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Ten capabilities worth checking before you commit, including templates, version control, instrument integration, full text search, mobile access and reporting.
Highlights from the show floor: AI-driven sample routing, liquid handling robots, cobots, cloud and IoT-connected systems, and digital twins for lab workflows.
Practical steps for flu season: scalable data systems, workflow automation, supply planning, staff readiness and surveillance reporting when volumes spike.
The cost case for handing sample storage and logistics to a third party, the risks worth weighing, and what to look for when choosing a partner.
FDA data integrity expectations and the EU move to MDR and IVDR are reshaping lab record-keeping. Here are the challenges and the systems that absorb them.
A walkthrough of the three suites, what each one handles, and how sample management, scientific documentation and automation fit together on one platform.
A side-by-side breakdown of what each system does, the financial case for each, the scenarios that call for both, and what delaying the decision tends to cost.
Cloud collaboration for research teams: shared access to data, consistent entry standards, version control and audit trails, plus habits that keep sites in sync.
Nine changes clinical labs see after leaving manual tracking behind, covering accessioning, data integrity, health record links, analytics, QA and margins.
The pressures on quality control teams and the tooling that answers them, with examples from pharmaceutical, food, automotive and cosmetics testing.
