The pharmaceutical industry — particularly companies involved in drug manufacturing—faces many pressing challenges. These include responding to global health crises by ensuring patients receive timely access to innovative treatments they need to support their health. Companies are under increasing pressure to accelerate the speed of bringing new medicines, vaccines, and diagnostic testing services through market launch and into commercial production.
However, the slow adoption of new, integrated data management technologies in quality control (QC) testing and broader manufacturing processes, coupled with the continued use of legacy systems and unconnected lab systems, is hindering the automation of essential processes, with consequences for time and data accuracy. Traditional QC labs, with few integrated instruments and applications, require technicians to manually transcribe and input data into systems and then transmit that data to other instruments by hand. Time is wasted not just during the transcription but also later due to the requirement for second-person verification. Such time delays and the risks of human error may all hinder the effective commercial production of potentially life-saving medicines.
Companies need to harness the power of QC lab automation not just to manage the collation and storage of data, but also to analyze it effectively to extract its full value and accelerate QC lab test cycles. This article explores how to harness lab automation to create a seamless workflow and streamline drug testing processes.
The drawbacks of traditional manual and unconnected labs
In recent years, many steps have been taken to streamline time-consuming manual lab operations in QC testing for commercial drug manufacturing. A new generation of lab informatics systems has been introduced, which has helped to reduce the time spent inputting and storing data.
However, if these technologies are not fully connected, there is a risk of valuable lab data remaining siloed in the systems to which it was input. This means that the potential gathering of information to draw valuable business or drug manufacturing insights becomes a laborious and tedious task.
This is the state of play for far too many laboratories. They have advanced technology for storing or analyzing data, but those systems are not integrated with one another or the larger organization's core IT processes. These labs then struggle with the “human middleware” between the labs and core systems. Humans must input data by hand or manually seek out and track down vital pieces of information across lab equipment, which increases the risk of errors or of valuable data sets being missed entirely. Anomalies must be investigated, and all new data inputs must be second-person verified, all taking up technicians’ valuable time that could be better spent analyzing the data for actionable insights that could benefit the business.
However, when these disparate QC lab systems are fully connected — integrated through applications and instrumentation — data flows within a lab and the wider organization can be automated. This automation can result in a significant boost to the user experience for multiple drug manufacturing stakeholders seeking to access business and lab data. There is also a major reduction in second-person verification needs, streamlining vital lab processes, and providing technicians with the time they need to perform high-value activities.
QC test lab automation — and the employee time saved — can have a significant business impact and deliver a competitive advantage in many ways:
- Streamlining commercial product launches with quality by design
- Accelerating QC test cycles
- Improving manufacturing efficiencies post-commercialization
- Enhancing regulatory compliance and audit-ready labs by eliminating manual data transcription and workflows, which reduces error rates and facilitates investigations into deviations followed by corrective action and preventive action (CAPA).
- Strengthening connectivity and seamless digital business process flow
- Delivering a single source of data truth for data integrity and end-to-end traceability.
What is hindering QC lab automation?
Although QC lab automation offers significant promise to life science companies, the industry has historically been hesitant to approve such investments. This largely comes down to concerns around cloud security, data integrity, regulatory compliance, perceived difficulties in the transformation process, value to business, and a shortage of skilled labor to implement the new technology and train lab technicians.
Legacy systems in place not just within the lab, but across an organization’s operations can hold back the integration of the latest connectivity solutions. Older equipment may not be integrated into an organization-wide system, limiting the ability to source and analyze valuable data from across the business in an effective way. Legacy systems may also not be compatible, either with the new technology being brought in to enable interoperability or with established counterparts already in use across the organization. Special consideration has to be given to the question of replacing such equipment and extracting any valuable data stored within it. The cost and time needed to upgrade might be daunting for some smaller organizations, even though these considerations should be outweighed by the potential productivity gains of lab automation.
