The Scientist’s Survival Guide:
Handling disparate lab systems and data
Does your lab have too many different systems for its own good? Read on to learn more about the problem with multiple systems and data sources, and find out how a unified lab platform can empower you with new efficiency and insight.
It’s mid-experiment, and you’re navigating from one lab system to another—log experimental insights in the ELN, check sample data in the LIMS, pull raw datasets from the SDMS, and then analyze everything in a separate business intelligence tool. The constant switching between multiple systems and logins may seem like a necessary part of the research process, but this daily ritual has more of an impact on efficiency and progress than one might think.
While each system has its unique value, the disjointed nature of lab workflow management introduces friction, slows research, and wastes valuable time on repetitive tasks that don’t add scientific value. So why do most labs continue working across multiple systems? We unpack this scenario and the struggles it brings in Episode 3 of our #savethescientist video series. You can watch the video below.
In this blog, we’ll take a closer look at the problems caused by disparate lab systems and uncover how a unified, science-aware platform can unlock new levels of efficiency and accuracy in the lab.
Why are multiple lab systems causing scientists so much pain?
Laboratory technology should be working with your research, not against it.
Yet for many scientists, the reality is a daily ritual of logging in and logging out that, at best, is inconvenient and, at worst is an obstacle to discovery. Juggling daily workflows across multiple lab systems and platforms creates a variety of challenges that slow progress, distract from the science itself, and even pose a threat to research quality.
Let’s break down why multiple logins and disconnected tools are a leading cause of pain and efficiency for scientists.
Data discrepancies and manual transfers
The first and most obvious source of pain associated with multiple systems is data discrepancy. With multiple scientific systems comes multiple data repositories. And with multiple data repositories comes a cascade of inefficiencies: manual imports and exports, duplicative data, missing entries, and risk of error.
For example, consider a scientist who must cross-check an assay result from their ELN with metadata in their LIMS. Without a unified solution, that scientist can spend hours of their work copying over values, checking for inconsistencies, and trying to validate results. On top of this, every time a scientist needs to export and transfer data represents another opportunity for the data to be compromised, introducing concerns related to data security and privacy.
Questions to consider
- How do you transfer data across systems?
- Can you remember a time when manual transfers led to data errors?
Disparate data, with no single source of truth
Inefficient workflows to move data from one system to the next is only one part of the challenge. In a lab with multiple systems, a single source of truth is virtually non-existent. The absence of real-time data synchronization means that scientists are often working with outdated or incomplete information, making it challenging for them to make informed decisions.
For example, the absence of a centralized data source and unified molecule registry prevents scientists from gaining granular traceability over samples, experiments, and assays, and raises questions about the accuracy of the data they rely on. No amount of manual importing and exporting will provide up-to-the-minute information that supports agile and data-driven scientific decision making.
Questions to consider
- How do you ensure your data is timely and accurate?
- Do you ever struggle to understand the status of an experiment or sample?
Fragmented workflows
Working from disjointed lab systems inherently leads to fragmented workflows that create additional barriers for scientists. For example, if a scientist is performing analytical testing to characterize compounds, they may need to set up the experiment in their ELN, then go into their LIMS to retrieve sample metadata, then return to the ELN to document experimental observations, then back to the LIMS to input test results, and so on.
Studies show that disruptions at work can consume up to 6 hours each day, when considering the time it takes to refocus after each interruption. For scientists, the constant back and forth between systems can lead to significant downtime, as they must break their focus to wait for each system to load.
Questions to consider
- How many different systems do you rely on in your lab?
Multiple logins
With multiple systems comes multiple sets of credentials. Managing credentials may seem like an obvious and even trivial inefficiency associated with multiple system logins, but it remains an important consideration. In fact, up to 50% of an organization’s help desk calls are for password resets, and an individual employee often spends as much as 11 hours per year searching for or resetting passwords. This number doesn’t account for two-factor authentication, which adds additional time to the process. What could you achieve with 11 more hours of productivity for every scientist in your organization?
With many scientists working in five, eight, ten, or even more systems, the scale and complexity of login management is a real impediment to efficiency in the lab.
Questions to consider
- How often do login issues disrupt your workflow?
- How do you manage your login credentials?
Complex data security and compliance
Managing data security and compliance in a lab with disconnected systems is a daunting task. Each isolated tool introduces new vulnerabilities and security variables that must be addressed. With critical data spread across multiple platforms, demonstrating compliance with GCP, GLP, GMP, and ISMS becomes far more difficult, especially without a single source of truth to ensure auditability.
Inconsistent security protocols across tools also hinders the ability to enforce unified encryption, access controls, and reliable audit trails. This increases the risk of data breaches and compliance violations, potentially undermining both scientific integrity and the lab’s credibility.
Questions to consider
- How does your lab currently maintain compliance across different systems?
- Are your data security practices standardized and auditable throughout your entire workflow?
Stifled visibility and collaboration
Disjointed lab systems pose significant obstacles to data visibility and collaboration among scientific teams. Without a centralized platform, critical information gets trapped in silos, making it difficult for researchers to share insights, stay aligned on findings, or gain a comprehensive view of ongoing work. This fragmentation doesn’t just slow individual workflows—it hinders the collaborative effort necessary to drive scientific discovery.
