Lab Digitalisation and Automation

What is the value of site-to-lab digitalisation, lab trial management systems, and end-to-end biobanking and specimen life cycle management in improving clinical labs?

Amreen Ahmed, Kelli Aufderheide and Gavin Hershaw at IQVIA Laboratories

As clinical research continues to diversify, the central lab sits at an increasingly crucial inflection point. Whether decentralised, adaptive, global and/or driven by emerging modalities (eg, cell and gene therapies [CGTs]), today’s clinical trials rely on labs not only for scientific accuracy, but also for operational consistency. The lab’s ability to keep pace with today’s complex study designs often determines how efficiently trial sponsors can initiate studies, manage patient visits and maintain quality throughout the trial life cycle.

This demand requires expert labs to address a long-standing quandary: how to accelerate critical trial activities, particularly study start-up and sample processing, without compromising quality or adding burden to scientific teams. Digitalisation is often offered as the answer. Yet in practice, technology only creates value when it is purposeful, intuitive and embedded directly into how lab teams, sites and sponsors realistically work. If poorly implemented, digital systems risk simply replacing old burdens with new ones.

In contrast, digital site-to-lab solutions are transforming this experience by capturing critical information at the moment of patient interaction. Electronic requisition systems are now guiding sites through protocol-specific workflows, ensuring that required fields are completed accurately, and that captured information is both consistent and validated. Going well beyond converting paper forms into PDFs, modern systems think along with the workflow, bringing up the appropriate visit window, kit information, sample instructions and shipping steps exactly when they’re needed per the context of the patient visit.

This shift has important downstream effects. When sites enter complete and validated information upfront, expert lab teams can accession samples more efficiently, eliminating the need to decipher unfamiliar handwriting or take time to verify missing fields. Data integrity improves because transcription errors are removed from the equation entirely. Fields captured digitally flow directly into lab systems, providing consistency across patient visits and reducing the time spent resolving queries. For sponsors, this translates into clearer oversight, more accurate monitoring of visit-level activity and fewer delays in processing critical endpoints.

Still, several advances are demonstrating substantial real-world impact, reshaping how labs deliver holistic and ongoing oversight, streamline workflows and protect data integrity to, ultimately, help trials reach patients sooner.

While much of clinical research has benefitted from digital tools in recent decades, one area has historically lagged behind: the site-to-lab workflow. Many trial sites still rely on paper requisitions, handwritten notes, manual transcription and fragmented communication to accompany specimens as they make their way to the lab. These outdated processes can create immediate bottlenecks, with slower sample accessioning (ie, receiving, logging and processing specimens), unclear instructions, higher query rates and more fragility in the chain of custody.

For some, the most important benefit may be the reduction in site team burden. Investigators and coordinators often juggle numerous platforms and protocol nuances for multiple clinical trials. Digital site-to-lab systems help simplify this layered landscape by providing clear, guided instructions during sample collection and packaging, which helps to reduce the likelihood of shipment errors or protocol deviations.

When implemented well, this digitalisation quietly ‘gets out of the way’, enabling sites to focus on patient care instead of administrative tasks.

Behind the scenes, central labs manage a deeply intricate ecosystem of processes that includes global kit supply chains, regional logistics, analytical workflows, temperature-sensitive shipments and testing capacity that fluctuates with enrolment patterns.

Historically, these components have been managed through a patchwork of spreadsheets, variations of lab information management system (LIMS) modules, courier portals and email threads. A siloed approach can create inefficiencies and is error-prone, particularly when applied to high-complexity trials like those involving CGTs or decentralised sample collection in high volumes.

Lab trial management systems (LTMS) are emerging as the connective tissue needed to orchestrate these activities from a centralised, real-time platform. Traditional LIMS focus on analytical processes and maintaining scientific truth, whereas LTMS are designed to also consider operational coordination. An LTMS becomes the ‘control tower’ that translates protocol requirements into actionable workflows, ensuring every operational step – from kit forecasting to spotting and resolving logistical issues – aligns to individual trial needs.

