Driving Innovation and Efficiency in the Lab Through Digital Continuity

Lab Organization

Companies involved in product development rely on R&D innovation and process efficiency to drive success. Yet, efforts to improve in these areas are often hampered by poor data management strategies. Many rely on paper-based methods or disconnected legacy systems that serve to wall off data into siloes. Researchers need to have readily accessible, searchable data that allows for optimal design of experiments and collaborative efforts that drive innovation. Currently however, much experimental data is used only once, limiting its value and forcing researchers to reinvent the wheel for every experiment. Additionally, siloed or inaccessible data limits an organization’s ability to drive the kind of comprehensive business analytics necessary to improve process efficiency in the lab and across the enterprise. Inefficient and ineffective innovation efforts, along with poor process efficiency, can ultimately impact an organization’s ability to remain competitive. In today’s rapidly changing business and economic landscapes, successful R&D organizations are implementing new models that create pathways to accelerated product development, improved quality and compliance, enhanced customer safety, and reduced cost.

The digital revolution is rapidly changing the landscape for R&D companies. The old model of disconnected systems – LES, LIMS, ELN, SDMS, etc. – utilized at various places along the development process is slowly being replaced by a more integrated approach. Technology vendors are moving towards a convergence of technologies on a single platform. This brings together many of these disparate systems into an integrated solution that fosters digital continuity or a digital thread across the product lifecycle. Once this digital thread is established, process efficiency and innovation efforts become dramatically more effective. Truly, the technologies available today are causing many companies to rethink their entire business model. Let’s examine this concept of establishing a digital thread across the product lifecycle in detail in order to understand how it can be utilized to drive innovation and efficiency in R&D, and across the organization.

Digital Continuity

The digital revolution has made readily accessible information and data available from nearly every aspect of life, and this has served to dramatically accelerate the pace of change in our world and intensify competition amongst businesses. Successful organizations are now striving to integrate legacy systems and digitize all aspects of the product lifecycle in order to gain a competitive edge.

Legacy systems typically contain large amounts of useful information, but the lack of integration between these systems prevents companies from mining all the value available in their data. To develop a high-quality product that stays current and ahead of the competition, the data created across the entire product lifecycle must be accessible and capable of being shared amongst R&D, quality, compliance, manufacturing, and product teams. Digital continuity means that, from the original product ideation through the design, manufacture and service life of the product, all the data associated with the process is maintained and accessible to team members through a single platform.

For the purposes of establishing digital continuity, a guidance document published by The National Archives of the United Kingdom believes that companies should strive to make digital information available and usable such that one can:

  • Find it when needed
  • Open it as needed
  • Work with it in the way needed
  • Understand what it is and what it is about
  • Trust that it is what it says it is

Optimizing innovation requires that a digital thread be available on all aspects of product development and production, from R&D to manufacturing. Establishing a digital thread enables more effective business analytics, helping you answer important questions – what equipment is being used, what experiments are succeeding, etc. Digital continuity allows the effects of minor tweaks on the process to be tracked and cataloged, effectively supporting process optimization and innovation.

A digital thread throughout your process allows for complete data traceability, enabling you to see what has been modified along the way. This approach provides the ability to dig into all the details of your product line and manage and assess the impact of any changes in terms of product efficacy, cost, timelines and regulatory compliance.

Digital continuity is about making sure that your data from across the product lifecycle is complete, available and therefore usable for your business needs. With a single source of truth accessible through a platform that integrates all disciplines within the organization, companies can optimize innovation and process efficiency to accelerate the manufacture of industry-leading products.

Industry Examples of Digital Continuity

The automotive industry is one sector that has fully embraced digital continuity. In the car production process, the digital thread begins with the supply chain of materials that are used to build the car. The thread continues through car design and manufacture, and all the way to the consumer. When the customer buys the car, they have the option to choose features they want via an online catalog that details all the options. After purchase, the car company stays in contact with the customer, tracking and servicing the car over many years. In the automotive industry, digital continuity is available today – the digital thread flows from early materials all the way through to product use and the customer experience.

The practice of digital continuity is not as mature in the Life Science Industry as it is in other industries, however. The drug discovery process in the Life Science Industry is, in fact, the least traceable of any major industry. There are many reasons for this – an abundance of legacy systems that are difficult to integrate, change fatigue, fear of losing proprietary information due to lack of data security, regulatory challenges, and rapidly changing scientific capabilities.

Nonetheless, the pharmaceutical industry is undergoing major transformations due to innovation challenges it is facing. These challenges, along with a demanding external economic environment and growing market share of generic manufacturers, are taking a significant toll on both the short and long-term profitability of pharmaceutical firms. The promise of improved innovation and process efficiency is drawing many pharmaceutical companies to begin to explore the idea of creating a well-connected digital universe.

The goal for pharmaceutical companies is to be able to follow a digital thread from early materials discovery through to customer use. Digital continuity will allow life science companies to shorten the product lifecycle, reduce cost, better control quality and compliance, and reach the patient with more personalized care.

Modeling and Simulation

Advances in computational power have opened up the possibility of creating digital models and simulations that can dramatically accelerate innovation and reduce costs. Digital modeling and simulation are already being utilized extensively in several industries – automotive, aerospace, and energy, as a few examples. These industries rely on advanced digital simulations to test products before they are built in order to gain assurance that they will work as intended, while saving vast amounts on materials and scale up. Modeling and simulation allows companies to save costs and time by working in the virtual world to innovate and learn, and then only moving into physical when the model is ready to be verified.

