Background & Aims

More than 100M people in the US suffer from chronic pain1,2. Although several therapeutic treatments exist, including NSAIDs, opioids, and gabapentinoids, a substantial fraction of patients remain inadequately treated3,4. Moreover, current pain therapeutics have significant adverse effects5–7. Notably, abuse of highly addictive opioids is a current public health crisis8. There has been minimal success in developing improved, non-opioid analgesics over past decades. To address this challenge, Quiver Bioscience has developed an integrated CNS discovery platform for identification of effective chronic pain therapeutics across different modalities, including small molecules (SMs) and antisense oligonucleotides (ASOs)9. Candidate therapeutic molecules are optimized for their ability to rescue disease-relevant cellular phenotypes while minimizing off-target effects.

Methods

We have integrated technologies along three axes—i) translational disease models using human cells, ii) cellular-resolved measurements of excitability using all-optical electrophysiology, and iii) quantitative assessment of candidate therapeutic rescue using machine learning driven analysis—all into a proprietary platform for high-throughput, high-content drug discovery for chronic pain. We have developed both target-focused spiking HEK cell models for validated pain targets (Nav1.7, Nav1.8)10 as well as target-agnostic high content ‘pain-in-a-dish’ assays for phenotypic assessment, where rodent or human iPSC-derived sensory neurons are exposed to a mixture of inflammatory mediators mimicking pain sensitization11. We have now used these methods to perform two focused therapeutic discovery efforts: i) a phenotypic SM screen for osteoarthritis/OA pain using an annotated library of approved drugs and ii) Nav1.7 target-focused screens for novel SMs and ASOs for cancer and neuropathic pain.

Results

Our screens yielded functional recordings from 100s of sensory neurons in parallel with single cell resolution, with a throughput of >500k neurons/day12. A target-agnostic screen of approved drugs identified known analgesics and novel mechanisms such as kinase inhibitors that rescued the OA phenotype, indicating that the MAPK pathway is involved in OA pain sensitization in sensory neurons11. Our target-focused Nav1.7 screens resulted in candidate SMs and ASOs. A 200k SM screen using our spiking HEK assay identified a potent inhibitor with >10-fold subtype selectivity against Nav1.513. We also screened for ASOs, identifying potent and selective hNav1.7 ASO lead candidates with confirmed activity in human primary DRG neurons. Intrathecally injected ASOs knockdown mRNA expression in DRG neurons and rescue ex-vivo and in vivo rodent pain behavioral measurements. ASOs rescue our cancer pain in vitro phenotype and are being tested in a model of small fiber neuropathy (Nav.1.7-I228M14).

Conclusions

Our integrated platform provided a unique, enabling ability to identify novel therapeutics for chronic pain. Our target-agnostic screening platform in both rodent and human sensory neurons allowed for studying pain biology in intact neuronal systems. A screen of annotated compounds revealed diverse potential analgesic mechanisms including known ion channel modulators as validation but also identified novel mechanisms such as kinase (e.g. MEK) inhibitors for OA pain. Our spiking HEK target-focused assays provided the rich information content of automated patch clamp, but with 5-10 times increased throughput10. We developed potent and selective SMs as well as rodent and human Nav1.7 specific ASO gapmers with in vitro and in vivo activity and acceptable tolerability profiles. We demonstrated that Nav1.7 ASOs can reverse hyperexcitability in our ‘pain-in-a-dish’ models. The intrathecally injected ASOs demonstrated the desired PK/PD profiles and increased thermal threshold.

References

1.Gaskin, D. J. & Richard, P. The economic costs of pain in the United States. Journal of Pain 13, 715–724 (2012).
2.Tompkins, D. A., Hobelmann, J. G. & Compton, P. Providing chronic pain management in the “Fifth Vital Sign” Era: Historical and treatment perspectives on a modern-day medical dilemma. Drug and Alcohol Dependence 173, S11–S21 (2017).
3.Yekkirala, A. S., Roberson, D. P., Bean, B. P. & Woolf, C. J. Breaking barriers to novel analgesic drug development. Nature Reviews Drug Discovery 16, 545–564 (2017).
4.Johannes, C. B., Le, T. K., Zhou, X., Johnston, J. A. & Dworkin, R. H. The Prevalence of Chronic Pain in United States Adults: Results of an Internet-Based Survey. The Journal of Pain 11, 1230–1239 (2018).
5.Wehling, M. Non-steroidal anti-inflammatory drug use in chronic pain conditions with special emphasis on the elderly and patients with relevant comorbidities: management and mitigation of risks and adverse effects. European Journal of Clinical Pharmacology 70, 1159–1172 (2014).
6.Benyamin, R. et al. Opioid complications and side effects. Pain Physician 11, S105–S120 (2008).
7.Wiffen, P. J. et al. Gabapentin for chronic neuropathic pain in adults. Cochrane Database of Systematic Reviews (2017) doi:10.1002/14651858.CD007938.pub4.
8.Grosser, T., Woolf, C. J. & FitzGerald, G. A. Time for nonaddictive relief of pain. Science 355, 1026–1027 (2017).
9.C, R. & MJA, W. Antisense oligonucleotides: the next frontier for treatment of neurological disorders. Nature reviews. Neurology 14, 9–22 (2018).
10.Zhang, H. et al. Correlation of Optical and Automated Patch Clamp Electrophysiology for Identification of NaV1.7 Inhibitors. SLAS Discovery 25, 434–446 (2020).
11.Liu, P. et al. A phenotypic screening platform for chronic pain therapeutics using all-optical electrophysiology. Pain (2023) doi:10.1097/j.pain.0000000000003090.
12.Werley, C. A. et al. All-optical electrophysiology for disease modeling and pharmacological characterization of neurons. Current Protocols in Pharmacology 2017, 11.20.1-11.20.24 (2017).
13.Borja, G. B. et al. Highly Parallelized, Multicolor Optogenetic Recordings of Cellular Activity for Therapeutic Discovery Applications in Ion Channels and Disease-Associated Excitable Cells. Front Mol Neurosci 15, 896320 (2022).
14.Chen, L. et al. Two independent mouse lines carrying the Nav1.7 I228M gain-of-function variant display dorsal root ganglion neuron hyperexcitability but a minimal pain phenotype. Pain 162, (2021).

Presenting Author

Hongkang Zhang

Poster Authors

Hongkang Zhang

PhD

Quiver Bioscience

Lead Author

E-mail

Pin Liu

Lead Author

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Gabriel Borja

Lead Author

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Fabricio Simao

Lead Author

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Dawei Zhang

Lead Author

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Jane Jacques

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Jennifer Grooms

Lead Author

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Adam Barnett

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Christopher Werley

Lead Author

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Benjamin Harwood

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Yang Lu

Lead Author

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Caitlin Lewarch

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Amy Elder

Lead Author

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Luis Williams

Lead Author

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David Gerber

Lead Author

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Owen McManus

Lead Author

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Graham Dempsey

Lead Author

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Topics

  • Novel Experimental/Analytic Approaches/Tools