Imagine a scenario where a research team is assessing the efficacy of a promising drug candidate. One scientist needs to extract chemical structures from the LIMS, another pulls assay protocols from the ELN, and a third gathers analytical data from screening experiments. Because these systems aren’t unified, the team faces time-consuming steps to manually consolidate data from multiple platforms. Worse still, efforts are sometimes duplicated due to lack of visibility. For example, two scientists may end up running the same bioassay, unaware that the other had already performed the test days earlier. This duplication happens because there’s no centralized system to easily track completed tasks, leading to wasted time, resources, and potential inconsistencies in experimental data.
Questions to consider
- How do you currently share data across teams?
- How much time could be saved with a single platform for scientific collaboration?
How can a unified platform save the scientist from fragmented lab workflow management?
To #savethescientist from disjointed workflows, multiple logins, data discrepancies and stifled collaboration, it’s important to choose a lab informatics platform that is truly unified, allowing you to perform all your critical work with a single login and experience. Here are some key things to look for:
A unified lab platform eliminates clumsy credential management, and the downtime associated with loading different systems. With a single login, scientists can access the ELN, LIMS, SDMS, and tools for scientific analysis, saving time and reducing errors associated with switching between systems.
For example, when conducting stability studies, a scientist can access all of their sample metadata and analytical results from the same place where they log their experimental observations, making the process much more streamlined. They no longer need to transfer data from one system to another—instead, the information already resides right where they are.
The unification of multiple systems in a true platform goes deeper than a single login and experience. A flexible data model allows scientific teams to seamlessly bring together data not only from each of the lab’s core systems, but also from the instruments it relies on in process design and analysis, in a way that is adapted to their lab environment. In turn, scientists can move seamlessly from experiment, to workflow, to insight, and back again.
When data feeds automatically into a single, secure solution, the need for manual data entry and cross-checking is eliminated. Take quality control testing as an example. When HPLC data is captured directly in the LIMS, scientists can monitor it in real-time and quickly identify any deviations before they lead to larger problems. This level of integration supports a more streamlined, insight-driven approach to lab work.
A science-aware platform that standardizes and unifies scientific data in a single place empowers scientists to make decisions faster than ever. Rather than shifting between systems to mine insights, scientists can access all the information they need from one central location.
Real-time experimental observations, instrument data, sample information, analytical results, and other key pieces of information all reside in the same place, and scientists can gain new confidence that all information is accurate, up-to-date, and decision-ready. Furthermore, scientists can access a single, unified registry that serves as a single source of truth for all molecules, compounds, and samples.
Even more powerfully, a truly unified and science-aware lab informatics platform allows scientists to visualize and analyze their data right where they are. Rather than moving everything into another tool for analysis, scientists are free to draw meaningful conclusions without barriers. For example, if a scientist needs to generate a dose response curve for a new drug candidate, they can plot drug concentration against response right in their core system and then easily visualize the curve to assess viability. The collective impact of built-in data visualization and analysis is significant, with the potential to accelerate research greatly.
A unified lab informatics platform significantly enhances data security and compliance by centralizing all lab data within a single, secure environment. This centralization makes it easier to adhere to industry standards, such as GCP, GLP, GMP, ISMS, and SOC 2 Type 2, with consistent access controls, encryption, and automated audit trails. Role-based access control is built into the system, ensuring only authorized users can access specific data and providing the level of privacy and security required for sensitive scientific research.
Additionally, a unified platform streamlines compliance workflows by automatically recording and maintaining transparent data logs. This not only simplifies regulatory reporting but also mitigates the risk of security breaches, allowing scientific teams to focus more on their research with full confidence in their lab’s compliance.
A unified and science-aware lab informatics platform also fosters rich and seamless scientific collaboration. When scientists and lab team members work from the same solution, they have access to shared data, enabling real-time visibility and more effective teamwork. Scientists can tag colleagues, share data directly within the platform, and track project progress from experiment setup to conclusions. Both scientists and lab operations team members have the visibility they need to conduct their daily work without opacity or duplicative effort.
For example, during a CRISPR gene editing project, multiple scientific teams are involved in different stages of the process. A unified platform allows each of these teams to access full experimental history, from initial guide RNA sequences to real-time gene editing results. Each team can view one another’s progress, know exactly where to start, and communicate directly within the platform, supporting greater accuracy and efficiency.
#savethescientist with Sapio’s fully unified platform
While some view multiple lab systems as a way of life, Sapio views a unified platform as a prerequisite to accelerating scientific discovery. We pride ourselves on removing barriers associated with navigating, managing, and securing multiple systems, and unleashing a new standard of productivity in the lab.
Sapio’s science-aware lab informatics platform brings together the LIMS, ELN, scientific data cloud, and robust analytics tools in a unified experience made for scientists. Scientists can handle every part of their workflow from a single login and a standardized interface, eliminating the errors and inefficiencies that come with maintaining multiple systems.
Ready to leave fragmented lab workflows and systems behind?
