Building the Lab of the Future: Connecting Instruments, Methodologies, and Analysts

Many GxP labs still depend on paper lab records, manual transcription, and second person review to move samples from receipt through release. While these processes are familiar, they introduce delays, increase the risk of transcription errors, and create a heavy review burden for analysts and quality teams.

At Operations Calling, leaders from Organon shared how they approached these challenges as part of their “digital lab journey,” describing the shift from paper-based lab records toward a more connected way of executing lab methods.

This article distills those lessons into a practical, informational playbook. It outlines how instruments, LIMS, and analysts can be connected through digital lab records, middleware, and enforced workflows, from proof of concept to scalable deployment while supporting data integrity and GxP compliance.

A connected lab is not defined by replacing paper with screens. It is defined by how lab work is executed end to end, with systems, instruments, and analysts connected through a single, controlled workflow.

In a connected lab, data does not need to be manually transcribed from one system to another. Analysts can select samples from a list of assigned tasks, then they can walk through testing procedures where data is automatically captured from connected instruments, and results can flow back without re-entry. This reduces delays, minimizes transcription errors, and improves consistency across methods.

Equally important, a connected lab prioritizes the analyst experience. When workflows guide execution step-by-step, analysts spend less time navigating systems and more time performing the work correctly. The result is better data integrity, clearer audit trails, and a lab environment that can be continuously improved without disrupting validated processes

Building a connected lab requires a clear, step-by-step approach grounded in how lab work is actually performed.

The following steps describe a practical path for connecting instruments, LIMS, and analysts

Step1: Start with the current-state workflow and where the waste is

The first step toward a connected lab is understanding how work actually flows today, not just how it’s documented, but how it’s executed.

Start by mapping one method from sample receipt through final release. Identify every step: where data is created, where it is written down, where it is entered into a system, where it is reviewed, and where work pauses. Include reagent preparation, equipment setup, calculations, second-person review, and result posting. Capture who performs each action and which system or document is used. In many labs, this exercise quickly exposes duplication and delay.

“If you do everything on paper, there’s a possibility that someone makes an error. Can be something small like a typo, but it has a big influence.” - Elke Van Camp, Senior Specialist, Quality, Organon

Mapping makes those risks concrete. It highlights where data is transcribed, where reviews interrupt execution, and where multiple documents carry the same information. Instead of debating paper vs. digital, teams can see exactly where rework and manual checks are adding time and quality risk.

The outcome of this first step is a shared, visible execution path that becomes the foundation for standardization and digitization.

Step 2: Map the standard lab flow end-to-end from ERP to release

After identifying current-state waste, define the standard lab flow from start to finish. In most labs, this runs from lot creation in an ERP, to sample receipt in LIMS, through execution, review, and final release. This is also where validation risk must be addressed.

Mapping this end-to-end flow makes execution visible. It shows where data is created, re-entered, reviewed, and delayed which establishes a clear, shared view of how work should move through the lab.

Without a defined end-to-end flow, workflows can’t be enforced, transcription can’t be reduced, and digital lab records can’t scale reliably.

Step 3: Define future-state goals for digital lab records

Before digitizing anything, define what the future state needs to achieve. The goal is to reduce manual entry, remove transcription, and shorten execution and review timelines.

Future-state goals should focus on eliminating paper forms and physical logbooks, automating calculations and data capture, and improving data integrity through enforced workflows. Integration between instruments, digital lab records, and LIMS is essential so data can move automatically without re-entry.

Step 4: Prove the architecture with a proof of concept

Before scaling, validate that the approach works in practice. A proof of concept helps confirm that instruments, LIMS, digital lab records, and middleware can function together in a regulated environment.

At this stage, the focus is on feasibility: removing manual transcription, validating integrations, and confirming that workflows can be enforced without disrupting existing systems. It’s also where early versions of review-by-exception and user experience can be tested.

A proof of concept reduces risk by proving the architecture works before committing to production deployment.

Step 5: Build methods using reusable “Lego brick” apps

With the architecture proven, methods can be built by linking small, reusable apps in a defined order. Common activities such as reagent management, equipment setup, and experiment generation are created once and reused across methods.

Method-specific steps are layered on top, allowing simple and more complex methods to follow the same execution structure. This modular approach makes it easier to standardize execution while still supporting different method requirements.

So reusable building blocks reduce complexity and make it easier to expand digital lab records across methods without starting from scratch.

Step 6: Move from second person review to review-by-exception

Once workflows are enforced and data is captured automatically, the second reviewer can shift from checking every step to focusing only on exceptions. Instead of re-verifying routine execution, the system checks that required steps and specifications are met.

When something falls outside expectations, an exception is raised and reviewed. Analysts can correct the issue or repeat the step, while the second reviewer focuses only on what requires attention.

“The second analyst is only checking those exceptions where something went wrong.” If needed, “we raise an exception and redo the step previously if your weight for example is out of the specification ranges.” - Michaela Chapman, Digital Labs IT Lead, Organon

Review-by-exception becomes possible only after workflows, integrations, and checks are in place and it reduces review effort without compromising data integrity or GxP compliance.

Step 7: Launch the minimum viable product and measure impact

With workflows, integrations, and review-by-exception in place, the next step is to move into production with a minimum viable product (MVP). An MVP provides a production-ready way to execute a method, with the expectation that it will continue to improve based on user feedback.

Once live, the impact can be measured.

“We measured the hands-on time and we had a reduction of 20% hands-on time for the moisture method.” -Elke Van Camp, Sr. Specialist, Quality, Organon

Adoption matters just as much. Guided workflows and a consistent user experience support onboarding and enable a smooth transition from pilot to production without disrupting lab operations.

Building a connected lab is a progression. By starting with workflows, proving the architecture, launching an MVP, and scaling across methods, labs can reduce manual transcription, support data integrity, and improve execution, without disrupting validated processes.

Tulip supports the connected digital lab by acting as a workflow layer that coordinates how lab work is executed across people, instruments, and systems. Tulip can augment or replace systems such as LIMS depending on the deployment. In many connected lab environments, it guides method execution step by step, enforces consistent workflows, and captures data in a structured way as work is performed.

Using modular, no-code applications, teams can build digital lab records by linking common lab activities such as reagent selection, equipment setup, sample preparation, and result review, into defined execution flows. Integration through middleware allows tasks to be sent to lab instruments and results to flow back automatically, reducing manual transcription and re-entry.

Tulip also provides dashboards and audit trails that support visibility into experiment status, material and equipment readiness, and execution history. Together, enforced workflows, integrations, and visibility help strengthen data integrity, support analyst adoption, and enable review-by-exception in regulated lab environments.