Laboratory Testing & Sample ManagementPurpose
1.2. Automator flags anomalies or deviations outside set thresholds, automating notification to supervisors and validation personnel for rapid corrective action.
1.3. Automated anomaly detection reduces compliance risks, automates recordkeeping, and enables auditing for regulatory standards (e.g., FDA, EMA).
1.4. Supports automated documentation by sending flagged events to digital logs or LIMS for full traceability and record retention.
Trigger Conditions
2.2. Receipt of new test results from laboratory instruments.
2.3. Scheduled batch QC review (e.g., end of day/process).
2.4. Manual initiation of automated QC for a selected sample or analysis run.
2.5. Reception of external or third-party data requiring automated validation.
Platform Variants
• Feature/Setting: Custom Apex trigger; configure Record Updated trigger to automate checks on sample data uploads.
3.2. LabWare LIMS
• Feature/Setting: Automated rules engine for QC; set up event scripts for threshold-based anomaly alerts.
3.3. STARLIMS
• Feature/Setting: Data Analysis API; configure with alert automation when quality metrics fail validation.
3.4. Thermo Fisher SampleManager LIMS
• Feature/Setting: Workflow Automation; schedule automated QC tasks and flagging by script.
3.5. Azure Logic Apps
• Feature/Setting: Recurrence trigger + Data Operations; automate routine QC checks over cloud-stored files.
3.6. Amazon EventBridge
• Feature/Setting: Rule-based automation; receive data uploads, route events to Lambda automators for QC.
3.7. Zapier
• Feature/Setting: Scheduled Zap; connect LIMS to email/Slack for automating anomaly notifications.
3.8. Microsoft Power Automate
• Feature/Setting: Automated flow with "When an item is modified" SharePoint trigger for lab data QC.
3.9. Google Cloud Functions
• Feature/Setting: Pub/Sub trigger; automate execution of Python anomaly checks on incoming lab files.
3.10. IBM Watson Studio
• Feature/Setting: Automated Model Deployment; configure anomaly detection models for live lab datasets.
3.11. Datadog
• Feature/Setting: Monitor alerting + API integration; automate alerts when metrics breach QC thresholds.
3.12. Splunk
• Feature/Setting: Data ingest & alert search; define queries to automate flagging QC failures.
3.13. Twilio SendGrid
• Feature/Setting: Email API integration; automate outbound alerts to QC or supervisory staff.
3.14. Slack
• Feature/Setting: Incoming Webhooks; automate instant lab team notifications upon QC anomalies.
3.15. PagerDuty
• Feature/Setting: Event Orchestration; automate escalations of flagged QC incidents.
3.16. Smartsheet
• Feature/Setting: Automation rules to lock rows or alert if data exceeds acceptable QC limits.
3.17. Trello
• Feature/Setting: Butler Automation; auto-create cards for each flagged laboratory QC anomaly.
3.18. Monday.com
• Feature/Setting: Automate board status changes upon receiving flagged QC reports via API.
3.19. Webhooks (Generic)
• Feature/Setting: Custom webhook; push flagged data to third-party dashboards automatically.
3.20. DocuSign
• Feature/Setting: Automated envelope creation for non-conformity records triggered by flagged QC.
3.21. ServiceNow
• Feature/Setting: Flow Designer; automate incident creation for flagged samples needing review.
3.22. Jira
• Feature/Setting: Automation for Jira; set rules that open tickets upon receiving flagged anomaly data.
Benefits
4.2. Automated escalations shorten response times for handling out-of-spec results.
4.3. Automation supports regulatory compliance by automating recordkeeping and audit trails.
4.4. Automated notification ensures rapid, systematic team awareness of potential laboratory issues.
4.5. Automating QC limits disruption to operations, improving productivity and reliability in pharmaceutical testing labs.