Starts:

Monday, September 19th
8:30am-12:00pm EDT

Category:

Hands-On Workshop

Tracks:

Basic Science: Pain Models

Room

803 A

Artificial Intelligence-Based Approaches to Preclinical Pain Assessment

Measurement of pain in non-human species in laboratory, clinical and domesticated environments is limited to surrogate outcome measures due to their inability to communicate, unlike humans. In this context, the interpretation of the pain state is based on the measurement of behavior as indicators of the impact of pain on various dimensions. Behavior of animals is dramatically influenced by the presence of humans, resulting in unpredictable biases during experiments. This fact, coupled with the increasing realization that the evaluation of complex behaviors may be more clinically relevant, has led researchers to explore ‘hands-off’ methodology to measure complex behaviors. The explosive growth and availability of high-quality video and computational technology is facilitating the development of automated or semi-automated methods to capture and analyze complex behaviors as surrogate measures of pain and analgesia. Attendees will meet and interact with experts across a diverse range of non-human species (flies, rodents, large animals) - experts who will explain, discuss and demonstrate the use of video and artificial intelligence (AI) in its application to the measurement of pain. AI-based automated video analysis is becoming increasingly available and utilized, and, as for any methodology, an awareness of its advantages and caveats will be essential for all scientists working with non-human species. The AI-based approaches used will be described and demonstrated in the context of particular species but have very broad potential applications across species and pain models.

Presentations

Time
8:30am EDT12:00pm EDT

Automated Analysis of Homecage Lid Interaction and Hanging Behaviour as a Measure of Pain in Mice

Tracks: Basic Science: Pain Models
Categories: Hands-On Workshop
Presented By: Robert Bonin

Most rodent studies of pain rely on the use of experimenter-evoked measures of pain and assess behavior under ethologically unnatural conditions, which limits the translational potential of preclinical research. We approached this problem by conducting an unbiased, prospective study of behavioral changes in mice within a natural homecage environment using conventional preclinical pain assays. We observed that cage lid hanging, a species-specific elective behavior, was the only homecage behavior reliably impacted by pain assays. Noxious stimuli reduced hanging behavior in an intensity-dependent manner, and the reduction in hanging could be rescued by analgesics. Finally, we developed an automated approach to assess hanging behavior. This demonstration will review the utility and limitations of studying homecage behaviors for the assessment of pain and describe technologies to automate the measurement of cage lid interaction.

8:30am EDT12:00pm EDT
8:30am EDT12:00pm EDT

Automated Facial Image Evaluation

Tracks: Basic Science: Pain Models
Categories: Hands-On Workshop

There will be a demonstration of the grimace scale used in small and large animal species, with a discussion of data collection and scoring. This will build into how the standard, human observer approaches, contrast with evolving automated, machine learning approaches, including a demonstration of automated image scoring.

8:30am EDT12:00pm EDT
8:30am EDT12:00pm EDT
8:30am EDT12:00pm EDT

Large Animal Automated Behavior Scoring using Machine Vision and 3D Cameras

Tracks: Basic Science: Pain Models
Categories: Hands-On Workshop
Presented By: Dr. Rick B. D’Eath

Automated measurement of animal behavior is possible using machine vision systems. We have worked with a small Agri-tech company using 3D cameras on farm to weigh pigs, but also to measure the posture of their tail, and we are working on measuring a wider range of behaviors. We first showed that tail posture in a group became lower response to the onset of a painful vice behavior - tail biting. On commercial farms, low tail posture was affected by tail biting, but also lameness, and aggressive social behaviour, suggesting it could be useful as a wider indicator of animal wellbeing.

Presenters

Dr. Nick Andrews

Director
Salk Institute for Biological Studies

Dr. Guorong Wu

Associate Professor
University of North Carolina, Chapel Hill

Dr. Rick B. D’Eath

Reader in Animal Behaviour & Welfare
Scotland’s Rural College (SRUC)

Dr. Duncan Lascelles

Professor
North Carolina State University, School of Veterinary Medicine

Ms. Liezl Maree

Scientific Programmer
Salk Institute for Biological Studies

Professor Gregory G Neely

Professor
University of Sydney

Dr. David P. Roberson

CEO
Blackbox Bio

Daniel Pang

Associate Professor
University of Calgary

Robert Bonin

Associate Professor
University of Toronto