Digitalization is the use of digital technologies to change a business model and provide new revenue and value-producing opportunities; it is the process of moving to a digital business. (https://www.gartner.com/en/information-technology/glossary/digitalization) Never before has the benefit of digital businesses become as relevant as in the current pandemic crisis. While local grocers, hospitals, and traditional manufacturing are suffering from the worst economic circumstances in a decade, digital businesses like Amazon, Teladoc Health, and Zoom are registering record stock evaluations. The lack of timely transition to new business models has killed industrial juggernauts of the past, like Kodak and Nokia.
With the raise of machine learning, unprecedented business advantages are given to those who have all their data findable, accessible, interoperable, and reusable. Only recently, Google’s Deepmind has proven superior in predicting potential drug targets through application of their deep convolutional neural networks. (https://deepmind.com/research/open-source/computational-predictions-of-protein-structures-associated-with-COVID-19) With increasing health care offerings supported by Accenture and Mayo clinic, Google Cloud poses a definite threat to established life science companies. Higher management and executives apparently have understood this, as the main mantra and key goal of many lighthouse IT projects in today’s life science companies is about digitalization. Unfortunately, the definition of this term, its imminent impact, and the associated urgency remain often misunderstood and underappreciated by the relevant stakeholders in the companies. These stakeholders are focused on their current business needs, and while they can see some benefit in technology, their real-life problems and stressful schedules prevent them from seeing the large picture. This blog is intended to help those that find themselves wondering how digitalization is to be achieved and what benefit it will bring to their part of the organization.
Let us look at the common challenges of stakeholders in life science businesses that could be solved by today’s technology and think a few steps ahead. If problem A is solved, which problem or opportunity B will present itself. We will see that extrapolating only a few steps will merge all stakeholder interests in the same final outcome, the foundation of a digital business.
As examples, we will put ourselves into the shoes of a Laboratory head, a Quality Control manager, a Regulatory Affairs representative, and a Collaboration manager.
With erooms law (https://en.wikipedia.org/wiki/Eroom%27s_law) working against them, Laboratory heads are mainly interested in finding better, safer, and more cost effective drugs. In order to make good decisions, they need to be able to find and access all relevant information related to a specific project. In most companies, it is currently not possible to retrieve all digital information for a specific product through a simple search. Therefore, much effort is being spent on breaking up data silos and providing basic search and retrieval function to laboratories. Once this problem is solved, the desire will arise to not only find specific data sets, but also to interrelate them with other projects in the company. The idea to increase efficiency by making better decisions on which drugs to promote and which projects to stop will result in greater quality and higher throughput. This can only be achieved if data is harmonized and transformed into information by adding descriptive metadata. A main bottleneck of integrating information are the incompatible data formats that digital information is often stored in. Leveraging data standards like Allotrope (https://www.allotrope.org/) will enable future reuse of data. A set of well curated, long-term usable information packages is the foundation of any digital business. The path of the Lab head will inevitably lead to this stage.
Quality Control & Compliance Manager
Our QC manager has one major concern in a world of rapidly advancing technologies, that regulatory officials will require access to legacy data the company cannot provide. Warning letters are detrimental to any life science company and need to be avoided by all means. The main reason for warning letters issued during the last years is missing data integrity. While paper prints and file backup solutions have sufficed in the past, current audits require frequently access to reintegrable data. It is therefore an eminent challenge for QC managers to put into place archiving solutions that keep data in a fully compliant storage. However, once the problem of storing measurements will be solved, a new challenge can be foreseen. How can the process that lead to a specific released batch be made visible, and how can a drill down into the data genealogy be made possible? The ability to reconstruct on the fly a human readable process description and all relevant descriptive information will become the next object of desire. Standardized data models and process descriptions integrated into the data storage solution will form the basis of what can be coined a streamlined audit. No more mountain archive explorations or calling people out from retirement will be necessary. All information will be available with the push of a button. Consider the system necessary to achieve this, it has to collect, harmonize, store, and reprocess digital information. Similar to the Lab head, this system forms the foundation of a digital business as the logical destination for the QC Manager.
Regulatory Affairs Manager
A most crucial task on the path to bringing a product to market is convincing the regulatory authorities of the safety and effectiveness of a new drug. Wagon loads of documentation has to be prepared, in agreement with minute specifications that vary between the countries. Today, a plethora of data management systems needs to be consulted to retrieve all the information necessary to produce the desired submission documents. Unfortunately, these systems do not communicate well with each other and require much manual effort to operate. Therefore, it is one high priority item for all regulatory affairs managers to increase efficiency and reduce errors by automation of manual efforts in data digitalization and transfer between systems. A key component to ensure data integrity are so called master data systems that hold definitions of contextual metadata to be assigned to individual information packages. Every data package created needs to be tagged with a set of mandatory and optional metadata. If such automation is fully deployed the resulting data packages will be connected on their metadata level. This means that a foundation is laid for completely automatic creation of submission material. It is clear to see that the need for automation, coupled with connecting data, can result in substantial time savings during the submission process, which equals millions of dollars per day for a block buster drug. While the desired outcome is very different from the one of the Lab head and QC Manager, the enabling technology has many parallels and again provides the basis of a digital business.
Collaboration Manager have the responsibility to ensure that contract research organizations (CRO) and contract manufacturing organizations (CMO) receive and deliver information at highest quality. While it has been established practice for decades to subcontract parts of the drug discovery & development pipeline to third party companies, never before has the need for digital exchange of data been greater. With the previously described needs for standardized and well curated data from all other units in the organization, the Collaboration Manager needs to make sure that the CROs and CMOs submit data according to required standards. A secure data transfer is only the first part of the pipeline, even more important are automatic quality checks to guarantee data integrity and compliance. While these abilities are currently under development in many companies, it can be conjectured that the next big leap will be an automatic monitoring and performance scoring of CROs and CMOs. Such a metric, completely data driven, will enable life science companies to go beyond trust and identify the best partners in the industry. The gained transparency will result in cost savings and higher product quality. Furthermore, the system necessary to accomplish this data exchange, quality checking, and performance scoring will have to rely heavily on standardized and contextualized data packages. As in our previous examples, this will be the foundation for a data driven, digital business.
Every life science company has to successfully go through the process of digitalization or risks to be overtaken. While many stakeholders do not grasp the full picture, their individual interests will lead them to contribute to the foundation of a data driven business. If management encourages a synchronized effort to build a system capable of transforming the organization, all stakeholders will instantly gain valuable business benefits. We at ZONTAL believe that technology holds the key to unprecedented productivity. Together with our Top 20 Pharma partners, we have developed ZONTAL Space to guide your digital transformation, while bringing immediate business benefits to important stakeholders.