Bridging the Biopharmaceutical Manufacturing Digital Divide

Bioprocessing 4.0 stems from Industry 4.0, an international, strategic initiative aimed at driving manufacturing forward by increasing the digitization and the interconnection of products, supply chains, and business models.1 It represents an end-to-end connected bioprocess wherein all systems and equipment in a process are connected digitally, in an effort to control and improve processes through feedback loops and the application of artificial intelligence. At the core of this vision of an interconnected industrial model are data that need to be accessed and managed in a way that promotes efficient decisions and outcomes. Because of the need for real-time control capabilities in bioprocess workflows, Bioprocessing 4.0 relies heavily on integrated data management and analytics, modelling and automation, and edge-based computing for the vast amounts of data it produces.1

While many other industries, such as oil and gas, adopted Industry 4.0 models decades ago, the biopharmaceutical industry has been slower to adopt this paradigm shift, as bioprocessing is not binary and working with complex living cells generally involves a high degree of variability and makes measurement and performance predictions more challenging. However, biopharmaceutical manufacturers are being compelled to embrace Bioprocessing 4.0 owing to increasing market pressures to produce biologics in a shorter time frame without compromising quality or safety. Live biologics are susceptible to a multitude of factors that can affect their robustness and quality during manufacturing, and having systems in place to accurately track, monitor, and intervene is vital. The COVID-19 pandemic underscores the importance of Bioprocessing 4.0 and serves as a reminder that supplying the entire world with lifesaving vaccines and therapeutics in response to the sudden onset of a novel, highly contagious disease requires reliable, safe, and expeditious manufacturing that can only be aided by implementation of Bioprocessing 4.0.

The Data Life Cycle

The data life cycle begins when a process is developed and defined and continues through the release of the product to the commercial market. Data management, including collection, monitoring, aggregation, correlation, analysis, visualization, and reporting is typically executed in silos across various departments and teams with different functions and systems. The unification and transformation of this data into executable tasks and directives is typically an arduous, disconnected process. 

Biopharma core functions, including quality by design (product development, technology transfer), process analytical technology (PAT; manufacturing, testing), and continued process verification (CPV; monitoring, quality assurance) all create and consume data across the process life cycle. These data require investigation and monitoring, and the integration of data collected from a variety of both similar and disparate workflows, some digital in nature and others paper-based, which create significant inefficiencies. Aggregating data across these blended digital and analog systems and processes in a meaningful way is time-consuming and error-prone without a purpose-built platform designed by biopharma engineers.

Next-Gen Bioprocessing and the BioContinuum™ Platform

To meet current manufacturing demands and overcome industrial challenges, as well as to lay the foundation for future sustainable growth amid market uncertainty, key business drivers such as speed, quality, flexibility, and cost converge to create challenges that require smart, integrated solutions. MilliporeSigma’s BioContinuum™ Platform optimizes integration across these key business drivers through digital technologies and data management, PATs, and intensified processing with MilliporeSigma’s Bio4C™ Software Suite.

The Bio4C™ Software Suite allows for data transparency and manufacturing intelligence resulting in efficient, data-driven outcomes at the process and plant level. What distinguishes the Bio4C™ Suite from other platforms is that it was conceived by bioprocess engineers for bioprocess engineers — this is of paramount importance in optimization across the myriad of people, processes, and equipment involved in biopharmaceutical manufacturing. Bio4C™’s browser-based, intuitive interfaces allow for broad, globally collaborative teams to break through organizational silos and adeptly control, monitor, and analyze equipment, processes, results, and data — all in near real time. The Bio4C™ Suite offers a convergent, open digital environment that is as flexible and adaptable as the rapidly evolving productivity, process, and regulatory needs of biopharmaceutical manufacturers around the world.

The Bio4C™ Software Suite addresses organizations’ digital transformation needs through convergence of the four Cs — control, for management of unit operations; connect, to integrate across the process continuum, collection, as it pertains to data and advanced analytics for rapid process insights; and collaboration, including remote support and cloud services.

A key component of the Bio4C™ Suite is Bio4C™ ProcessPad — a next-generation data visualization, analytics, and process monitoring platform that ensures that data are current, complete, and contextualized throughout the product life cycle. Bio4C™ ProcessPad enables bioprocess life cycle management, reporting, investigation, and CPV seamlessly integrating process data from batches, enterprise resource planning (ERP), manufacturing execution systems (MES), laboratory information management systems (LIMS), data historians, process equipment, and manual sources into a single, validated, data source.


