Multi-organ-on-chip device for modeling opioid reinforcement and withdrawal, and the negative affective component of pain: a therapeutic screening tool.

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SUMMARY This supplemental application is to facilitate fulfillment of previously modified milestones prior to transition to the UH3 phase. This request for supplemental funds is a result of significant impediments to progress resulting from restriction of operational capacity during the COVID-19 pandemic. While significant progress has been made, the additional time required to complete the milestones will result in us incurring additional personnel and supply costs. The overall significance and scope of the project remains the same as the original proposal. There is a desperate need to develop therapeutics for treatment of opioid use disorder (OUD), and also to develop pain treatments that are non-addictive. Both of these goals will be served by high-throughput models amenable to drug screening, based on human cells, that recapitulate features of the neurobiology underlying the addictive process. The model we are developing focuses on a key component of addictive circuitry – the dopaminergic and GABAergic neurons of the midbrain, long recognized as responsible for mediating the reinforcing properties of many classes of abused drugs, including opioids. We are developing a multi-organ microphysiological system (MPS) based on human induced pluripotent stem cell (iPSC)-derived midbrain dopamine (DA)/Gamma-Amino Butyric Acid (GABA) neurons on a 3-dimensional platform that ultimately will incorporate microglia, blood-brain-barrier and liver metabolism components. RNA sequencing (RNAseq) and metabolomics analyses will complement the primary DA release measure to identify novel mechanisms contributing to chronic opioid-induced plasticity in DA responsiveness thought to underlie 1) the anhedonia characteristic of opioid withdrawal; 2) the negative affective component of chronic pain states; 3) craving and relapse. The chronic pain-relevant aspect of the model will be realized by examination of aversive kappa- mediated opioid effects on DA transmission in addition to the commonly abused mu opioid receptor agonists, and by incorporation of inflammatory-mediating microglia into the model. Throughput will be increased by the integration of online sensors into the MPS for online detection of DA.