomanufacturing

Biopharma’s digital future is about the right technology—plus shifts in culture, strategy, and investment

Rana Sader
Rana Sader, MilliporeSigma

A seemingly unfathomable quantity of data is generated during the development, manufacturing, and quality control of biologics. Some data have yet to be digitized and continue to be collected and managed via paper-based systems. This limits the ability to search for information, collaborate effectively, respond to requests from regulators, ensure compliance, and gain important insights into processes to drive efficiency.

In other cases, analog processes have been digitized to make data easier to search, retrieve, share, and preserve in an archive. Regardless of whether data are analog, digital, or a blend of both, only a fraction is typically used to guide and optimize operations.

Lee Asplund
Lee Asplund, MilliporeSigma

As an example, while extensive process data are collected, only endpoint data are actually used in many cases, offering a narrow snapshot with which to guide decision making.

Digitalization necessitates the digitization of information. It is the process of enabling, improving, and transforming operations through the use of digitized data and technologies. Digitalization brings data together on a platform and contextualizes it so that it can be leveraged with various tools to model, predict, and understand processes. Trends and correlations can be revealed that otherwise would have remained hidden from view if the data were siloed and stored in disparate places across the organization.

When successfully implemented, digitalization can transform and accelerate decision making, lead to significant improvements in productivity, and support end-to-end supply chain integration. In its Digital Plant Maturity Model (DPMM), the BioPhorum organization envisions this journey as a series of stages from simple paper-based facilities to the fully automated and integrated “adaptive plant” of the future. The adaptive plant is also known as the “lights out” smart manufacturing plant.

Digital tools enabling transformation

Every bioprocess step and unit operation generate a massive amount of data at an incredibly fast rate, which in many cases is stored in multiple, disparate systems. While information flows into and out of these siloed data stores, it may never converge in a truly integrated manner, contributing to the difficulty in leveraging the data to inform and guide decision making.

Many digital tools are being developed to enable this convergence, providing access to more data, more rapidly, and with greater context. With such tools, data become increasingly connected, actionable, and intelligent. This enables deep process insights and understanding, data-driven decision making, as well as greater speed and agility, setting the stage for next-generation manufacturing.

Software is now available to support continuous process verification (CPV) by collecting, aggregating, and providing access to all data generated throughout a connected biomanufacturing process (Figure 1). In addition to CPV, some software offers data visualization, analytics, and process monitoring. These features enable bioprocess lifecycle management, reporting, and investigations.

Figure 1. Bio4C™ ProcessPad
Figure 1. Bio4C™ ProcessPad software efficiently captures data on a single platform, allowing it to be contextualized and used for improved process understanding and control.

Such software intelligently combines process data from batch records, enterprise resource planning systems, manufacturing execution systems, laboratory information management systems, data historians, process equipment, and manual sources into a single, validated data source.

By applying historical data, one can establish what is known as a golden tunnel or golden reference profile for a batch. This is a holistic view of a connected process—from start to finish—in which critical process parameters have values that enable the process to generate a product of the desired quality and quantity, and that define the boundaries of the process.

Input includes the maximum values allowed for up and down deviations as well as actionable deviations. Critical process parameters can then be monitored in real time, with the golden tunnel fitting within the actionable values.

Predictive analytics tunnels that are built across multiple steps of a process define the significant impacts at each step and can be used for process troubleshooting. As the process is ongoing, a live golden tunnel dashboard predicts whether the process will remain within the allowable tunnel boundaries based on current data and averages from previous steps.

If a deviation occurs, these real-time analytics offer the opportunity to intervene several steps ahead of time, and if that is not possible, fail the batch sooner, minimizing the financial impact.

Software can also assist with non-
conformances or process discrepancy investigations by providing single-window access to relevant charts, graphs, and tables. Access to such a comprehensive set of information accelerates and facilitates root cause identification and corrective and preventive actions (Figure 2).

Figure 2. Bio4C™ ProcessPad
Figure 2. Bio4C™ ProcessPad software can help answer key questions such as what, when, and how a process deviation occurred.

Digital transformation success factors

Digital transformation is not solely reliant on adoption and implementation of advanced technologies. It requires shifts in culture, strategy, and investment to liberate and leverage vast quantities of contextualized data. Among the factors that are critical to a successful transformation are standardization, accessibility, and upskilling.


The standardization of digital technologies across the biopharmaceutical industry will be essential. This begins with the development of solutions that will allow for seamless integration of new technologies with existing infrastructure and legacy systems. A core, near-term requirement is plug-and-play modularity.

In the future, technologies such as mobile robots will have to be vertically integrated and connected into the production floor’s automation system and the facility design itself.

The highly competitive nature of the biopharmaceutical industry may prove to be challenging when it comes to standardization, however. A balance must be struck between the aspects of a drug company that are unique and competitive, and those which enable the ability to collaborate without impacting or eroding competitiveness and the industry’s collective ability to excel.

A lesson in standardization can be drawn from Apple and the strategic decision to move away from its proprietary Lightning connectors to universal USB type C devices. With all the differentiated benefits offered by their products, Apple didn’t need a proprietary connector; some components could become universal.

Accessibility and upskilling

Not only do vast quantities of data need to be contextualized to maximize utility and value, but the data must also be accessible to users with a wide range of skills and between organizations and partners such as CDMOs. It is essential that the tools implemented during a digital transformation are user friendly and easy to access for those with the proper permissions.

Digital transformation also demands that organizations and end users think and work in new ways, embracing what digitized data and digital technologies can offer. Holistically, the biopharma industry lacks the necessary skills in this area as process engineers and scientists don’t typically also have IT degrees; as such, we need to draw experts from other industries and invest in upskilling the collective biomanufacturing workforce.

The need for upskilling was emphasized in “Rewired to Outcompete,” an article published by the management consulting firm McKinsey & Company, which noted that “digital transformations are, first and foremost, people transformations.” They advise that no company can outsource its way to digital excellence, and each should invest in establishing a bench of digital talent.

The future is digital

In the coming years, digitalization will be well on its way to becoming embedded across the industry. Breaking down silos and contextualizing data to unleash powerful information and insights will deliver improvements in productivity and process economics. A variety of software solutions are available to help kick-start the digital transformation process in biopharma.

In addition to adopting new tools to enable digital maturity, drug developers and manufacturers must recognize the organizational changes that come with this transformation and be ready to move out of their comfort zones. Each company will grapple with numerous decisions that are related to culture, strategy, and investment. and that will either accelerate or hinder progress toward digital maturity. As an industry, we must also tackle important questions around standardization and accessibility and ensure that our collective workforce is able to take full advantage of this digital transformation.

This evolution won’t be easy, but the benefits it will deliver to the biopharmaceutical industry and to patients by way of access to medicines will be well worth it.


Rana Sader ([email protected]) is Director, Bioprocess Software Product Management and Lee Asplund ([email protected]) serves as Analytical and PAT Solutions Consultant, both with MilliporeSigma, the U.S. and Canada Life Science business of Merck KGaA, Darmstadt, Germany.