In an effort to address the critical public health need for new, safer and more effective medicines to treat pain, a consortium based at the Laboratory of Systems Pharmacology (LSP) at Harvard Medical School has launched an ambitious project titled STOP PAIN (Safe Therapeutic Options for Pain and Inflammation).
By combining a wide range of experimental and artificial intelligence-driven approaches, the consortium aims to identify compounds that selectively block the activity of nociceptors--the sensory neurons that sense and initiate pain--with the goal of developing new, preclinical drug candidates that offer an alternative to the opioid-based medications at the heart of the U.S. opioid epidemic.
The project is led by researchers from HMS and Boston Children's Hospital, with collaborators from Massachusetts Institute of Technology (MIT) and the Max Planck Institute for Medical Research in Germany.
It is supported by the U.S. Defense Advanced Research Projects Agency (DARPA) through the Panacea program, which aims to engender new therapies that address under-met medical needs of active duty soldiers and veterans. The DARPA cooperative agreement includes funding of up to $23,378,281.
The STOP PAIN consortium encompasses expertise across research disciplines, including neurobiology, systems pharmacology, stem cell biology, and computational and medicinal chemistry, and is led by:
We have substantial opportunities today to combine new laboratory methods, advanced chemistry and artificial intelligence and bring those tools to bear on the enormous societal, scientific and medical challenges of pain management.
Modern cancer care, for example, is now full of promising new medicines based on transformative science, yet if we look back two decades the field appeared to be stuck. We hope that advances in the science of sensation and computing will similarly shift the trajectory of drug development for pain."
Peter Sorger
According to the National Institute on Drug Abuse, an estimated 1.7 million Americans suffered from substance use disorders related to prescription opioid pain relievers in 2017 alone, and more than 47,000 died as a result of opioid overdose, leading government agencies to declare a nationwide public health emergency that year.
Prescription opioids are generally effective for the immediate and temporary treatment of severe pain, such as after trauma or surgery. However, they are only partially or not at all effective for chronic pain, and their prolonged use carries serious risks for developing tolerance, addiction and misuse.
Efforts to develop nonopioid pain therapies have been largely unsuccessful, highlighted, for example, by the high-profile recall of the prescription pain and inflammation drug Vioxx in 2014. Currently available medications such as acetaminophen and ibuprofen are not as effective as opioids and, when used long-term, can have adverse side effects that include gastrointestinal bleeding and liver damage.
Due to the lack of viable alternatives, prescription opioids remain a primary therapeutic option for the management of both acute and chronic pain.
"If we can successfully build better drugs to control pain, such that no physician would ever need to prescribe opioids because there would be safer and more effective options available, there would be an enormous impact on both the practice of medicine and on the societal catastrophe that the opioid epidemic has created," Woolf said. "As a consortium, we are keen to accept this challenge and to do everything possible to achieve this goal."
To identify new, nonopioid drug candidates, the STOP PAIN consortium is taking a unique approach that embraces the complexity of the biology of pain.
Current drug development processes in industry typically focus on screening for compounds that affect a single biological target--such as recent failed efforts to develop drugs targeting the protein Nav1.7, identified as defective in people with a congenital disorder that renders them insensitive to pain.
In contrast, the consortium will not begin with predetermined targets but instead focus on the activity of cells, specifically the nociceptor neurons responsible for initiating the sensation of pain.
"This project is based on the recognition that many of the most effective drugs for other neurological diseases have many molecular targets, not just one," Bean said. "Our goal is to systematically understand the complex network of molecules controlling the function of pain-sensing neurons and use that knowledge to design drug molecules that hit many targets, with the aim of safely and selectively inhibiting nociceptor function."
The team will screen for small molecule, nonopioid-based compounds that silence the activity of stem-cell derived human nociceptors under laboratory conditions.
The team will focus on compounds that exclusively block nociceptor function, while leaving the activity of other cell types, such as motor neurons or heart cells, unaffected. This selective targeting is a key preclinical marker of safety and specificity. These compounds then will be comprehensively analyzed for their molecular and biological characteristics, including effects on gene expression, protein production and cell physiology.
These data will be combined with insights drawn from INDRA (Integrated Network and Dynamical Reasoning Assembler), a powerful artificial intelligence system developed at the LSP, which automatically parses the scientific literature and public databases to construct models of gene and protein networks that can then be tested in the lab.
Together, these analyses aim to articulate the precise molecular mechanisms by which compounds inhibit nociceptor function and reveal the specific molecular targets involved in order to inform further drug development.
Once fully characterized, promising compounds will be refined or redesigned through computational and experimental chemistry techniques to maximize their potential efficacy.
The compounds will then be tested for safety and efficacy for pain management in preclinical models and through new machine vision and learning tools developed by the consortium.
By integrating these complementary approaches, the STOP PAIN consortium intends to generate thoroughly evaluated drug candidates for submission to the U.S. Food and Drug Administration for Investigational New Drug designation.
In addition, the team believes that the shift from a target-based approach to a cell-based screening approach backed up by sophisticated computational modeling could help transform the process of drug discovery and validation by offering an alternative model to address other critical unmet therapeutic needs.
Drug development is notoriously slow and arduous, but the researchers say they are optimistic that the depth and breadth of their collective expertise--drawn from multiple disciplines and institutions--makes it possible to develop drug candidates suitable for human clinical trials within the five-year time frame of the project. As one measure of progress, new compounds are already being synthesized and tested by the team.
This project is closely aligned with the recently launched Therapeutics Initiative at HMS, which aims to expedite the translation of basic science discoveries into new treatments for patients.
To this end, the consortium will pursue development of the most promising drug candidates through new ventures or collaborations with existing pharmaceutical or biotech companies. This includes working with life sciences incubators such as the Pagliuca Harvard Life Lab or the recently announced Blavatnik Harvard Life Lab Longwood, which both support early-stage, high-potential biotech and life sciences projects from the Harvard community.
"The development of safer medications to replace prescription opioids for pain management remains one of the most pressing unmet needs in medicine," said George Q. Daley, Dean of HMS. "This ambitious multi-institutional consortium offers promise for improving the health and well-being of countless patients and families."
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Consortium launches ambitious project to transform the treatment of pain - News-Medical.net
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