A well-designed LTMS can map a protocol into operational terms with precision. Kits, draw windows, regional supply rules and lab panels can be configured once and applied consistently across countries and sites.

Amendments to the study protocol can be implemented while allowing live activity to continue. Approvals and regional variations are controlled within the system to ensure full compliance with accepted protocol versions at the study, region, country and site level. In parallel, logistics visibility enables labs to monitor shipments in transit, identify delays and escalate issues before they impact sample stability.

This centralisation becomes even more critical in complex modalities. For CGTs, where vein-to-vein timing and chain-of-identity are essential, LTMS platforms can align scheduling, transportation and analytic readiness. When combined with managing logistics workflows, these systems can help lab teams ensure that deviations – such as a temperature excursion – are not only recorded, but then trigger timely action.

The value of an LTMS, however, depends heavily on usability and adoption. A sophisticated system that is cumbersome to navigate can introduce friction instead of eliminating it. Therefore, change management is as important as technical configuration. Engaging bench scientists, accessioning staff, kit planners and study managers early in the design process helps ensure the system reflects real-world workflows instead of ideal process maps.

As drug development becomes increasingly multimodal and exploratory, biospecimens have gained a new level of strategic importance. A single sample may support safety testing at baseline, biomarker discovery during development, and retrospective analysis years after a therapy is approved and available to patients. However, this expanded use case also means that labs need to maintain meticulous records across the entire specimen life cycle, from initial collection to long-term storage, retrieval and secondary analysis.

Traditional biobanking practices are often reliant on Excel spreadsheets, static freezer logs or disconnected databases, which make it difficult to support today’s level of R&D complexity. To match the needs, end-to-end specimen life cycle management systems are becoming a part of the essential infrastructure. Advances in platforms are allowing lab teams to assign each specimen a persistent master identifier that links all derivative samples (ie, aliquots, extractions and slides) back to the original collection. Every touchpoint is captured within a continuous chain of custody, providing full traceability and strengthening data integrity from start to finish. Digitising these audit trails is especially valuable because the

International Council for Harmonization Guideline E6(R3): Good Clinical Practice emphasises the need for robust, traceable and secure computerised systems that maintain data integrity throughout the entire data life cycle.1

Consent management plays a central role in this evolution, too. In many trials, participants provide nuanced permissions regarding how their samples may be used, where they may be stored and for how long. Additionally, when no longer needed, as agreed upon, samples can be eliminated in a timely manner, freeing storage and related cost. Digitising these consent terms makes them machine-interpretable. In cases where a researcher may later request specimens for secondary analysis, the system can automatically verify whether the intended use aligns with the participant’s consent. This prevents improper use, improves compliance and reduces the burden on bioethics committees to manually verify each request.

Across site-to-lab digitalisation, lab trial management and specimen life cycle management, one principle stands out: technology must be applied with intention. Well-designed digital tools aim to relieve existing pressures, not create new ones. The most effective transformations are those grounded in the day-to-day realities of lab operations and built around how lab staff, site teams and other stakeholders realistically work. Achieving this requires careful attention to user experience, strong master data governance and a commitment to open, interoperable systems, rather than technological lock-ins. A staged, pragmatic roadmap also helps ensure that digitalisation unfolds sustainably. Stabilising intake processes, developing orchestration capabilities and then modernising biobanking infrastructure allows each layer to reinforce the next, extending value across the entire trial network.

When executed thoughtfully, digitalisation does far more than accelerate study timelines. It lightens the operational load for those closest to patients and samples, enabling labs to deliver both efficiency and scientific rigour with quality. In an environment where trial complexity is rising sharply, this balance is not only advantageous for sponsors, sites and labs – it has become essential.

Reference: 1. Visit: ichgcp.net/4-data-governance-investigator-andsponsor-ich-e6-r3