Chronic pain impacts over 50 million Americans, causing disability and reduced quality of life. While medications provide some relief, they often have concerning side effects and risks. Could new scientific approaches enable better, more personalized pain care? An emerging concept called predictive processing shows excellent promise to transform how we understand and treat pain in the coming years. As chiropractor and pain management expert Dr. Michael Vianin advocates in his book “Dispositionalism in Musculoskeletal Care,” the most effective approach is patient-centered and collaborative. An emerging concept called predictive processing shows excellent promise to transform how we understand and treat pain in the coming years.
What is Predictive Processing, and How Does it Relate to Pain?
Extensive research shows our brains actively utilize past experiences, memories, and contextual clues to generate predictions about expected sensations – this phenomenon is known as predictive processing. Scientists have discovered that variations in how these predictive mechanisms function relate to measurable differences in how people perceive, cope with, and suffer from pain.
Assessing each person’s unique predictive pain processing patterns through brain imaging and computational models could allow more targeted, personalized pain medicine approaches. For example, neuroimaging can identify how someone’s predictive processes actively distort pain perception, like over-amplifying signals from an aching joint or interpreting minor discomfort as severe. Understanding the neural roots of these pain distortions is critical to developing more effective, personalized treatments.
The Future of Personalized Pain Medicine
Emerging research suggests that leveraging information on each individual’s distinctive predictive pain processes could guide tailored interventions aimed at “recalibrating” maladaptive predictive patterns to reduce excessive suffering. Psychological or behavioral therapies may help retrain some patients’ predictive mechanisms. For others, knowing the genetic, molecular, and neurochemical factors underlying predictive processing differences could inform personalized pharmacotherapy or bioelectronic medicine approaches.
Translating Cutting-Edge Science into Improved Patient Care
While predictive processing shows the potential to transform pain care, significantly more research is still needed to validate the real-world clinical effectiveness of personalized pain treatments based on these emerging scientific insights. As neuroscience and computing power continue illuminating the staggering complexity of pain, scientists, doctors, and healthcare innovators must work diligently to translate these discoveries from lab to clinic.
This will require open collaboration between disciplines to fulfill the potential of predictive processing research to help chronic pain patients through interdisciplinary, patient-centered, and demystified care. Scientists studying fundamental mechanisms must interface with medical product developers, forward-thinking clinicians, patient advocates, and regulatory bodies to progress responsibly in this emerging field.
The Bright Future of Pain Medicine
Once the stuff of science fiction, the future looks increasingly bright for dramatically improving the quality of life for those living with chronic and neuropathic pain. Harnessing cutting-edge neuroscience, machine learning, and computing methods may soon enable personalized care based on each individual’s predictive pain processing profile. By profoundly understanding pain’s neural underpinnings in each patient, we can develop better-targeted, more effective integrated treatment regimens. As Dr. Vianin emphasizes, the experts in pain are the patients themselves. By deeply understanding each person’s unique pain experiences, predictors, and responses, we can develop better-targeted, more effective integrated treatment regimens tailored to the individual.
First Actionable Steps to Advance This Promising Field
What initial steps should stakeholders across disciplines take to progress predictive processing research and bring more personalized pain medicine to suffering patients? As outlined in “Dispositionalism in Musculoskeletal Care,” a dispositionalism model incorporating psychological, neurological, and environmental factors is key for patient-centered care. This requires open collaboration between doctors, scientists, patients and policy makers. A few key priorities include longitudinal studies further validating neuroimaging-based assessments of predictive pain processing patterns; basic science on how psychological, behavioral, device-based, and pharmacological interventions may directly target predictive neural mechanisms; controlled trials of such interventions tailored based on predictive biomarkers; dedicated funding to support scientists studying the basic science of pain prediction across levels from molecules to circuits to cognition; and emphasis on genuinely interdisciplinary collaboration between doctors, scientists, patients, and policymakers.
While significant challenges remain, by working together, we can unravel pain’s mysteries, develop life-changing treatments, and offer renewed hope to millions locked in battle with chronic pain. The emergence of predictive processing as a unifying, mechanistic framework for personalized care represents a historic opportunity to transform patient outcomes – but only through open science and collaboration.