In the United States, as many as 100 million people are estimated to suffer from pain every year. Opioids are some of the oldest analgesics, and they are still among the most effective treatments for pain. Unfortunately, opioids come with many adverse effects. They include sedation, nausea, tolerance, physical dependence, and respiratory depression, and they can lead to death in the event of an overdose. Widespread use of opioids has resulted in an epidemic of addiction and significant loss of life.

Efforts to develop novel, non-opioid pain therapeutics have been disappointing. Many promising programs with encouraging early data have ultimately failed in the clinic. Here, we look at three companies working on new approaches to pain drug discovery, plus one with a program for the development of digital biomarkers of pain. The ground covered by these companies includes a fresh approach to opioids as well as newer targets like NaV1.7 and a class of drugs—psychedelics—that has never before been investigated for pain.

Modeling, measurement, and analysis

“Pain, as we all now recognize, is a particularly tough nut to crack,” says Hongkang Zhang, PhD, director, pain therapeutic lead, Q-State Biosciences. To develop therapeutics that can overcome pain, Q-State leverages three key resources: patient-derived neuronal models, high-throughput optical electrophysiology tools, and next-generation artificial intelligence (AI)/machine learning–based computational resources.

Essentially, Q-State has an integrated platform for engineering disease-relevant in vitro cell models of pain, amassing neuronal activity measurements, and conducting AI/machine learning–based analytics. Using this platform, the company identifies disease-relevant parameters for the development of therapeutics. “Our in-house-designed and -built instrumentation enables recordings from approximately 100,000 neurons per multiwell plate with single-cell and single-action-potential resolution,” Zhang details. “[It provides] massive datasets with rich information content that are used to define disease phenotypes and mechanisms as well as characterize candidate therapeutic compounds.”

Q-State’s current focus is on voltage-gated sodium channels. The company’s pipeline of therapeutics includes a program for small-molecule inhibitors of NaV1.7 for osteoarthritis pain; antisense oligonucleotides targeting knockdown of NaV1.7 and NaV1.8 for moderate to severe pain; and a target-agnostic phenotypic screening program to identify small-molecule drugs that can reverse hyperexcitability in osteoarthritis. Q-State has completed a 200,000-compound small-molecule screening and identified novel NaV1.7 inhibitors with submicromolar potency and more than 100-fold selectivity against NaV1.5.

“This approach,” Zhang asserts, “has the potential to identify novel pain targets as well as therapeutics targeting diverse mechanisms.” Q-State plans to continue to advance its small-molecule and antisense oligonucleotide programs through IND toward clinical application.

New paradigms for pain

Research in psychedelic drugs flourished in the 1950s and 1960s. Newly discovered compounds such as lysergic acid diethylamide (LSD), psilocybin, mescaline, and dimenthyltryptamine (DMT) were found to have powerful effects on the brain while posing few risks of adverse effects. However, with the passage in the United States of the Controlled Substances Act of 1970, funding for studies of the medical benefits of psychedelic drugs dried up. Effectively banned for a half century, psychedelics are now experiencing a renaissance as potential treatments for intractable conditions such as depression, anxiety, and pain.

The therapeutic potential of psychedelics is being explored by Mind Medicine (MindMed), a biotech company that focuses on psychiatric and neurologic indications. One of the company’s priorities is the discovery of pain therapeutics.

“What MindMed is here to do is usher in an entirely new treatment paradigm using this incredibly well-studied class of molecules that we know as psychedelics,” says Robert Barrow, MindMed’s CEO. “If you look back to the 1950s and 1960s and research into LSD in particular, there are really fascinating studies where there’s analgesic effects both in acute severe pain conditions and chronic pain conditions.”

Barrow emphasizes the favorable pharmacology of psychedelics: “The systems targeted by these molecules are similar to those targeted by some of the serotonin and norepinephrine reuptake inhibitors that are approved for chronic pain. We see both mechanistic and direct evidence of analgesic effects.”

According to Barrow, early studies showed that a single dose of LSD reduced cancer pain for weeks, and that a three-week course of LSD at doses below the threshold for perceptual effects showed promise for treating phantom limb pain. What’s missing, Barrow notes, are modern, large-scale clinical trials for LSD and other psychedelics. To help fill the gap, MindMed is advancing several programs.

One program is exploring the analgesic effects of LSD, which are believed to be mediated by the serotonin receptor. Another program is pairing perceptual-level dosing of LSD and therapeutic guidance to treat generalized anxiety disorder. Yet another program, one that is being conducted in the Netherlands and Switzerland, is evaluating repeat low dosing of LSD for treating adult ADHD. Finally, MindMed recently finished a Phase I study of 18-MC, an ibogaine-derived molecule, as a treatment for addiction. Barrow adds that MindMed’s pain program is on track to open an IND and begin clinical trials in the second half of 2022.

