Using Virtual Patients to Predict Perceptual Outcomes for Optogenetic Sight Recovery Technologies

Area of Science:

• Biomedical Engineering
• Neuroscience
• Ophthalmology

Background:

• Optogenetics is a promising strategy for partial vision restoration in inherited retinal diseases.
• Current clinical trials use light-sensitive proteins (opsins) to restore light responsiveness in retinal cells.
• Predicting patient perceptual outcomes from ex vivo opsin activity remains a challenge.

Purpose of the Study:

• To introduce a computational framework linking opsin properties to predicted patient perceptual outcomes.
• To enable quantitative prediction of temporal contrast sensitivity from microbial opsin photocurrent responses.
• To provide a tool for selecting and optimizing opsins for clinical translation in vision restoration.

Main Methods:

• Development of a 'virtual patient' framework.
• Quantitative linking of opsin sensitivity and kinetics to neural responses.
• Simulation of temporal contrast sensitivity functions from microbial opsin photocurrent data.

Main Results:

• The virtual patient framework successfully predicts temporal contrast sensitivity.
• Opsin sensitivity and kinetics were shown to jointly determine perceptual outcomes.
• Enhanced opsin sensitivity without considering temporal resolution can impair perception of dynamic stimuli.

Conclusions:

• The developed computational platform is a generalizable tool for comparing and selecting opsins for vision restoration.
• This framework guides the design and optimization of next-generation optogenetic sight restoration strategies.
• Accurate prediction of perceptual outcomes is crucial for successful clinical translation of optogenetic therapies.