This review synthesizes evidence on biotoxin assessment using organoids and organ-on-chip systems, suggesting best practices for improved methodologies.
Human organoids and organ-on-chip/microphysiological systems (OoC/MPS) are increasingly used as new-approach methodologies for biotoxin assessment. They retain human-relevant tissue organization and enable interpretable analysis of exposure geometry, barrier transport, perfusion, and (when needed) multi-organ coupling. In this review, we synthesize primary evidence across major toxin classes, including bacterial enterotoxins (e.g., cholera toxin, heat-stable enterotoxins, Shiga toxins), mycotoxins (e.g., aflatoxin B1, ochratoxin A, deoxynivalenol), and algal/cyanobacterial toxins (e.g., saxitoxin, domoic acid, microcystins, biliatresone). We emphasize studies that clearly define toxin identity and exposure context and that demonstrate mechanism-critical model competencies under assay conditions. We highlight decision-informative functional endpoints that align with the dominant pathophysiology. These include cystic fibrosis transmembrane conductance regulator (CFTR)-dependent secretion in human enteroids/colonoids, transporter-linked proximal tubular injury in kidney MPS, gut–kidney axis injury from Shiga toxin-producing E. coli in microfluidic systems, and multi-electrode array (MEA) network readouts in human 3D neural tissues. We then summarize best practices that improve cross-study comparability. These include reporting delivered versus nominal exposure, assessing recovery/mass balance and device/material interactions, applying proportional biological qualification (polarity, transporter/enzymatic competence, functional stability), defining a minimal comparable endpoint core, and preserving QIVIVE readiness in reporting. Finally, we outline near-term priorities for the field, including chronic low-dose and mixture designs, harmonized reference panels and acceptance criteria, and fit-for-purpose escalation to coupled OoC/MPS only when perfusion or organ–organ coupling is expected to change the interpretation.
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Li et al. (2026) studied this question.
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