Quality control (QC) laboratories play a vital role in ensuring that pharmaceutical products are tested, verified and compliant with international standards of quality and safety. QC operations therefore are typically high-throughput and data intensive, in order to guarantee both research accuracy and integrity. Over the past few years, the topic that has dominated the conversations of many industries has seeped into the QC laboratory discussion. That is of course, digitalization. Yet considering the widespread changes these innovation projects will have on the operations of many QC laboratories, there simply isn’t enough research on how innovation will alter general practices and procedures. To assess the impact, this article focuses on the findings of various qualitative research, drawing its conclusions from studies to pinpoint the overall impact automation, Internet of Things (IoT) and other software will have on QC laboratory operations.

There’s not a need to dwell on why digitalization initiatives are being implemented in QC laboratories. The simple answer is that as in other industries, disruptive technology offers a plethora of opportunities that in a globalized world, private research organizations feel pressure to capitalize on. The benefits vary from the reduction of reliance on manual labor tasks through automation, increased accuracy of high volume tasks, cost reduction, better compliance and transparency of results, to name a few. Also worth noting is that in many cases digital technologies and the standards underlying them are already present in the practices of QC laboratories. 

The QC laboratories of today require an environment that encourages compliance, standardization and accuracy. By implementing comprehensive, autonomous and eventually intelligent infrastructures, working in QC laboratories becomes more streamlined and efficient.

Electronic lab notebooks (ELNs) and other documentation software are readily available on the markets and have reduced reliance on paper-based processes in a move to improve data accuracy, integrity, and security. Storing research on a digital platform makes sense for a lot of QC laboratories as it not only gives teams greater oversight over projects but also provides the foundation for further digital implementation. Some ELNs have built-in FDA compliant verification processes, some have standardized operating procedures that facilitate the day-to-day tasks of a QC laboratory operator. A McKinsey & Company article stated that “an average chemical QC lab can reduce costs by 25 to 45 percent by reaching the digitally enabled lab horizon”. Ultimately, QC research is especially suited to digital initiatives as their work environment thrives on the very features digital software offers.

However, a digitalization strategy for QC laboratories goes far beyond a documentation solution. It means creating an entire ecosystem of smart technologies that connect a QC researcher with their equipment, whether that be a centrifuge, a fridge or even a set of scales. It requires a form of Internet of Things (IoT), a combined solution that provides both laboratory automation and monitoring. In order to construct a successful digital strategy, change management needs to be considered.

As Bharadwaj et al emphasize, there are four elements to digital business strategies that lay the foundation for success, one should consider: “(1) the scope of digital business strategy, (2) the scale”-”(3) the speed”-” and (4) the sources of business value creation and capture in digital business strategy”. Translating this into the QC laboratory context, it is first important to establish the extent of the digitization project and what the desired goal is. Secondly, one must decide what processes should be digitized, i.e. whether this also includes streamlining inventory management. Next, what is the timeline for action, including onboarding team members to the new system. And finally, how to best maximize the new systems in place and track how the changes have helped or hindered practices and procedures within the QC laboratory.

The introduction of IoT technology into the QC laboratory environment will no doubt be disruptive. It’ll mean incorporating digital components into workflows to increase the connection between researchers and their equipment. As aforementioned, IoT software uses a combination of automation and monitoring. Standards in many ways lay the foundation for successful QC laboratories and the transfer of high-volume tasks to automated solutions has been shown to reduce errors, thereby increasing accuracy.

Automation reduces sampling and other logistic tasks. Having a fully automated system of robots, cobots or larger advanced automated solutions streamlines repetitive tasks such as pipetting. As McKinsey & Company emphasize: “improved agility and shorter testing time can reduce QC-lab lead times by 60 to 70 percent and eventually lead to real-time releases”. When combined with laboratory monitoring which can be used to record environmental changes, the laboratory ecosystem becomes information-driven. The collection of additional data such as temperature changes can be used to pinpoint optimal conditions for experiments. As a result, the laboratory becomes a place where all data is taken into account, processed, and put to use.

In establishing the scale of digital transformation, it is important to plan for long-term development in QC laboratories. AI and machine learning are disruptive technologies that are advancing at a tremendous pace, and will revolutionize QC laboratory operations. Once the foundations have been laid with digital documentation and automated workflow execution, the natural step is to link everything together with an intelligent infrastructure that can ensure quality control by identifying quickly operator errors, deviations from the norm, and other components that could impact the reliability of results. To meet complex regulatory requirements, it’ll become necessary to enhance automation and monitoring capabilities with AI, as then the laboratory ecosystem will be truly connected, transformed to be in the position to ensure the best quality management and oversight.

AI systems could also be used to automate tasks that previously relied upon the expertise of staff – of note is that this will not make their job redundant, but instead allow greater flexibility within a team that is capable of carrying out tasks assisted by AI. It is not difficult to envisage a more connected environment, whereby work can be completed remotely and at the optimal time instead of in accordance with the busy schedules of QC laboratory operators.

As QC laboratories embark on the journey to Laboratory 4.0, it is still important to acknowledge the significant financial costs of implementing IoT solutions which could cause delays to digitalization projects. Thus, beforehand it is crucial to have a vision, strategy and timeline of adoption. While initially expensive, implementing such technology can deliver a strong return on investment, and shape the way QC laboratories operate for years to come. In order for there to be value in the adoption, there needs to be a structure in place to ensure that all members of the team can be onboarded with the changes. McKinsey & Company emphasize this, stating that “a poor rollout can cost five to ten times more and take three to five times longer than a properly planned and executed investment”. Therefore, if the benefits of digitalization are to be maximized, QC laboratories seeking to start with this process must set appropriate goals, hand-picking the best solutions for them, in order to yield the best results.

With these latest technologies, QC can be made more efficient, agile, and compliant. Using automation, monitoring and eventually, AI will create an ecosystem whereby pharma companies can turnover safe and reliable products in a smarter way.