New MIT robot helps with stroke medication trials

A new MIT robot developed by scientist Hermano Igo Krebs is a breakthrough in accelerating stroke medication trials, according to the published article in the journal Stroke.

Krebs and his colleagues invented the robot MIT-Manus at MIT's Newman Laboratory for Biomechanics and Human Rehabilitation as a tool for evaluating patient improvement over time. So far it's used only as a rehabilitation device where patients maneuver the robot's arm with some assistance from the robot if needed.

Krebs' speedy creation is helpful because the process of developing drugs to treat acute stroke or aid in stroke recovery is arduous. And with costs in the billions of dollars, the payoff in pharmaceutical sales is rarely worth the lengthy process. Drug companies spend years testing safety and dosage only to find in Phase III clinical efficacy trials that target compounds have little to no benefit, Krebs explained in a statement.

"Most drug studies failed and some companies are getting discouraged," he said. "Many have recently abandoned the neuro area [because] they have spent so much money on developing drugs that don't work. They end up focusing somewhere else."

With this robot, pharmaceutical companies can now know earlier in the medication clinical process whether a drug will have the desired effect in stroke patients.

The researchers realized that by using a robot's measurements to gauge patient performance, there would be a 70 percent decrease in the time and cost companies waste determining a drug's effectiveness - or the equivalent of testing about 240 patients.

FDA approval is still needed for these drugs, but now, Krebs says, scientists can know earlier if a drug should be pursued or not. If the drug shows measurable effects after 240 robot-measured patients, the pharmaceutical company can confidently continue investing in the trial.

Currently only a few stroke drugs are in late stage development, but Krebs says that once Phase III is reached, the robot can be operated to more effectively determine a drug's impact.