Analysis of stochastic fluctuations in responsiveness is a critical step toward personalized anesthesia
- McKinstry-Wu, A.R., Wasilczuk, A.Z., Harrison, B.A., Bedell, V.M., Sridharan, M.J., Breig, J.J., Pack, M., Kelz, M.B., Proekt, A.
- eLIFE 8: (Journal)
- Registered Authors
- Bedell, Victoria, Pack, Michael
- anesthesia, individual differences, mouse, neuroscience, personalized medicine, physics of living systems, state transitions, stochastic fluctuations, zebrafish
- MeSH Terms
- Anesthetics/administration & dosage
- Computer Simulation
- Dose-Response Relationship, Drug*
- Models, Biological
- Precision Medicine/methods*
- Stochastic Processes
- 31793434 Full text @ Elife
McKinstry-Wu, A.R., Wasilczuk, A.Z., Harrison, B.A., Bedell, V.M., Sridharan, M.J., Breig, J.J., Pack, M., Kelz, M.B., Proekt, A. (2019) Analysis of stochastic fluctuations in responsiveness is a critical step toward personalized anesthesia. eLIFE. 8:.
Traditionally, drug dosing is based on a concentration-response relationship estimated in a population. Yet, in specific individuals, decisions based on the population-level effects frequently result in over or under-dosing. Here, we interrogate the relationship between population-based and individual-based responses to anesthetics in mice and zebrafish. The anesthetic state was assessed by quantifying responses to simple stimuli. Individual responses dynamically fluctuated at a fixed drug concentration. These fluctuations exhibited resistance to state transitions. Drug sensitivity varied dramatically across individuals in both species. The amount of noise driving transitions between states, in contrast, was highly conserved in vertebrates separated by 400 million years of evolution. Individual differences in anesthetic sensitivity and stochastic fluctuations in responsiveness complicate the ability to appropriately dose anesthetics to each individual. Identifying the biological substrate of noise, however, may spur novel therapies, assure consistent drug responses, and encourage the shift from population-based to personalized medicine.
Genes / Markers
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Engineered Foreign Genes