Bio4C™ ProcessPad Modules and Features 

Bio4C™ ProcessPad makes all critical bioprocess data readily available through data aggregation, management, visualization, and analysis. The intuitive user interface/user experience (UI/UX) makes it easy to learn and use, and, since it is browser based, there is no software to download, install, update, or manage. Bio4C™ ProcessPad provides security for sharing data, reports, and visualizations across global teams, and gives a common access between contract development and manufacturing organizations (CDMOs) and sponsors for robust collaboration.

Bio4C™ ProcessPad offers three modules for phased deployment planning. Bio4C™ ProcessPad Offline comes equipped with analysis and visualization tools created specifically for the monitoring and troubleshooting of batch biomanufacturing. It enables manufacturing organizations to execute capture, trending, analysis, investigation, and reporting of batch performance data for batch/run data via statistical trending, statistical quality control, process capability, and CPV. It provides multivariate analytics capabilities for selection of key process attributes for process optimization studies. 

Bio4C™ ProcessPad-RT collects, aggregates, and provides direct web browser access to near real-time streaming data from processing equipment spanning bioreactors, chromatography systems, buffer systems, and more. Visualizations include live plant utilization, time-range and batch overlays, and batch events or batch excursion analysis. This module provides additional capabilities for anomaly pattern detection in machine historical data sets, which in return saves a lot of time for operators during investigations. Bio4C™ ProcessPad-RT integrates and complements Bio4C™ ProcessPad Offline and is also available as a standalone module.

Bio4C™ ProcessPad Stab enables capture and trending of drug product/drug substance stability data and shelf-life estimation and is an add-on module to Bio4C™ ProcessPad Offline. 

Batch Data Analytics 

The batch data analytics in Bio4C™ ProcessPad are purpose-built to assess batch manufacturing processes that involve quantitative data, like process parameters, as well as qualitative data like events and textual information. Since Bio4C™ ProcessPad was designed by expert bioengineers with years of batch manufacturing data-analysis experience, charts and visualizations intuitively display events and textual information related to the particular batch in ways that are most useful to users. There are several applications of the batch data analytics feature, including lot genealogy analysis, which helps investigators instantly find raw materials, intermediates, or finished products that correspond to defective lots. Unit operations alignment is positioned on a timeline that correlates execution time context with a process event under investigation. It also includes control charts for statistical process control, which is useful for understanding process variability and intra- or inter-batch time-series data for comparing batch profiles within expected processing times. Compare groups allows for ad hoc data grouping for statistical comparison to identify substantial differences.

These analytic capabilities provide rich context into various trends, charts, and visualizations, combining all key data parameters in one window, making it easy to draw useful conclusions about process and product. Due to our browser-based UI, information is available on-demand for whomever needs access, and root-cause investigations, process monitoring and trending, tracing and tracking of buffer/media and product batches, outlier batch detection, cell culture profile comparison, and process capability assessment are all easily accessible.

Machine Data Analytics 

Bio4C™ ProcessPad’s real-time module provides direct access to streaming data from process equipment for real-time machine and batch data analysis. Process engineers receive actionable data for performing routine monitoring of batch profiles and troubleshooting. Many day-to-day tasks become exponentially simplified, for activities ranging from determining current stage or phase of the process batch, to tabular access, to execution stats like batch start time, end time, and batch duration. Engineers can also compute and compare utilization for overall equipment estimations, easily find process tags to overlay or compare parameter values within the time window of the non-conformance event or investigation and overlay current and historical batch profiles on a common time scale for easy comparison and benchmarking. Bio4C™ ProcessPad allows access to real-time extract data within batch phases, and engineers can compare phase data across batches, perform correlation of streaming parameters, align multiple batch events to compare and troubleshoot batch differences arising due to operational shifts in scheduled batch events, and generate batch excursion reports on both quantitative metrics like pH and concentration levels, as well as non-numeric qualitative parameters that include operators, phases, and events.


Process Data Integration

Bio4C™ ProcessPad’s advanced data connection tool can aggregate data for various batches, parameters, and unit operations from a variety of external data sources that include legacy Excel, SQL-Server, MySQL, Oracle and third-party web-services. Data can even be captured from manual paper records via Bio4C™ ProcessPad’s data-capture templates, transforming manual sheets into digital records. The platform is flexible enough to capture time-based observations, end-point performance data, textual observations and events, and qualitative batch attributes, such as column re-pack details, resin lot ID, assay results, assay stability sample results, and qualitative assay attributes. This helps integrate, unify, and optimize data related to batches, unit operations, and parameters. The data-capture template design is highly customizable, enabling the addition of any number of parameters by the system user without the need for any special IT skills or expertise. 