Finding a functionally selective GPCR agonist

Opioids provide strong pain relief, but they pose serious problems such as respiratory depression, sedation, constipation, tolerance, and addiction. These problems are being addressed Mebias Discovery, a drug developer focused on pathway-selective drug discovery. The company’s co-founders and managing partners, Brett Tounge, PhD, and Shariff Bayoumy, point out that opioids exert their desirable effects via activation of G-protein-coupled signaling at the µ-opioid receptor, and their adverse effects via activation of β-arrestin signaling. The challenge then, is to activate signaling at the G-protein-coupled receptor (GPCR) while minimizing or eliminating β-arrestin signaling. This preferential signaling is commonly referred to in the field of GPCR drug discovery as biased agonism or functional selectivity.

Mebias Discovery develops drugs that target GPCRs and avoid adverse on-target effects. For example, the company’s lead candidate, MEB-1170, is designed to engage opioid receptors without causing the adverse effects common to opioid drugs. In the graph shown here, MEB-1170 is contrasted with morphine. Different signaling biases are associated with different propensities toward respiratory depression, as measured by partial pressure of oxygen in blood.

A limitation to developing biased GPCR agonists is that it has been impossible to measure bias beyond a threshold due to sensitivity limitations of cell-based assays. Mebias Discovery’s NMR-based platform (19Fluid) provides a fundamentally different read on bias by detecting the dynamic conformation of full-length GPCRs in solution. The platform uses 19F labeling to capture conformational changes indicative of either G-protein recruitment or β-arrestin recruitment with extreme sensitivity.

“Using the NMR platform with purified native GPCRs, we can achieve greater resolution and see further into the level of bias,” Bayoumy explains. “So, the fundamental basis of this is you can dial up the efficacy and you can dial down the adverse effects based on the degree of bias the agonist confers.”

Tounge adds that the compounds that the company has discovered are “cleaner,” and that its lead compound, a drug candidate called MEB-1170, does not have the typical adverse effects of opioids in preclinical in vivo studies. MEB-1170 targets the µ-opioid receptor for the treatment of acute/chronic pain. Phase I trials are planned to begin in 2022.

Preclinical programs are in progress for two drug candidates, MEB-1837 and MEB-1997, that target sphingosine-1-phosphate receptors subtype 1 (S1PR1) for the treatment of neuropathic pain. Like the MEB-1170 program, these programs make use of bias in GPCR signaling.

Bayoumy notes that Mebias Discovery’s strategy is to work with well-validated targets. “If you can take some of these targets that are out there and dial out the side effects, you redefine the standard of care in that area,” he elaborates. “That’s the philosophy we take.”

Enhancing pain research with digital biomarkers

Measures of pain used in clinical trials and even in clinical practice tend to be subjective. Patients are usually asked for a pain score, and a report on how well they are functioning or sleeping. Dean J. Mariano, DO, head of neuroscience and pain, Exploratory Medicine and Pharmacology, Eli Lilly & Company, is working on developing objective digital biomarkers as a complement to subjective data provided by the patient.

In addition to providing more consistent information for treatment and dosing, digital biomarkers can also be used to gain insight into the mechanisms of pain and the physical, sleep, and cognitive responses associated with pain. Mariano sees digital biomarkers as the next evolution in pain research to enhance our understanding of the pain experience by developing interventions that reduce not only the pain severity but improve on the other components that impact the patient’s life for a more personalized medicine approach.

One type of digital biomarker, Mariano says, could be provided by devices such as wearables or portable monitors to assess body movements, facial expressions, and sleep quality. For example, facial recognition technology is now used routinely to access personal computers and mobile phones. “You can actually use that type of technology to assess what are called facial action coding systems and understand what kind of experience [is causing] suffering,” Mariano says.

Emerging technology from disciplines such as psychiatry and neurodegenerative medicine can provide a rich source of potential pain biomarkers. For example, speech patterns such as frequent use of “I” statements, metaphors, or superlatives can be reflective of a pain experience.

“One of the big ones we’re focusing on is sleep,” Mariano points out. Looking at whether patients experience disrupted sleep, whether they’re moving a lot, or whether they’re up and down in the night can be indicative of pain in conditions such as diabetic neuropathy, chronic low back pain, and osteoarthritis. Mariano suggests that investigators can consider how these indicators factor into the overall quality of sleep and the restorative component of it, as well as how the lack of that restorative component may affect patients through the day.

Sleep factors, then, can be combined with other data such as gait changes. All this data can be used to predict events such as falls or pain episodes, or to track the effectiveness of pain medications or other interventions.

Mariano says that Eli Lilly is using an FDA guidance published in December 2021 for incorporating digital health technologies for remote data acquisition into its clinical trials. “We are developing our digital biomarker strategy to study how chronic pain disease biology reflects the natural course of the disease [and relates to] subjective and objective pain measures,” Mariano explains. “I believe the digital approach is going to evolve our understanding of the totality of a pain intervention’s efficacy and [improve the personalization of] pain treatments for individuals in clinical practice.”

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