Lab testing doesn’t always go as planned. In clinical, QC, or research labs, results may be inconclusive, instruments may fail, or data may look off. When issues arise, labs must manage them to protect data integrity, stay compliant, and keep workflows efficient. A lab informatics system helps by setting clear protocols for unexpected events while allowing flexibility for cases needing human judgment.
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This episode of
Decoding the Digital Lab explores how to integrate AI into labs. Host Megan Pettyjohn and expert Glenn Everett discuss the need for strong data systems, specialized software, clear goals, and staff training. They stress managing buy-in by showing AI’s benefits and ROI, while underscoring one key point: “Bad data in, bad results out.”
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Protect the food chain by strengthening animal feed quality control testing. Screen for mycotoxins, heavy metals, pathogens, and verify nutrition with proximate analysis. Standardized workflows and LIMS integrations centralize data, speed turnaround, and maintain audit-ready compliance, improving safety, consistency, and profitability.
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Rework in quality control is a daily reality for many food and beverage industries. Each step redone, analysis repeated, or retained batch means extra costs, wasted time, and delivery delays. Digitalizing quality processes can change this. In this article, we explore how a LIMS can reduce rework, improve traceability, and boost productivity. If you work in the food industry and want to optimize your lab, read on.
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AI-powered oil analysis is transforming gold mining by enabling predictive maintenance that reduces downtime, extends equipment life, and lowers repair costs. By identifying early signs of wear through automated diagnostics, mining operations can stay ahead of failures and protect both productivity and safety.
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When implementing new lab informatics systems, “the lab” is often treated as as a single unit. labs are dynamic environments with multiple people, each with different responsibilities, goals, and frustrations. A system that helps one user may hinder or even cause outright failure for another. To implement a system or LIMS that works well for all users, labs need recognize the different personas that make up a lab.
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In our previous post, we explored AI’s growing impact on regulatory and clinical documents. Now, we focus on Structured Content Authoring (SCA)—a key enabler of reuse, traceability, and large-scale automation. More than just a technical upgrade, SCA lays the groundwork for AI-driven content generation, helping life sciences companies accelerate time to market and reduce costs.
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Labs consume far more energy and resources than most workplaces—but it doesn’t have to stay that way. Explore how smarter lab management practices and digital systems can significantly reduce waste, cut energy use, and support long-term sustainability without compromising performance or compliance.
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The lab of the future is intelligent, agile, seamlessly connected, and sustainable. By leveraging integrated digital tools, advanced AI, and automated workflows, labs drive greater productivity and innovation, ensuring scientists stay at the leading edge of discovery. Thermo Scientific SampleManager LIMS v21.3 offers an integrated data management platform designed to support AI-enabled lab operations.
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Tariffs—taxes on imported goods—are making global trade increasingly unpredictable, with direct and indirect impacts on laboratory supply chains. From rising costs on critical reagents to unexpected customs delays, many labs are already feeling the effects. This blog explores what tariffs are, how they disrupt lab operations, and strategies to help labs navigate these challenges.
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In regulated lab environments, validation is a crucial step for ensuring the reliability and integrity of scientific data. Two key types of validation often come into play: assay validation and computer system validation (CSV). Each type serves a distinct purpose. However, how they are applied varies across industries, based on the nature of the lab’s work, the particular regulatory standards that apply, and the lab’s risk tolerance.
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The gene-to-protein workflow represents one of molecular biology’s most fundamental processes, allowing scientists to express and study proteins of interest. This comprehensive guide details each step from initial DNA sequence to purified protein, highlighting critical decision points and technical considerations.
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In this podcast episode, Veronica DeFelice from Sapio Sciences joins us as we explore digital transformation in drug discovery, where precision and tracking in biological data are crucial for maintaining accuracy and making advanced decisions.
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Environmental labs face increasing pressure to improve accuracy, efficiency, and compliance. Discover how the right digital tools can streamline data management, reduce manual errors, and help your lab meet regulatory demands. These solutions also improve turnaround time and support more sustainable operations.
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Artificial Intelligence (AI) is rapidly transforming how scientific research is conducted, offering new ways to accelerate discovery, optimize experiments, and make sense of complex datasets. In 2025, Scientific AI is more than just a tool—it’s a necessity. This article explores more than 10 essential AI tools that are shaping the future of hypothesis generation, molecular modeling, data analysis, and beyond.
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Labs that struggle with manual tasks, poor data visibility, compliance gaps, or fragmented collaboration may be falling behind. Recognizing these signs early allows teams to modernize workflows, improve accuracy, and boost overall efficiency using integrated digital tools that support adaptability and growth.
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In today’s digital world, data is the lifeblood of every laboratory business. However, it’s not just the data itself that matters. It’s how that data is stored, tracked, and managed over time as electronic records. While they’re often discussed in the context of regulatory compliance, electronic records are fundamental to running an efficient, high-quality lab, whether the lab is regulated or not.
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In today’s high-stakes lab environment, precision, speed, and control are essential. That’s where quality indicators and visual dashboards come in. These powerful tools are game-changers for industries where accuracy is non-negotiable—whether it’s environmental testing, food safety, or industrial analysis. Integrated into a cutting-edge LIMS, they deliver real-time insights, streamline operations, and drive smarter, faster decisions.
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Is your laboratory's LIMS feeling a bit behind the times? In today's rapidly evolving scientific landscape, an outdated LIMS can be a significant bottleneck, silently impacting everything from daily lab efficiency to crucial regulatory compliance. While the thought of a LIMS upgrade may seem daunting, the truth is, the transformative benefits for your modern lab are often too compelling to ignore.
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LIMS and ELN are powerful laboratory software tools that serve different purposes. LIMS focuses on managing samples, workflows, and compliance, while ELNs support scientific documentation and collaboration. When integrated, they streamline operations, reduce errors, and improve data integrity across the lab.
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