The Future of Quality Control in the Pharmaceutical Industry: Digitization, Automation, and In-Process Testing

Editor's Note:

In the Industry 4.0 era, the focus of emerging technologies has shifted from connectivity to advanced analytics, robotics, and automation; over the next five to ten years, these technologies have the potential to fundamentally transform every aspect of pharmaceutical laboratories.

The first QC laboratory to successfully undergo transformation saw its productivity increase by 30% to 40%, while comprehensive improvements reduced its overall quality control costs by at least 50%. Digitalization and automation can ensure better quality and compliance by reducing manual errors and variability, enabling faster and more effective problem resolution.

Case studies demonstrate that digitization and automation have reduced deviations by more than 65% and shortened deviation resolution time by over 90%. Moreover, preventing major compliance issues alone can save millions of dollars in costs. Furthermore, enhanced flexibility and reduced testing times can shorten QC laboratory turnaround times by 60% to 70%, ultimately enabling real-time release.

So, what does a pharmaceutical laboratory need to do to become a leader in the QC field?

Recently, the global management consulting firm McKinsey & Company released a report titled “Digitalization, Automation, and Online Testing: The Future of Quality Control in the Pharmaceutical Industry.” The report points out that although most advanced technologies are already available, few pharmaceutical companies have realized any benefits from them. To seize the opportunities brought by emerging technological advancements, pharmaceutical companies should act swiftly to leverage new technologies for transformation, thereby becoming industry leaders.

The following is a report compiled and translated by VCBeat (WeChat ID: vcbeat) reporters, mainly covering the following aspects:

I. Three Directions for the Laboratory's Future Development

II. Typical Factors Influencing the Successful Transformation and Value Capture of Pharmaceutical Laboratories

III. What Pharmaceutical Laboratories Need to Do to Achieve Transformation

Although most advanced technologies are already available, few pharmaceutical companies have recognized their benefits. On one hand, quality leaders often struggle to establish a clear business case for technological change, making it difficult for them to convince senior management that laboratory digitalization or automation can yield significant impact.

On the other hand, pharmaceutical companies rarely formulate clear long-term strategic plans and blueprints for their laboratories, leading to costly investments with limited tangible benefits. For instance, many companies have taken steps to first minimize the number of entries by simplifying paper records, then digitize laboratory test records to achieve paperless operations. Today, these initiatives are being replaced by smart, connected devices capable of directly transcribing thousands of data points without any manual data entry or review.

To seize the opportunities presented by emerging technological advancements, pharmaceutical companies should establish clear objectives, develop robust business cases for investments at different stages, conduct rapid pilots of new technologies, and then quickly scale up these pilots to generate meaningful results.

To achieve future success, pharmaceutical companies must also possess the foresight to make long-term strategic investments, including the development of novel testing methodologies and the agile adjustment of development plans in response to rapid technological advancements.

Various digitalization and automation technologies have created opportunities for the transformation of pharmaceutical laboratories. Most pharmaceutical laboratories have not yet achieved digital transformation, but they can target one of three directions for future technological development.

Pharmaceutical laboratories adopting new technologies willDigitalization, Automation, and Distributiondirection. Digital laboratories have achieved at least 80% paperless operations. These laboratories have transitioned from manual data entry to automated data transfer between instruments and general laboratory information management systems (GLIMS).

Digital laboratories leverage advanced real-time data analytics and continuous process verification to monitor trends, prevent deviations or out-of-specification events, and optimize scheduling.They leverage digital tools such as smart glasses to transform standard operating procedures into step-by-step visual guides for operational workflows, and have established a digital twin platform for the laboratory to predict impacts before implementing physical changes.

By achieving the level of a digital laboratory, general chemistry quality control laboratories can reduce costs by 25% to 45%. The potential savings for general microbiology laboratories will range from 15% to 35%. The improvement in productivity mainly comes from the following two aspects:

1. Reduce manual documentation workload by up to 80%

2. Automation and optimization of planning and scheduling have improved the utilization of personnel, equipment, and materials

By reducing manual error rates and enabling data-driven root cause analysis, laboratory investigation workloads can be reduced by 90%. Digital laboratories also benefit from improved compliance through reduced errors and variability, as well as seamless data retrieval and analysis. Furthermore, enhanced production efficiency and scheduling flexibility can reduce laboratory turnaround times by 10% to 20%.

Not long ago, a large global pharmaceutical company transformed its laboratory within an Italian Lighthouse Factory into a digital lab. By leveraging a modular and scalable digital twin platform for advanced scheduling optimization, the company increased its laboratory productivity by more than 30%. Additionally, through the use of advanced analytics, the company reduced deviations by 80%, completely eliminated recurring deviations, and accelerated deviation closure rates by 90%.