Stability Trending 

Testing for stability and trending for shelf-life estimation is important for engineers and scientists involved in biopharmaceutical drug development and manufacturing. Bio4C™ ProcessPad’s stability management console allows scientists to perform essential data management and analysis functions without the need to export data to external systems. Data-capture templates mimic the in-process test/assay data-capture format to ensure that there is no need for additional training for lab and QA personnel who are entering, verifying, and approving data. Users can flag protocol events, addenda, and method changes for better data correlation and quick compilation of protocol data, events, or addenda throughout the entire life cycle of the protocol execution. The stability module also comes embedded with an advanced statistics engine for predicting shelf-life for long-term storage conditions. All of the shelf-life prediction models designed for poolability of batches conform to statistical approaches mentioned in ICH-Q1E.

Reporting and Sharing 

Reports can be easily shared with relevant stakeholders, providing a forum for process insights. Using an aggregated and contextualized single source of truth data, Bio4C™ ProcessPad enables precise recordkeeping and data management, simplifies knowledge transfer, supports annual product quality reviews and process summary reports, and improves decision making on the plant floor, allowing for identification of opportunities for corrective and preventative action. Reports can be generated on-demand or scheduled on a daily, weekly, or monthly basis. The sharing feature is also helpful in collaborating with external parties where only specific information needs to be exchanged, and access to the whole application is not required. Global teams, CDMOs, and sponsors can easily share data and reports, avoiding time-consuming manual efforts, errors, rework, and potential supply chain and quality or compliance problems. Some of the built-in reports include manufacturing campaign reports, batch summary and run excursion reports, plant equipment utilization reports, and ad hoc reports in support of root cause analysis.

Compliance and Regulatory 

Beyond the need to integrate systems, processes, and people, regulatory standards and expectations for bioprocess monitoring and control are becoming more stringent. According to the U.S. Food and Drug Administration’s (FDA) Process Validation Guidance, “An ongoing program to collect and analyze product and process data that relate to product quality must be established. The data collected should include relevant process trends and quality of incoming materials or components, in-process material, and finished products.”2 The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) states in their quality guidelines that “Pharmaceutical companies should plan and execute a system for the monitoring of process performance and product quality to ensure a state of control is maintained.”3 As technology evolves, so do standards set forth by regulatory agencies, and it is critical that biopharmaceutical companies and CDMOs embrace tools that ensure safety and quality. Bio4C™ ProcessPad facilitates 21 CFR Part 11 compliance by meeting applicable requirements, including unique usernames and passwords, timestamped audit trails, and secure storage of all records. Bio4C™ ProcessPad also undergoes stringent internal validation and has a mature software development life cycle and quality software development practices. 

Future Market Implications

With the global biologics market projected to reach over $500 billion by 2027,in addition to the new reality of global pandemics such as COVID-19 plus growing market pressures for efficient, safe, effective, and efficient production of biologics, the need for seamless, modern, data-driven biopharmaceutical production continues to grow. In the absence of a structured process data management tool, engineers and scientists spend more than 80% of their time hunting and gathering data and only 20% of their time on quality analysis, leading to considerable delays in final corrective action. With Bio4C™ ProcessPad, bioprocess scientists spend as little as 15% of their time on data capture and over 80% of their time on data analysis, allowing for timely corrective and preventive actions, quicker release of quarantined lots under investigation, improved productivity, and better process monitoring — implementing Bio4C™ ProcessPad achieves significant times savings on data aggregation and reporting. Additionally, the Biophorum Operations Group (BPOG) estimates that using an automated data management system for CPV reporting across multiple sites can reduce manufacturing and capital expenditure costs by 90%. Bio4C™ ProcessPad’s collaborative and intuitive manufacturing intelligence tool provides an out-of-box solution for acquiring, aggregating, and analyzing data seamlessly across all facets of the biopharma manufacturing process, leading to increased quality and reduced costs and timelines.


  1. Demesmaeker, Mark; Kopec, Dan; Arsénio, Artur Miguel. “Bioprocessing 4.0—Where are we with Smart Manufacturing in 2020?” Pharmaceutical Outsourcing. 8 Sep. 2020. Web. 
  2.  “Process Validation: General Principles and Practices.” U.S. Food & Drug Administration. Jan. 2011. Web. 
  3. “Quality Guidelines.” International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. Web. 
  4. “Global Biologics Industry” GlobeNewswire. 2 Dec. 2020. Web. 

Vikas Revankar

With over 20 years’ experience in the IT industry spanning both application and infrastructure management services, Vikas Revankar specializes in the establishment and management of high-performing, global software organizations. In his current role, Vikas leads a team of product managers, engineers, and data scientists as they develop the strategy and roadmap for software, automation, and analytics technologies. Vikas earned his Bachelor of Technology in Computer Science from Dr. Babasaheb Ambedkar Technology University and his MBA in Software Enterprise Management from the Indian Institute of Management, Bangalore.