In this free webinar, learn how AI in scientific research is influencing translational practices and improving therapeutic development. Attendees will analyze supervised and unsupervised learning approaches in AI model training. The featured speakers will examine case examples of AI applications in preclinical research and drug discovery. Attendees will identify methodological and data-related limitations affecting AI reliability. The speakers will also discuss strategies to enhance translational relevance through AI integration.

TORONTO, Sept. 24, 2025 /PRNewswire/ -- Artificial intelligence (AI) is rapidly transforming how scientific research is conducted, from accelerating model development to uncovering novel drug discovery pathways. However, with every promise comes complexity — and the need for critical evaluation.

This webinar brings together perspectives from neuroscience, software development and academia to explore how AI is trained (supervised vs. unsupervised learning), where it excels and where its limitations lie. The featured speakers will examine real-world applications in preclinical and translational research, highlight potential pitfalls that can compromise results and discuss strategies for integrating AI tools effectively and responsibly.

Drawing on extensive experience in translational neuroscience, the conversation will focus on how AI can help create more predictive models, reduce the gap between laboratory findings and clinical outcomes and ultimately accelerate the development of safer, more effective therapies.

Register for this webinar to learn how AI in scientific research is influencing translational practices and improving therapeutic development.

Join Dr. John Huxter, PhD, Associate Director and Global Head of Rodent Electrophysiology and Data Science, Transpharmation; Dr. Na Helian, PhD, Associate Professor in Research, University of Hertfordshire; and Dr. Winthrop Gillis, PhD, Scientific consultant, Self-employed, for the live webinar on Wednesday, October 8, 2025, at 10am EDT (4pm CEST/EU-Central).

For more information or to register for this event, visit AI and Machine Learning Uses in Neuroscience Drug Discovery.

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