The digital transformation of biopharmaceutical manufacturing has continued at a rapid pace as companies mine the rich sources of data available. The requirement for more people to maintain ‘physical distance’ during the coronavirus pandemic has helped to further fuel interest in digital solutions as companies sought to avoid delays and disruption to development, production and distribution. Innovations that enable data capture and review include predictive analytics, big data analytics, and building upon the digital plant. These forms of digital transformation offer mechanisms to revise its business model, to improve production processes, to design new drugs faster by using artificial intelligence (such as to screen compounds), and to increase responsiveness to customers. Furthermore, the volume of data processed by pharmaceutical firms shows no sign of slowing down. This means pharmaceutical companies must continue to act quickly in terms of building core internal digital capabilities and moving beyond their traditional IT functions to all areas of the business.
It is not only pharmaceutical companies who are driving digital technologies, there are expression of interest from regulators as well, as with undertaking more assessments of new products and clinical trials through digital portals. Perhaps the most important step is the U.S. FDA’s embracing of new methods to enhance the safety and security of the pharmaceutical distribution supply chain under the Drug Supply Chain Security Act (DSCSA). The continual application of the DSCSA initiative is intended to enhance the security of the pharmaceutical distribution supply chain and evaluate any pilot projects conducted prior to enactment of the law.
One example of a new technology that was piloted and evaluated through the process was blockchain. Blockchain is software that provides a digital ledger system for records and log transactions, by grouping them into chronologically-ordered blocks. This makes it ideal for tracking supplies and ensuring that required storage conditions have been achieved and that goods have not been tampered with. Based on success stories relating to other sectors of the economy like financial services and energy suppliers, blockchain became seen as a suitable technology to meet the DSCSA requirement for an interoperable, electronic tracing of pharmaceutical products at the packaging level. This was demonstrated through a pilot program run jointly between IBM, KPMG, Merck and Walmart, who worked closely with the FDA’s DSCSA pilot program. This is leading towards wider adoption in 2023 once the DSCA requirements for medicinal distribution come into force and with it the necessity to demonstrate full unit level traceability across the supply chain.
To facilitate blockchain, competing solutions are available, each of which seeks to integrate directly into a healthcare company’s existing global infrastructure. These integrations allow for the secure exchange of critical and confidential information with authorized partners in an open, interoperable format. the final 2023 DSCSA deadline requiring full unit level traceability across the supply chain.
Outside of regulatory drivers, a number of pharmaceutical companies have been exploring other innovative technologies.
Digital analytics for process improvement
Digital analytics can support a range of process improvement measures, such as lean six sigma, predictive maintenance, and process optimisation. As an example of this in practice, GE Healthcare operates a digital data exchange collaboration program with another manufacturer, Amgen. The aim is to use data analytics to better understand the relationship between raw material variability and process performance during manufacturing. What can be leveraged from such analysis are better ways to ensure consistent and predictable biomanufacturing performance. The collaboration rests on the efficiency of the data exchange capabilities between the two companies, as well as their willingness to share data.
Creating the digital company
The “digital plant” and technologies that go along with digital transformation, such as robotics, data analytics, artificial intelligence, and the industrial Internet of Things (IoT) can deliver greater efficiency. For these reasons, Eli Lilly and Company advanced the implementation of these technologies to its pharmaceutical manufacturing organization.
The digital plant can accelerate improvements. For example, technology can reduce ergonomic risks through robotics lifting boxes and ensure quality through real-time analytics rather than after-the-fact testing. These technologies can also drive cost efficiencies. Of the different digital transformation tools, robotics and advanced analytics are seemingly the most mature and thus the ones that will be easier to implement in the shorter-term. A related area is with automation, such as robotic process automation, machine learning, and smart workflows, designed to simply and standardise tasks by avoiding errors and accelerating the execution time by removing the human from certain aspects of the operation.
Predictive manufacturing seeks to move from the reactive to the proactive by being predictive. This concept applies to maintenance, in terms of being both lean (avoiding unnecessary maintenance) and proactive (addressing maintenance before failure is expected to occur). The approach also enables process range adjustments to take place.
An example of predictive manufacturing is with Teva Pharmaceuticals Industries, who worked with Insilico Biotechnology to apply predictive biomanufacturing processes using real-time data to Teva’s manufacturing processes. The aim was to create more efficient production processes.
Such technology assess the vast quantities of data generated from bioprocessing. By being able to satisfactorily review this data presents new opportunities for solutions to improve manufacturing operations based on predictive biomanufacturing. The focus is with optimizing biologics production processes through the use of computational simulations.
Augmented reality involves the pairing of digital technology with objects that reside in the real-world to enhance the operation, improvement, or maintenance of the objects (by object, this can be a single item of equipment or an entire process). An example is with the Tandem 4.0 platform, designed to assist with pharmaceutical operations by using augmented reality. The technology can be deployed in the laboratory, on a manufacturing line, and or within cleanroom environments. Through this system, users can connect globally and engage in problem-solving in real-time. The aim is to assist organizations with avoiding process deviations and to help to prevent manufacturing delays.
Whereas virtual reality immerses the user in a fully artificial computer-generated environment, augmented reality overlays virtual three-dimensional graphics on the real-world environment. The aim is to ‘augment’ the way users view everyday life (or work tasks) and, in doing so, reveal more information. The platform also allows for customized user menus, plus there is the facility for voice commands. The use of voice can be switched on to guide users through each processes step. The platform also permits single- or multi-user drawing annotations to be made on any captured image.
Image capture also allows for remote and live support. Here experts can help to bring attention to a specific aspect of a machine that is showing a process or performance machinery. This works by remote experts dropping three-dimensional augmented reality arrows into the real-world environment back in the pharmaceutical facility. As well as using the platform directly, users can stream sessions from smartphones or tablets.
The adoption of augmented reality in areas of complex manufacturing, like pharmaceuticals is becoming part of the digital strategy of many firms (a report revealed that 30 percent of Global 2000 companies have reported they are set to try out both virtual and augmented reality as part of their digital transformation strategies).
In pharmaceuticals this includes applications like visualizing physiological processes, or “handling” models of chemical compounds and molecules, as well as the assistance with helping review machine operations, as with the Tandem concept.
Augmented reality also paves the way for digital twins. These are virtual representations of physical systems and enable connections to be made between different locations and specialisms by using digital models. Acting as a virtual replica of the physical environment, a digital twin can be used in advanced ways to automate, optimize and connect systems. Digital twins can be applied to design and to assist with operations, such as providing real-time data about the condition of a process or an item of equipment; or extending to an entire system, building or town. An example is with bioreactors, by streaming data collected from sensors digital twins technology enables engineers to fine tune the fluid path without physically disrupting a cell line as the actual process is taking place.
The technologies outlined have disruptive potential and signal the future. Yet it remains that many biopharmaceutical companies will find it challenging to determine which technologies to adopt and which what initiatives to scale up and how quickly. For others the costs and development times can appear prohibitive. This may change as roll-out increases and costs lower. Nonetheless, the digital success take time to come to fruition, and there will be misses and well as success. Important lessons can be drawn from other industries. These include developing a digital transformation agenda; ensuring the projects are shared across the organization and not just retained within the IT department, and that a digital embracing culture is developed from within, beginning at the top in the C-Suite and ensuring that all functions buy into the aims and strategy of digital transformation.
Topics: Industry Trends