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Optimizing Community Pharmacy Workflow with Real-time Anomaly Detection Using Artificial Intelligence (GRA-039)

Summary ~

  • Grant ID: GRA-039
  • Sponsor / funder: DePaul ↔ RFUMS partnership
  • Program: AI in Biomedical Discovery and Healthcare
  • Status: awarded
  • Period: 2025 – —
  • Lead unit: Driehaus College of Business / Jarvis CDM
  • Amount: $47,343

Award details

  • Topics: artificial_intelligence, healthcare, pharmacy
  • Grant type: research_grant

DePaul PIs Sina Ansari (BUS) and Vahid Alizadeh (CDM); RFUMS PI Ateequr Rahman; Award $47,343; real-time AI anomaly detection for community pharmacy workflow optimization.

People

  • Sina Ansari (PI) — person identity unresolved
  • Vahid Alizadeh (Co-PI) — person identity unresolved
  • Ateequr Rahman (Collaborator) — person identity unresolved

None documented.

None documented in outputs layer.

See PI person pages for linked publications; grant-level publication edges not yet indexed.

Verification

  • Status: repo_derived (~)
  • Confidence: high
  • Notes: 2025 RFUMS collaborative award; parent program GRA-029. No DePaul facility named in source.

Source URLs

Notes

Internal knowledge object — award metadata for Resource Map hypertext navigation. Full provenance retained in data/grants.yaml.