Robot Can Help Speed Up Clinical Stroke Drug Trials
February 12, 2014

MIT-Developed Robot Could Reduce Cost, Time Of Clinical Trials

redOrbit Staff & Wire Reports - Your Universe Online

A new robot developed by engineers at MIT could drastically reduce the time and cost associated with Phase III trials for stroke-related medications by approximately 70 percent, according to research appearing in a recent edition of the American Heart Association journal Stroke.

“The development of drugs to treat acute stroke or aid in stroke recovery is a multibillion-dollar endeavor that only rarely pays off in the form of government-approved pharmaceuticals,” said Jennifer Chu of the MIT News Office wrote. “Drug companies spend years testing safety and dosage in the clinic, only to find in Phase III clinical efficacy trials that target compounds have little to no benefit. The lengthy process is inefficient, costly, and discouraging.”

However, MIT’s Hermano Igo Krebs and his colleagues have developed a new robot that could help speed up the stroke drug-development process, letting pharmaceutical companies find out earlier in the process if the treatments would actually be effective in stroke patients.

“Most drug studies failed and some companies are getting discouraged,” Krebs, a principal research scientist with the MIT Department of Mechanical Engineering explained. “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.”

Typically, receiving US Food and Drug Administration (FDA) approval for a drug requires a pharmaceutical company to conduct a trial involving 800 patients in a Phase III clinical trial that demonstrates that the drug is safe and effective. That sample size is partially determined by the accuracy of standard outcome measurements, which quantify a patient’s ability to meet specific criteria.

Between finding and enrolling appropriate patients, conducting the necessary tests and analyzing the results, clinical trials typically can take several years to complete. However, Krebs and his fellow researchers found that by using a robot’s measurements to help gauge patient performance, companies might only need to study just 240 patients in order to determine whether or not the drug works, likewise reducing the time and cost required for such trials.

“While pharmaceutical companies would still have to adhere to the FDA’s established guidelines and outcome measurements to receive final drug approval, Krebs says they could use the robot measurements to guide early decisions on whether to further pursue or abandon a certain drug,” Chu explained.

“If, after 240 patients, a drug has no measurable effect, the company can pursue other therapeutic avenues,” she added. “If, however, a drug improves performance in 240 robot-measured patients, the pharmaceutical company can continue investing in the trial with confidence that the drug will ultimately pass muster.”

The robot used for the study, MIT-Manus, was developed by the institute’s Newman Laboratory for Biomechanics and Human Rehabilitation. MIT-Manus has previously been used for physical therapy, as patients play a video game by maneuvering its arm, in this study it served as a tool for evaluating a patient’s improvement over time.

“As a patient moves the robot’s arm, the robot collects motion data, including the patient’s arm speed, movement smoothness, and aim,” Chu said. “For the current study, the researchers collected such data from 208 patients who worked with the robot seven days after suffering a stroke, and continued to do so for three months.”

The study authors also devised an artificial neural network map which related a patient’s motion data to a score which correlated with a standard clinical outcome measurement, and selected a second group of nearly 3,000 stroke patients who went through standard clinical tests and did not utilize the robot in their rehab sessions.

Krebs and his colleagues determined that the effect size, or the difference in patient performance from the start of a trial to its conclusion, was twice the typical rate for those who used MIT-Manus. Furthermore, after determining the optimal sample size for a given technique, they found that the robot scale would only require 240 patients to determine a drug’s effectiveness, leading to the 70 percent reduction in trial time and cost.