Pharmaceutical companies have numerous options when selecting and customizing technology solutions to create digital laboratories. In addition to bespoke dual-digital platforms and advanced analytics platforms, other solutions include Internet of Things (IoT) platforms (such as ThingWorx), laboratory scheduling software (such as Bookitlab or Smart-QC), and digital assistants for visualized standard operating procedures from vendors (such as Tulip), which enable real-time monitoring.

Automated laboratories employ robots, collaborative robots, or more specifically, advanced automation technologies to perform all repetitive tasks, such as sample preparation and delivery.During the automated laboratory phase, certain high-volume tests (such as microbial testing and sterile water analysis) are conducted online rather than in physical laboratories. Automated laboratories can also leverage predictive maintenance technologies to schedule infrequent tasks, such as maintenance of large-scale equipment, which can be performed by laboratory analysts with remote expert support.

While full digitalization is not a prerequisite, automated laboratories can be built upon a digital foundation to unlock greater value and achieve higher cost savings. Automated micro-laboratories can reduce costs within the laboratory by 10% to 25%, while generating equivalent savings outside the laboratory. If chemical laboratories implement similar improvements, their potential cost savings could be 10% to 20% higher than those of digital laboratories.

These laboratories have been able to improve productivity mainly due to the following factors: automation of 80% of sampling and sample delivery tasks, automation of 50% of sample preparation tasks, and reduced equipment maintenance costs through remote monitoring and failure prevention.

Automation also reduces sampling and related logistical tasks performed outside the laboratory, which translates to a 25% cost saving for micro-laboratories and an 8% cost saving for chemistry laboratories.

In addition to efficiency gains, pharmaceutical companies can reap extra benefits from laboratory automation. Built-in remote monitoring and predictive maintenance capabilities minimize downtime, thereby reducing reliance on costly equipment such as chromatography systems, near-infrared spectrometers, and isolators. By integrating rapid microbial testing into environmental monitoring, companies can shorten the overall laboratory turnaround time by 40% to 75%.

Technologies already established in healthcare, research laboratories, or manufacturing operations can be applied to pharmaceutical laboratories in a relatively straightforward manner, thereby advancing laboratory automation. Current vendors offering such solutions include Aethon, MICROMO (sample dispensing systems), BioVigilant, Colifast (online microbial testing systems), Metrohm, Sotax (automated sample preparation), Milliflex, Light Guide Systems (visual guidance for workflow optimization), and Scope (maintenance assistance).

Distributed Quality Control Disrupts Traditional Quality Control Methods.In a distributed quality control laboratory, nearly all routine product testing is conducted on the production line, thereby enabling Real-Time Release Testing (RTRT). Distributed QC equipment and robots are equipped with artificial intelligence capabilities. In distributed QC scenarios, the laboratory continuously performs specialized and stability testing, which can be carried out at centralized off-site locations.

Due to regulatory filing and approval requirements, the adoption of Process Analytical Technology (PAT) and Real-Time Release Testing (RTRT) has been relatively slow. To facilitate a smooth transition to online testing in the future, the operations department needs to collaborate with the research and development department to formulate optimal quality control and archiving strategies, particularly for new products and manufacturing sites.

Distributed QC laboratories primarily enhance value by significantly reducing the footprint and costs associated with traditional laboratories. Due to R&D investment requirements, as well as the need for equipment and operational changes, existing sites with stable or declining volumes are unlikely to present a compelling business case for distributed QC in the short or even medium term.

Meanwhile, laboratories that are rapidly expanding or under construction can derive substantial value by minimizing capital expenditures associated with establishing or scaling traditional quality control (QC) laboratories, provided they can perform a high volume of routine testing online. Distributed QC and real-time release will also enable truly continuous manufacturing processes (Figure 2).

For example, Biogen plans to implement distributed real-time release testing (RTRT) and exception management for quality control (QC) at its new facility near Solothurn, Switzerland. When production commenced in 2019, the Solothurn plant achieved raw material control through screening and pedigree tracking, enabling minimal testing via rapid identification and electronic data interchange (EDI).

Bioreactor processes controlled via online instrumentation will eliminate the need for process control sampling. The new facility will feature adaptive process control levers, recipe laboratory execution, and automated data transcription from all equipment, all underpinned by a deep understanding of raw materials, processes, and product characteristics. The integrated control system allows personnel to view data and respond in real time.

As pharmaceutical companies begin to explore methods for building distributed QC laboratories, they may adopt relevant technologies from adjacent fields. For instance, Perceptive Engineering’s PharmaMV platform and Siemens’ Sipat platform can provide the advanced process control necessary for parameter release. Meanwhile, artificial intelligence systems from companies such as Arago and IBM enable pharmaceutical companies to automate tasks that were previously performed by highly trained professional staff.

As pharmaceutical laboratories evolve, they will face substantial costs associated with implementing IT and automation solutions. Even costly solutions can deliver a strong return on investment (ROI); unfortunately, many companies struggle to realize value from these digital upgrades.

