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OpenLearning

AI IN CLINICAL PHARMACY

via OpenLearning

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Overview

Master AI & Machine Learning for 50% Off
Go under the hood of AI — neural networks, real-world applications & more. Designed by UNSW experts.
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This advanced course develops pharmacists’ ability to evaluate and safely override AI outputs in clinical practice. It applies pharmacological reasoning to decision-support alerts, pharmacogenomic insights, dosing software, antimicrobial stewardship, predictive analytics, and fragmented specialist systems across ICU, oncology, and ambulatory scenarios.

Syllabus

  • Identify the categories of AI tools encountered in clinical pharmacy practice, explain their clinical value and key limitations, and describe the pharmacist's role in evaluating rather than simply accepting AI-generated outputs.
  • Apply pharmacological reasoning to evaluate CDSS alerts and AI-integrated EHR workflow outputs and interpret pharmacogenomic AI insights to make precision pharmacotherapy decisions that go beyond the AI's single-gene recommendation.
  • Apply Bayesian dosing software with appropriate population pharmacokinetic model selection, evaluate AI antimicrobial stewardship recommendations against real-time resistance data, and integrate predictive analytics and telepharmacy AI outputs with direct pharmacist clinical assessment.
  • Resolve conflicting outputs from disease-specific AI systems using cross-guideline synthesis, identify and deprescribe anticholinergic prescribing cascades, and integrate frailty, falls risk, and patient-centred factors that isolated AI risk scores cannot assess.
  • Identify root-cause medication contributions to drug-induced clinical problems rather than accepting AI symptom-management suggestions and integrate conflicting outputs from multiple fragmented specialist AI systems into a single, safe, patient-centred medication plan.
  • Demonstrate integrated AI evaluation and clinical override competencies across simulated ICU, oncology, and ambulatory pharmacy scenarios, applying the assess–verify–decide–document sequence and identifying AI errors that would cause patient harm if undetected.

Taught by

Eshwar Madas

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