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Artificial Intelligence in Clinical Pharmacy and Drug Safety
- AI concepts relevant to clinical pharmacy and drug safety
- Machine learning, NLP, predictive analytics, and generative AI use cases
- Medication-related risk identification and prioritization
- Adverse drug event and safety signal support
- Clinical documentation and patient-monitoring applications
- Bias, privacy, explainability, validation, and model performance
- Human oversight and safe integration into clinical workflows
Overview of the webinar
Artificial intelligence can process large and complex datasets that are difficult to evaluate manually, creating opportunities for clinical pharmacy and drug-safety teams. This webinar explores how AI-based approaches may support pharmacists in identifying medication-related risks, recognizing patterns in patient information, prioritizing clinical reviews, and strengthening drug-safety activities. Topics will include machine learning, natural-language processing, predictive analytics, and generative AI as they relate to clinical pharmacy workflows.
Practical applications will be considered across medication reconciliation, adverse drug event identification, drug interaction support, risk stratification, clinical documentation, patient monitoring, and safety surveillance. The session will distinguish between AI that assists professional decision-making and systems that may create unacceptable risks when used without adequate validation or human review.
Participants will also examine the governance issues that accompany AI use in clinical settings, including data privacy, security, bias, transparency, explainability, validation, performance monitoring, and accountability. The webinar emphasizes that AI should support—not replace—clinical judgment. Attendees will gain a practical framework for assessing AI outputs, recognizing common failure modes, and incorporating appropriate human oversight into AI-enabled clinical pharmacy and drug-safety processes.
Who should attend?
- Clinical Pharmacist
- Drug Safety Associate
- Drug Safety Pharmacist
- Clinical Research Professional
- Medication Safety Specialist
- Pharmacovigilance Professional
- Healthcare Data Analyst
- Healthcare IT Professional
Why should you attend?
Clinical pharmacy increasingly depends on timely interpretation of complex patient, medication, and safety information. AI can assist with identifying patterns, prioritizing risks, supporting clinical review, and processing large volumes of healthcare data. This session will help clinical pharmacy and drug-safety professionals understand where AI may complement their work and where human expertise remains essential. Participants will learn about practical applications of AI in medication-related risk identification, adverse event signal support, patient-specific decision-making, clinical documentation, and drug safety surveillance. The webinar will also highlight limitations including false positives, false negatives, biased datasets, incomplete patient information, model drift, explainability concerns, and inappropriate reliance on automated outputs. Attendees will leave with a clearer understanding of how to evaluate AI tools, establish appropriate oversight, and integrate technology into clinical workflows without compromising patient safety or professional accountability.
Faculty - Mr.Mohammed Ilham Ahmed
Mohammed Ilham Ahmed is a PharmD graduate and accomplished training professional with 8 years of experience spanning the Technology, Pharmacy, and Engineering sectors. He brings a rare blend of clinical pharmaceutical expertise and technical fluency, specializing in Pharmacy, the Microsoft Office Suite, and Artificial Intelligence. Known for translating complex, high-level concepts into practical, actionable learning, he empowers professionals and organizations to bridge the gap between healthcare knowledge and modern digital tools. His interdisciplinary approach and commitment to excellence make him a distinctive voice at the intersection of science, technology, and innovation.