Semaphore Solutions

A successful LIMS implementation doesn’t start with software—it starts with people. Too often, labs dive into requirements and workflows without first asking: 👩🔬 Who will be using this system? 🔄 What do they need from it—day to day, week to week? 🧭 Why does their role matter to the broader lab mission? In this blog post, we explore why defining lab personas—the real users behind your lab software—creates better alignment, smoother adoption, and systems that actually get used. 🔗 Read the full post: https://lnkd.in/etsh35Cp #LabInformatics #LIMSImplementation #DigitalLab #UserExperience #ChangeManagement #LabPersonas #ClinicalLabs #LabSoftware

Legacy lab software may still be running—but is it holding your lab back? Outdated systems can quietly limit your ability to adapt, scale, and integrate with modern tools. In Part 1 of our classic blog, we explore: 🔍 Common pain points with legacy lab software ⚙️ The hidden costs of patching vs. replacing 📈 Key considerations for deciding whether to modernize If your lab is relying on a system that’s been “good enough” for years, this is your guide to spotting the warning signs and planning for what’s next. 🔗 Read the full post: https://lnkd.in/eVFiTn5C #LabInformatics #LegacySystems #LIMS #DigitalLab #SystemModernization #LabSoftware #LaboratoryIT

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Reposting this because I think labs are too quick to merge assay and system validation into a single, tangled effort. Yes, they touch each other. No, they shouldn’t always be managed together. Assay validation is about scientific method. System validation is about software quality and compliance. When you blend them too closely, you often end up with: – Confusing test ownership – Delays driven by cross-dependencies – And a validation package that’s harder to maintain over time This blog unpacks how and when to separate—and why doing so can actually lead to stronger validation with less friction.

In many labs, assay validation and computer system validation (CSV) get lumped together into one effort—but that’s often a mistake. While they’re both essential, they serve very different purposes: 🧪 Assay validation proves that the lab method works 💻 System validation ensures the software operates reliably and compliantly When labs combine them by default, they risk: ❌ Redundant testing ❌ Misaligned timelines ❌ Cloudy ownership and accountability Our latest blog encourages labs to take a more deliberate approach—analyzing where coordination is needed, but separating when it adds clarity and efficiency. 🔗 Read the full post: https://lnkd.in/ejDCw-fH #LabInformatics #CSV #AssayValidation #ValidationStrategy #ClinicalLabs #RegulatedLabs #DigitalLab #LIMS

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LIMS implementations don’t fail because the “happy path” wasn’t clear. They fail because teams weren’t ready for what happens outside of it. In this classic post, we cover 5 key considerations that help labs move beyond ideal scenarios and plan for real-world complexity—like: 🔄 Handling edge cases and exceptions 🤝 Engaging users and stakeholders early 🔧 Making room for iteration and change If you’re planning a LIMS implementation (or recovering from one that went off-track), these practical insights will help you build a more resilient path forward. 🔗 Read the full post: https://lnkd.in/e83cGMhV #LIMS #LabInformatics #DigitalLab #LIMSImplementation #ChangeManagement #LabSoftware #SystemsThinking

Electronic records aren’t just digital versions of paper—they’re foundational to how modern labs operate. Whether you’re in clinical diagnostics, R&D, or regulated production, how your lab stores and manages records has major implications for compliance, traceability, and data integrity. In our latest blog post, we explore: 📄 What electronic records actually are 🔍 Why they matter for every lab—not just regulated ones 🧠 What to look for in a lab system that handles electronic records well If your lab is scaling, modernizing, or preparing for greater compliance expectations, this post is a must-read. 🔗 Read the full post: https://lnkd.in/eBnEuHR5 #LabInformatics #ElectronicRecords #DigitalLab #DataIntegrity #LIMS #21CFRPart11 #LaboratoryIT

When it comes to reporting and analytics, LIMS data is only part of the picture. But how should you connect that data to the broader enterprise stack? 🔗 Do you integrate with a data warehouse? 🌐 Or use data federation to query across systems? In this classic blog post, we explore: 📊 The pros and cons of each approach 🏗️ What labs should consider based on complexity, performance, and compliance 💡 Why your lab’s informatics strategy should influence the decision If you’re planning to scale reporting or data analytics across lab systems, this breakdown will help clarify the path. 🔗 Read the full post: https://lnkd.in/edVJdRp3 #LabInformatics #LIMS #DataWarehouse #DataFederation #LabDataStrategy #DigitalLab #EnterpriseData

Two weeks ago, we broke down the six types of software requirements in lab informatics: https://lnkd.in/enZFaU9r But understanding the types is just the beginning. To bring a requirement to life, you need to answer a more practical question: 👉 How will we know when it’s done—and done right? That’s where acceptance criteria come in. In our latest blog post, we dive into: ✅ What makes acceptance criteria different from requirements 🧪 Why they’re so essential in lab software projects 🛠️ How clear criteria improve quality, reduce ambiguity, and make validation smoother If you’re specifying, reviewing, or implementing LIMS or lab workflows, this is the bridge between vision and execution. 🔗 Read the full post: https://lnkd.in/erfAn9sT #LabInformatics #LIMS #SoftwareRequirements #AcceptanceCriteria #DigitalLab #ValidationReady #LabSoftware