Chronic abdominal and pelvic pain have historically been difficult to treat, but new research and tools — including artificial intelligence (AI) — are beginning to make a difference.
Anna Malykhina, PhD, professor in the Division of Urology in the University of Colorado Anschutz Department of Surgery, explores the topic in a recent perspective paper for the journal Frontiers in Pain Research, for which she serves as chief editor for the Section on Abdominal and Pelvic Pain.
“I wanted to write about the future of abdominal and pelvic pain research — what is important today, and what will be even more important tomorrow,” Malykhina says. “How can we adapt all these new directions in pelvic research and take it to the next level? How can we develop organoids? How can we incorporate new AI technologies in the research? What are their advantages, and what are the challenges we will face when we start using them?”
One of the factors that makes chronic pain difficult to treat, Malykhina says, is that we usually cannot determine what triggered the pain in the first place. That’s especially true when the central nervous system (CNS) gets involved, amplifying pain signals and causing neurons to respond to even small triggers.
“In general, pain is a good thing, because it's a signal for us,” she says. “If we touch something hot or something sharp, the pain response is there to warn us. It's very important signaling for us to have. But when it becomes chronic, it creates lots of other issues that cause a significant decrease in quality of life for people. There are also difficulties with treatment, because when it comes to abdominal and pelvic pain, several systems or organs could be involved, including the gastrointestinal, urological, or reproductive system.”
In recent years, pain researchers have begun to identify biomarkers of pelvic and abdominal pain, in some cases using them to stop pain before it starts.
“If you think about local anesthesia for surgeries, once the anesthetic is injected, the person doesn't feel anything when they do the incision,” she says. “We would like to do something like that for chronic pain. If, for example, we know that neurons become excitable from innocuous stimuli, some small infection or inflammation, and we know that specific molecular targets are responsible for that, what can we do preventatively to block those targets?”
As such studies move toward clinical trials, Malykhina says, AI can play a role by analyzing large data sets for multiple patients at multiple institutions to find the most accurate biomarkers for specific chronic pain conditions.
“Can we find, for example, a specific molecular target for migraine, so we can use it at the onset of this headache to stop the pain? Or is there a specific bladder pain biomarker, so we know it's coming from the bladder and not the GI or reproductive system?” she says. “AI can help with pulling out this information from analyzing multidisciplinary and multi-institutional datasets, then we can go back to the lab with the best potential candidates and focus on testing them.”
Another promising new direction in research for chronic pelvic and abdominal pain is the use of microphysiological systems — 3D models of human cell structures, derived from patient samples. Sometimes known as “organ-on-a-chip,” the structures allow accurate testing of drugs and other treatments in the lab.
“The development of human microphysiological systems is an emerging technology to mimic human physiology at the basic level with the potential to replace in vivo animal studies for evaluating safety and efficacy during the initial stages of drug and therapeutic development,” Malykhina writes in the paper. “While epithelium-derived microphysiological systems are exciting first steps in the development of full-scale 3D organoids of the lower urinary and reproductive tracts, additional advancements to achieve adequate muscle layer presence, vascularization and innervation of the organoid tissue would be necessary to make them suitable for pelvic pain research.”
As the tools and technologies for studying chronic pelvic and abdominal pain continue to develop, Malykhina hopes to see treatment reach the current level of cancer treatment, in which medications are trained on molecules and other targets to deliver therapy to specific sites.
“We are getting very good at treating blood cancers with CAR T and modified immune cells,” she says. “Soon enough, I hope we will be able to do the same for the pain field. The challenge will be, even if we identify certain cells or receptors, to develop those treatments locally to specific sites, so we don’t affect the entire body.”