Researchers used artificial intelligence (AI) to evaluate stem cell-derived “patches” of retinal pigment epithelium (RPE) tissue for implanting into the eyes of patients with age-related macular degeneration (AMD), a leading cause of blindness.
The proof-of-principle study helps pave the way for AI-based quality control of therapeutic cells and tissues. The method was developed by researchers at the National Eye Institute (NEI) and the National Institute of Standards and Technology (NIST) and is described in a report appearing online today in the Journal of Clinical Investigation. NEI is part of the National Institutes of Health.
“This AI-based method of validating stem cell-derived tissues is a significant improvement over conventional assays, which are low-yield, expensive, and require a trained user,” said Kapil Bharti, Ph.D., a senior investigator in the NEI Ocular and Stem Cell Translational Research Section.
“Our approach will help scale up manufacturing and will speed delivery of tissues to the clinic,” added Bharti, who led the research along with Carl Simon Jr., Ph.D., and Peter Bajcsy, Ph.D., of NIST.
Cells of the RPE nourish the light-sensing photoreceptors in the eye and are among the first to die from geographic atrophy, commonly known as “dry” AMD. Photoreceptors die without the RPE, resulting in vision loss and blindness.
Bharti’s team is working on a technique for making RPE replacement patches from AMD patients’ own cells. Patient blood cells are coaxed in the lab to become induced pluripotent stem cells (IPSCs), which can become any type of cell in the body. The IPS cells are then seeded onto a biodegradable scaffold where they are induced to differentiate into mature RPE. The scaffold-RPE “patch” is implanted in the back of the eye, behind the retina, to rescue photoreceptors and preserve vision.
The patch successfully preserved vision in an animal model, and a clinical trial is planned.