A human stem cell phenotypic drug screening assay for identification of opioid and non‐opioid analgesics with lowered risk of addiction

Abstract

Mu opioid receptors, a subclass of G protein-coupled receptors (GPCRs), are involved in the control of pain perception and reward properties. They are also the primary molecular target of opioid drugs and mediate their efficacious analgesic effects, euphoric properties, as well as undesired negative side effects such as tolerance and physical dependence. The biology of pain is complex and has considerable redundancy, thus screens that observe the effect of a single protein, cell lineage, or animal model(s) may be fated for failure. In an effort to find analgesics with lessened risk of addiction we designed Biological Assay for Next Generation Analgesics (BANGA). BANGA is a phenotypic approach using human stem cells (hESC, hiPSC, and/or directly converted neurons) to generate human neurons involved in pain signaling such as sensory neurons (pain), and dopaminergic neurons (reward and addiction) that together with other neurons and glia, used for 3D printed tissue organoids, authentically represent Dorsal Root Ganglion (DRG) and Ventral Tegmental Area (VTA), in different “banks” of drug screening assays. High throughput calcium imaging of human nociceptors, in the DRG organoids, quantitates sensory pain input and its dose response inhibition by candidate analgesic drugs. To reveal addiction risk, dopaminergic neurons’ quantitative secretion of dopamine, in the VTA organoids, measures analgesic drugs’ level of risk for dependence and addiction. All reprogrammed and directly converted neurons and glia used in this assay are patient specific, making studies of pain and addiction patient cohorts possible. The BANGA assay is a dramatic shift from the commonly used models for anti-pain drug discovery and could revolutionize the discovery of the next generation analgesics. Our presentation will include results of BANGA screening of commercially available FDA approved compound libraries that has so far identified novel classes of opioid and non-opioid efficacious analgesic drugs with low to no risk of dependence and addiction.