Negin Imani Farahani ^1,2,3 Lisa Lin ^2,3,4 Shama Nazir ^2,3,4 Alireza Naderi ^2,3,4 Leanne Rokos ^3,5,6 Anthony Randal McIntosh ^3,5 Lisa Marie Julian ^1,2,3,4*

• ¹ Department of Molecular Biology and Biochemistry, Faculty of Science, Simon Fraser University, Burnaby, British Columbia, Canada
• ² Centre for Cell Biology, Development, and Disease, Faculty of Science, Simon Fraser University, Burnaby, British Columbia, Canada
• ³ Institute for Neuroscience and Neurotechnology, Simon Fraser University, Burnaby, Canada
• ⁴ Department of Biological Sciences, Faculty of Science, Simon Fraser University, Burnaby, British Columbia, Canada
• ⁵ Department of Biomedical Physiology and Kinesiology, Faculty of Science, Simon Fraser University, Burnaby, British Columbia, Canada
• ⁶ Rotman Research Institute, Baycrest Health Sciences, University of Toronto, Toronto, Canada

Precision, or personalized, medicine aims to stratify patients based on variable pathogenic signatures to optimize the effectiveness of disease prevention and treatment. This approach is favorable in the context of brain disorders, which are often heterogeneous in their pathophysiological features, patterns of disease progression and treatment response, resulting in limited therapeutic standard-of-care. Here we highlight the transformative role that human induced pluripotent stem cell (hiPSC)-derived neural models are poised to play in advancing precision medicine for brain disorders, particularly emerging innovations that improve the relevance of hiPSC models to human physiology. hiPSCs derived from accessible patient somatic cells can produce various neural cell types and tissues; current efforts to increase the complexity of these models, incorporating region-specific neural tissues and non-neural cell types of the brain microenvironment, are providing increasingly relevant insights into humanspecific neurobiology. Continued advances in tissue engineering combined with innovations in genomics, high-throughput screening and imaging strengthen the physiological relevance of hiPSC models and thus their ability to uncover disease mechanisms, therapeutic vulnerabilities, and tissue and fluid-based biomarkers that will have real impact on neurological disease treatment. True physiological understanding, however, necessitates integration of hiPSC-neural models with patient biophysical data, including quantitative neuroimaging representations. We discuss recent innovations in cellular neuroscience that can provide these direct connections through generative AI modeling. Our focus is to highlight the great potential of synergy between these emerging innovations to pave the way for personalized medicine becoming a viable option for patients suffering from neuropathologies, particularly rare epileptic and neurodegenerative disorders.