Pain is a distressing sensation often associated with tissue injury, disease, or external stimuli. In research, pain causes significant distress to animals, compromises their welfare, and works against the accuracy of experimental outcomes, so how a study handles it is part of its animal welfare program. Recognizing and evaluating pain also determines whether a treatment effect can be measured at all. If pain goes undetected, it cannot be treated, which shows up later as questionable conclusions about analgesic efficacy and dosage, and as suboptimal outcomes in preclinical studies.
Since animals, unlike humans, cannot verbalize their discomfort, assessing pain presents real difficulty. Most assessments in Pain Models rely on clinical signs and overall behavior, which, though imperfect, can identify severe pain in many instances. Lameness, or a specific reaction to palpation of a particular body region, points to localized pain. Species-specific pain assessment techniques have improved the accuracy of evaluations, particularly in procedures such as post-surgical pain assessment in dogs and rats.
Challenges in Animal Pain Assessment
Currently, no universally accepted objective standards exist for assessing the degree of pain experienced by animals. Pain responses vary widely across species, and even within the same species, different types of pain can elicit diverse reactions. Behavioral observations, combined with clinical assessments, remain the most reliable tools for gauging animal pain.
Some commonly employed techniques in pain evaluation include:
- Behavioral Monitoring: recording animal behaviors without disturbing them.
- Physical Examination: evaluating reactions to gentle palpation, especially in areas likely associated with pain, such as surgical sites.
- Nutrition and Weight Tracking: monitoring food and water intake, along with weight changes, to detect potential pain or discomfort.
- Analgesic Trials: administering analgesics and re-evaluating the animal 30-60 minutes after treatment to assess drug efficacy.
Innovations in Pain Evaluation: The AI-based NHP Behavior Analysis System
The AI-based NHP Behavior Analysis System uses a markerless design that reduces stress on non-human primates (NHPs). Marker-based systems interfere with natural behavior, because attaching markers to an animal changes how it moves and how it is handled, which in turn can skew research outcomes. Removing the markers lets researchers observe NHP behavior without altering movement, so the recorded behavior stays closer to what the animal would do unobserved.
The system combines multi-view synchronization with deep learning algorithms to improve the accuracy of observations. High-speed cameras capture NHP movements from several angles at once, which is what makes a precise 3D reconstruction of behavior possible. The output is a detailed, objective, non-invasive method for evaluating pain and monitoring disease progression, and it addresses the main limitation of traditional behavior scoring, namely that a human observer assigns the score.
Accurately assessing pain in research animals requires a multidisciplinary approach involving researchers, veterinarians, and animal care personnel. Continuous improvements in pain evaluation techniques, such as AI-driven behavior analysis, are helping to overcome the subjectivity of traditional methods. Further research is still needed to develop reliable and universally applicable tools for pain assessment across different species, and the use of AI in pain evaluation is a promising direction for preclinical work, particularly within NHP Pharmacology. Programs that need the model side rather than the measurement side are covered under NHP Pain Models: Accelerating Analgesic Drug Development At Prisys Biotech.
