Home Pharmacology Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery
Pharmacology JoVE (Open Access) Citable · DOI

Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery

DOI: 10.3791/53800-v
What you'll learn
  • Execute four standardized pain assessment modalities: electrical, pressure, cold, and inflammatory stimuli
  • Measure pain detection and tolerance thresholds in human subjects
  • Interpret analgesic efficacy using integrated, multi-modal pain task results
  • Implement proper controls and safety protocols in human pain research
Protocol

Human pain models are valuable tools used to assess the analgesic potential of novel compounds and predict their clinical efficacy, especially when used in an integrated manner. Although implementation of these models is complex, with proper execution, the pain models described in this protocol can provide predictive and reliable results.

Difficulty
advanced
Total time
~2–3 hours per subject (includes baseline acclimation, four pain tasks, and recovery periods)

Steps

1
Administer electrical stimulation pain scoring task

Deliver calibrated electrical pulses to determine pain detection threshold and pain tolerance threshold. Record subjective pain ratings and threshold values.

▶ 00:52
2
Perform pressure stimulation pain assessment

Apply graduated mechanical pressure to identify pressure pain detection and tolerance thresholds. Document threshold pressures in kilopascals or force units.

▶ 02:56
3
Execute cold pressor immersion task

Immerse subject's hand in cold water and measure time to pain detection and time to tolerance limit. Record temperature and immersion duration.

▶ 03:45
4
Induce localized UV inflammation model

Apply controlled UV exposure to forearm skin to create standardized mild inflammation. Assess resulting pain sensitivity and hyperalgesia at specified intervals.

▶ 05:28
5
Analyze analgesic effects on pain tolerance

Compare threshold and tolerance data across treatment conditions (e.g., placebo vs. analgesic). Present results demonstrating drug efficacy predictions.

▶ 07:36
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