This New Therapy Can Be Cure of Blindness, Parkinson and Schizophrenia
Optogenetics is the name given to a process that has just been carried out on a blind lady in Texas. She suffers from pigmentosa which is a disease that kills off the retinas light sensitive cells.
Optogenetics is the name given to a process that has just been carried out on a blind lady in Texas. She suffers from pigmentosa which is a disease that kills off the retinas light sensitive cells. If the trials are successful, the light sensing cells will be created again, and sight will be restored.
The ganglion cells in the lady’s eyes will be made light sensitive, and this is as a result of DNA from algae that is light sensitive itself being injected into her eye. There is hope that if this is successful, it could be used to treat Schizophrenia and Parkinson’s.
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The Michael J. Fox Foundation for Parkinson’s Research neuroscientist Todd Sherer finds this fascinating as it is so easy to work on the eye due its accessibility. The eye that had already been treated is going to be monitored for the next year, and there could be another three doses of the therapy given. There will also be checks for side effects.
Perfect vision is not expected, but there should be some vision. The hope is that they will know someone is near them or being able to get across the street. The trial is ongoing, and 14 additional patients involved, and they will not just be people who do not have a lot of vision, but some who are profoundly blind and do not have light sensitivity. Dr. Birch, who carried out the first treatment, tells the future patients they are pioneers and are taking a big step forward but without guarantees.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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