Workshop 3: Advancing Rational Drug Treatment: Integrating People, Computerized Decision Support and Artificial Intelligence
Tracks
Track 1
| Sunday, July 12, 2026 |
| 11:15 AM - 1:15 PM |
Details
The workshop "Advancing Rational Drug Treatment: Integrating People, Computerized Decision Support and Artificial Intelligence" aims to explore cutting-edge innovations in the use of technology for enhancing drug therapy management, as well as human factors. With the rapid advancements in artificial intelligence (AI) and computerized decision support systems (CDSS), healthcare professionals are equipped with potentially powerful tools to optimize medication use, improve patient outcomes, and reduce adverse drug events. This workshop will bring together esteemed speakers from around the globe, each of whom is a pioneer in their respective fields of computerized decision support for rational drug treatment. The agenda includes short keynote presentations that highlight recent research breakthroughs, practical applications, and case studies demonstrating successful implementation of these technologies. A dynamic panel discussion will provide an interactive platform for experts to debate the future directions and ethical considerations of AI in drug treatment. Attendees will have the opportunity to engage with the speakers during a Q&A session and network with peers to foster collaboration and innovation. By bridging the gap between technological advancements and clinical practice, this workshop aspires to empower healthcare providers with the knowledge and tools necessary for rational drug treatment in the digital age.
Speaker
Prof Melissa Baysari
The University Of Sydney
The impact of drug-drug interaction alerts on drug-drug interactions and patient harms
Biography
Professor Melissa Baysari leads the Digital Health Human Factors Group at the University of Sydney, Australia. Her team apply human factors methods and approaches to evaluate and optimise health technologies to support healthcare work and improve patient safety. Melissa has published widely in the areas of medication safety, electronic medical record systems and decision support systems, and she has secured over AUD $30Mill in research funding. Importantly, Melissa’s research has resulted in a number of significant changes being made to clinical information systems, as well as to hospital policy and work practices, and her research has informed clinical decision support design guidelines both nationally and internationally.
Assoc Prof Matt Doogue
University of Otago & Health New Zealand
Clinical decision support for medicines use – an ontological challenge
Biography
Matt Doogue is a clinical pharmacologist passionate about applying clinical pharmacology principles to patient care. He has clinical and academic roles in clinical pharmacology and is a physician in a busy acute general medicine service. His interests include quality use of medicines, adverse drug reactions, clinical decision support, and therapeutic drug monitoring.
Dr Kenji Fujita
Kolling Institute
Advancing Pharmacy Practice in Japan Through AI and CDSS for Medication Optimisation
Biography
Dr. Kenji Fujita is a Postdoctoral Research Fellow at the Laboratory of Ageing and Pharmacology, Kolling Institute, University of Sydney. His research focuses on evaluating interventions for deprescribing inappropriate polypharmacy in older inpatients, developing a multidomain frailty index using routinely collected clinical data, and investigating the impact of deprescribing on physical functions in older mice with polypharmacy using neural network models. Since 2020, he has served as the working group co-lead on guidelines and indicators within the Pharmaceutical Care Network Europe (PCNE). With expertise in big data analysis, epidemiology, statistical modelling, and web application development, he has co-led a Japanese government funded project developing and validating quality indicators for community pharmacies (2024-2026).
Session chair
Ylva Bottiger
Linköping University
Lisa Kouladjian O'Donnell
University of Sydney