Change management is also often a significant obstacle hindering companies from achieving an automated testing lab. Any time an organization focuses on a transformation change of this type, it has the potential to impact all of its employees. For larger companies, this may mean that efforts to automate lab data processes may affect hundreds of team members. In this scenario, all the impacted individuals need to have full understanding of what is happening, why, and how it will benefit them and the wider business. They will also need training in how to use the new equipment. All this can take time and effort to achieve.
What is the starting point for businesses automating QC lab data processes?
Any business seeking to embark on a lab automation journey needs to start with a vision of what the future could look like and take a value-based approach to digital transformation. This vision shouldn’t just be kept within the leadership team; it needs to be shared with all affected employees so that they understand the value of the changes being made and support their implementation.
For instance, eliminating the time spent inputting data and performing second-person reviews frees them up to do scientific work, creating value for them and the business.
With this in mind, key considerations to help organizations overcome challenges on their lab automation journey include:
- Gain buy-in and sponsorship from people at all levels: Effective change management is one of the most important factors in successful digital transformation. It’s crucial to onboard and engage employees throughout the organization and across all sites from the very earliest stage to ensure that they are fully invested in the journey the company is about to embark on. People need to understand what will happen so they can explain it to their colleagues and get everybody on board, excited about the change, and not afraid of a negative impact on them. Bringing employees into the conversations about the company’s vision for the future and the plan for rolling out new technologies from the beginning, with regular updates, will keep people engaged and enthused about the journey.
- Understand your organization’s level of digital lab maturity: During the planning stage, it’s important to assess how advanced the organization’s existing technology is and how integrated its data management systems are with each other. This is key to making an effective, manageable, and realistic plan of action for QC lab automation that works for the organization’s unique needs. It means a company can begin with basic upgrades that will streamline processes, such as connecting lab systems to core business networks, before advancing toward greater sophistication, such as the automation of method execution. It also means that an organization may be able to retain some existing technology, reducing costs. Some equipment may already possess digital capabilities but may require reconfiguration to enable cloud access and control. Assessment of digital abilities and cloud access control can help determine how much reconfiguration is required. Equipment that cannot be integrated into the new system will have to be replaced.
- Focus on speedy implementation to avoid the risk of the obsolete: The fast pace of technological innovation can prevent some organizations from taking the action they need to automate their labs and achieve digital transformation. Many companies may feel they have to wait until the next advancement appears on the market, which can often result in unnecessary delays in investment that ultimately undermine operational efficiency. Investing in what’s available now and ensuring that the resulting system has the processes in place to allow straightforward upgrades with new technology is preferable to waiting until the perfect technology appears.
- Seek support from an expert partner: Expert support from specialist contract partners can be vital in ensuring the success of a lab automation journey. These partners can help organizations understand what sort of data they hold, where it is held, and its value. In addition, they have expertise to draw on, which can be invaluable in identifying the key areas where both technology and data can have the most positive impact on operational efficiency and drug development success.
A dedicated digital transformation partner can provide advice based on years of experience with the most effective technologies to maximize the value of data in the lab, as well as easy access to new advancements, such as Gen AI, Bots, CoBots, AR/VR, RPA, cloud computing and IoT systems. These innovations, in particular, have a lot to offer companies seeking to optimize lab asset performance management, thanks to their unique ability to connect lab systems with other equipment potentially across multiple sites. This can enable even greater integration of enterprise data across an organization not just to optimize general operations but also to help better utilize data from manufacturing in lab processes to positively impact productivity post-commercialization.
Embracing the full potential of automation
With the right support and a comprehensive plan in place, companies can achieve effective lab automation, unlocking efficiencies to enhance decision-making capabilities and adding greater value to their operations. Automation can revolutionize how organizations operate, impacting everything from productivity to sustainability to drug commercialization success.
Taking an “act now or fail fast” approach, with the support of expert partners, companies can ensure they benefit from lab automation as quickly as possible, giving themselves a distinct competitive advantage while fuelling further innovation to ultimately improve patient outcomes.