Once an organization establishes a digital thread across the product lifecycle with trustworthy data, the data can be utilized to create models and simulations that will help scientists design experiments and screen materials. The digital continuity platform is utilized to create a digital twin of your process in order to optimize innovation and provide for better and faster decision making. Using proprietary company data to create models and run simulations generally will make those models and simulations much more relevant and powerful than simply using data from the literature or other sources, ultimately leading to better value for your organization.

As with digital continuity, digital modeling and simulation are not currently as extensively applied in the Life Sciences as they are in other industries. This is due to the complexity of modeling biological systems, insufficient scientific understanding of disease conditions, and lack of large amounts of real-world health outcome population data. With advances in all these areas, however, digital modeling and simulation is poised to transform the drug discovery process from R&D all the way to commercialization.

Medical device companies are leading the way in the Life Sciences with digital models now available for human bone, muscle, blood, and other tissues. One example of a useful digital twin created in the medical device industry is The Living Heart Project. In this case, a digital model of the human heart was created that permits medical devices to be safely tested in the virtual world before they are tried on real patients. Models such as this can be utilized for education and training, medical device design and virtual testing, clinical diagnosis and even for supporting regulatory approval. As a sign of the growing interest of regulatory bodies in digital modeling and simulation, the FDA has signed a five-year collaborative research agreement with The Living Heart Project in order to help bring this model closer to providing personalized and interventional cardiac-patient care.

Enabled by digital continuity, realistic modeling and simulation has enormous potential to transform healthcare – from improved patient education and physician training, to facilitating new innovations in medical devices, drugs and procedures. Demonstration of virtual efficacy may one day even be sufficient to gain regulatory approval. Examples of modeling and simulation facilitating a regulatory fast-track do in fact already exist – in the midst of an influenza epidemic in 2009, the FDA used modeling and simulation to identify and approve a safe pediatric dose of an experimental drug (peramivir) that had never even been clinically studied in children.

Continuous (Data-Driven) Manufacturing and Quality by Design

Another compelling example of digital continuity in action is continuous API drug manufacturing, which has been embraced by both regulators and innovative manufacturing companies and sponsors. At the moment, most pharmaceutical manufacturing is done using a multi-step batch manufacturing process, where batch testing is done on raw materials and products at various stages of the production process. With traditional batch manufacturing, one to two months can elapse from the time the manufacturing process is begun to the release of a finished product ready for sale.

In continuous manufacturing, the raw materials used to produce an oral drug are fed into a single, continuously running machine that features real-time release testing to create commercial-ready medicines in just one day. Continuous manufacturing requires a complex, real-time, multi-tier control strategy underpinned by a series of multi-variate processes and control models that control individual unit operations and interactions between them. For this reason, continuous manufacturing requires a complex, coordinated, integrated IT system which handles data and control mechanisms in real-time—a true digital thread. The nature of the electronic records and key data generated in the continuous paradigm are largely the same as in traditional batch processing, except that the underlying data and models required to support the generation of the data are much richer.

As described by the FDA in its PAT guidance document (21 CFR211.165), process understanding and control of critical quality attributes (CQA) provides a scientific, risk-based approach to justify real time release of drug product, and is potentially superior to laboratorybased sample testing in traditional batch manufacturing. Leveraging process understanding and real-time control of product quality to create drug products faster and cheaper are the key business drivers behind the continuous processing paradigm. Other benefits include:

  • More consistent product quality
  • Smaller equipment and high equipment utilization rates
  • Elimination of hold tanks and unit operations that do not provide value
  • Increased volume of production
  • More automation and less human interaction
  • Reduced inventory and storage needs

Conclusion

The digital revolution is providing a more integrated and effective approach to product development for R&D companies. By integrating formerly disparate systems on a single platform, companies are establishing a digital thread throughout the product lifecycle that is facilitating enormous strides in the areas of process efficiency and innovation. As companies establish digital continuity throughout their process, digital modeling and simulation are enabled that help to further reduce costs and drive innovation.

Although good examples of digital continuity exist in the Life Science Industry, this sector generally has a long way to go to catch up with other industries in this area. Given the benefits that digital continuity provides, however, leading Life Science companies are embracing this concept and moving forward with initiatives to digitize their laboratory and manufacturing processes.

Life Science companies that strive to implement digital continuity will gain a significant competitive advantage by improving their ability to deliver innovative, high-quality products to customers. In addition, the improved process efficiency that digital continuity provides will allow these companies to produce life-saving medicines both faster and more cost effectively. The digitization of our lives will certainly continue, and those companies that get ahead of this trend and incorporate a digital thread into their processes will lead the way.


About The Author 

Rob Knippenberg is a Managing Director for Astrix Technology Group in the Informatics Professional Services Practice.  He is focused on customer informatics solutions delivery through strategic partnerships with many of the top scientific software and services providers. Mr. Knippenberg brings to the role over 25 years of experience in scientific software project and program management, directing widely distributed global teams.  During his career, Mr. Knippenberg has worked with hundreds of commercial, academic, and government institutions delivering scientific informatics solutions to many thousands of scientists.