Abstract
Inadequate treatment of acute and chronic pain causes depression, anxiety, sleep disturbances, and increased mortality. Abuse and overdose of opioids and the side effects associated with chronic use of NSAID illustrate the need for development of safer and effective pain medication. Working toward this end, an in silico tool based on an emergent intelligence analytical platform that examines interactions between protein networks was used to identify molecular mechanisms involved in regulating the body's response to painful stimuli and drug treatments. Examining interactions between protein networks associated with the expression of over 20 different pain types suggests that the regulation of autophagy plays a central role in modulation of pain symptoms (see Materials and Methods). Using the topology of this regulatory scheme as an in silico screening tool, we identified that combinations of functions targeted by cannabidiol, myo-inositol, and fish oils with varying ratios of eicosapentaenoic and docosahexaenoic acids are projected to produce superior analgesia. For validating this prediction, we administered combinations of cannabidiol, myo-inositol, and fish oils to rats that received formalin injections in hind paws, prior to substance administration, and showed that analgesic effects produced by these combinations were comparable or superior to known NSAID analgesics, which suggests that these combinations have potential in treatment of pain.