Are patient-derived models of amyotrophic lateral sclerosis a game changer for novel drug discovery?

ALS drug discovery has long depended on model systems that incompletely capture human disease heterogeneity, aging, and TDP-43 proteinopathy. Patient-derived platforms have therefore emerged as increasingly important human-relevant complements to animal and molecular models.

This Critical Perspective examines when patient-derived ALS models genuinely change therapeutic decision-making rather than merely add mechanistic insight. The authors then propose a heuristic framework based on disease-relevant phenotype recapitulation, capture of patient-to-patient heterogeneity, and generation of findings that influence therapeutic prioritization or clinical translation. Furthermore, the authors evaluate iPSC-derived motor neurons, directly reprogrammed neurons, glial co-cultures, organoids, neural networks, and organ-chip systems against these conditions, while also addressing aging fidelity, reproducibility, upper motor neuron modeling, and regulatory implementation.

Patient-derived models are not yet standalone decision-grade tools for ALS drug development. Their present value lies in functioning as a human-biology filter for target discovery, reverse translation, biomarker development, and patient stratification when used within rigorous, standardized, and clinically linked workflows. The strongest current evidence supports proof-of-principle rather than generalized predictive validity.