Using a High-Throughput Microphysiological System to Model ADC- and Chemotherapy-Induced Peripheral Neuropathy

Peripheral neuropathy (PN) is a dose-limiting side effect of chemotherapeutic and antibody drug conjugate (ADC) treatment which significantly impacts patients’ quality of life. Despite a high clinical incidence of PN across monomethyl auristatin E (MMAE)-ADCs, it has not been predicted from standard preclinical toxicology studies. Advanced cell models including microphysiological systems (MPS) have the potential to bridge this gap and improve the predictive assessment of PN, enhancing the early selection of safer ADCs and improving clinical success. 

To model PN in vitro, axonal outgrowth MPS model incorporating human iPSC-derived peripheral neurons was employed. Neurons were embedded in extracellular matrix in the OrganoPlate®, a 3D microfluidic culture platform with 40 chips. The axons extend into an adjacent layer of gel, while the dendrites and soma remain in the somal compartment. Toxicity was assessed over three timepoints (48, 72, 96 h) and a clinically relevant concentration range, by labeling the axonal networks with calcein-AM and quantifying axonal outgrowth following confocal microscopy.

Our findings demonstrate the success of our MPS in vitro model to capture chemotherapeutic- and ADC-induced neurotoxicity, which was observed as a dose- and time-dependent disruption of the neurite network following compound exposure. Importantly, the compounds tested could be ranked by the level of neurotoxicity induced, highlighting the potential value of in vitro models as tools to select molecules with an improved PN toxicity profile for further progression, circumventing dependence on animal toxicology models. 

Learning Objectives:

1. Analyze how advanced cell models including micrphysiological systems (MPS) may bridge the translational gap between preclinical safety models of peripheral neuropathy (PN) and the clinic.

2. Interpret how to test a MPS of peripheral neuropathy (PN) to better select molecules for an improved PN profile.

3. Analyze axonal outgrowth data from an MPS model to assess dose- and time-dependent neurotoxicity of chemotherapeutics and ADCs.