These companies typically encounter one or more of the following barriers:

1. Some specific laboratories lack a clear transformation goal.Although most laboratories can make a compelling business case for the scope enabled by digitalization, not all laboratories have sufficient volume and operational setups to justify automation and distributed QC.

For example, automating a small laboratory that may save less than $200,000 in costs annually might make it difficult to justify the investment, whereas the same investment could quickly yield a positive return on investment (ROI) for large-scale sterile equipment with extensive environmental monitoring.

2. There is no compelling business case for transformation.Many companies begin implementing costly IT systems without a clear understanding of the full benefits that IT and automation solutions can deliver. This often results in delayed execution and the partial rollout of solutions.

For example, a laboratory might migrate individual modules to a paperless system, while other modules still require substantial manual effort to transfer data from one system to another. This necessitates that analysts record test results in paper logs before manually entering the data into the Laboratory Information Management System (LIMS). This manual entry step prevents them from realizing the full cost savings that should be derived from automated documentation.

3. Focusing solely on comprehensively tested end-to-end future states, without continuously testing and rapidly scaling high-value solutions to quickly capture value.

For example, even if a laboratory has not yet fully achieved paperless and digital operations, it can rapidly implement automation and optimization of scheduling, thereby beginning to generate significant value.

4. Lack of proper planning or management for the launch of new systems and technologies.In extreme cases, pharmaceutical companies may need to spend several years and over $100 million to implement a LIMS. Given such an extended timeframe and the rapid pace of technological change, some of its features may become obsolete before they are fully deployed across the entire network.

Pharmaceutical companies need mature resources to accelerate product time-to-market and should avoid excessive customization at each site. A poor rollout plan can take five to ten times longer and cost three to five times more than a well-structured rollout plan with long-term planning.

5. Not fully aware of the capabilities of these systems they have acquired.Pharmaceutical companies may purchase systems such as LIMS to comply with data integrity regulations, but they do not truly understand or consider the system’s potential to enhance productivity.

6. Pursuing automation alone while neglecting optimization of scheduling.Dispatch automation can reduce QC costs by 2% to 3%, but combining automation with dynamic dispatch optimization can deliver three to four times the value.

7. Hesitant due to the recognition of the need to validate all systems and technologies.Many high-impact changes, such as optimized scheduling and data-enabled bias analysis, do not require validation and re-archiving.

8. Lack of the skill set required to extract full value from data.Most typical pharmaceutical laboratories lack the advanced analytics capabilities required to derive maximum value from their data sources. Consequently, while these laboratories collect data, they fail to leverage it effectively to generate insights that could prevent issues or reduce testing volumes.

9. Insufficient time and effort were devoted to developing a robust change management plan.Digital transformation requires a fundamental shift in mindset and has significant implications for organizations and individual employees, who must cultivate new skills and capabilities. To succeed, companies must make upfront investments to drive cultural change, secure enterprise-wide buy-in, and establish strong linkages between business and IT functions.

The good news is that most of the technologies currently available can achieve the objectives at any of the three development levels for QC laboratories in the Industry 4.0 era. Many of the technologies mentioned in this article have already been deployed in pharmaceutical environments, with some successful pilot projects completed and others still pending approval.

To successfully implement emerging technologies in the Industry 4.0 era, pharmaceutical companies need to set the right goals and take swift action. Here are a few things they should do at present:

1. Rapidly test several use cases and technologies to identify the optimal solutions for various laboratory types.

2. Establish a Lighthouse Factory QC Laboratory to showcase the potential benefits of integrating these innovative technologies.

3. Identify which innovative tools can generate the greatest direct impact, and then rapidly scale them across multiple sites.

Do not attempt to build a fully functional laboratory by adopting every possible technology, only to find yourself in a predicament. In fact, many use cases (such as scheduling optimization) can be implemented before other elements (such as paperless laboratories) are in place.

4. Establish clear objectives and a business case for the laboratory as early as possible.

Track value capture throughout this process and reinvest the savings into the next round of technological upgrades. It is important to evaluate chemical laboratories and micro-laboratories separately, as benchmark costs and the impact of improvements can vary significantly.

5. When planning and establishing new laboratories to meet the immediate needs of seizing opportunities in digital transformation and upgrading upon opening, target the highest value ranges demonstrated by business cases.

6. Establish a talent foundation and skills framework as early as possible.

Clearly understand future capability requirements, train high-potential employees, and hire staff with new skills (such as advanced data analytics) at an early stage to scale up more rapidly.

Modern technology can make QC faster, more flexible, more reliable, more compatible, and more efficient. By setting appropriate goals, selecting suitable technologies, and scaling up rapidly, pharmaceutical companies can become leaders in quality control and reap rewards in the form of speed, compliance, cost savings, and improved productivity.

(Compiled by Cheng Xiaoqin)