AI Robo-Doctor accelerates eyesight saving technology

A humanoid robot has accelerated sight restoration research by finding the best conditions to grow replacement retinal layers from human stem cells.

The AI ​​system known as Maholo took just 185 days to complete experiments that would have taken humans two and a half years.

In just a quarter of the time, Maholo processed a trial-and-error search of 200 million possible conditions.

The AI ​​known as Maholo processed trial-and-error research made up of 200 million possible conditions to grow replacement retinal layers from human stem cells to restore sight.

The robot was created by a joint research group at the RIKEN Center for Biosystems Dynamic Research (BDR) in Kobe, Japan, to grow functional retinal pigment epithelium (RPE) cells from stem cells.

Degeneration of the RPE, which is a layer of supporting cells below our photoreceptors, is commonly seen in a progressive disease that is the leading cause of blindness in the elderly.

RPE transplants have had some clinical success in the past.

The robot continuously repeated a series of exact movements and was able to evaluate the results in order to formulate the next experiment.

For every 100 stem cells, 50 have become RPE cells. These cells had many biological markers that would make them suitable for transplantation.

Automating life science research experiments that depend on a number of variables helps avoid labor-intensive experiments that take months.

In the case of cell differentiation, the process by which stem cells are created from specific tissues, variables include finding the optimal type, dose, and timing of reagents.

Physical variables such as temperature, pipette force and cell transfer time are extremely important “because minute differences in physical conditions have a significant impact on quality,” said team leader Genki Kanda.

The success of the new system goes beyond the researchers’ findings, as Kanda explained: “We chose to differentiate RPE cells from stem cells as a model, but in principle, the combination of a precision robot with the Optimization algorithms will enable autonomous trial-and-error experiments in many areas of the life sciences.”

Despite this, the study does not aim to replace humans with robots.

Kanda said, “The use of robots and AI to conduct experiments will be of great interest to the public.”

“However, it is a mistake to see them as substitutes.”

“Our vision is for people to do what they are good at, which is to be creative.”

“We can use robots and AI for the trial-and-error parts of experiments that require repeatable precision and are time-consuming, but don’t require thought.”

The study was published on June 28 the scientific journal eLife.

This story was provided to Newsweek by Zenger News.

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