Studies Aim to Improve DMD Clinical Trial Outcomes by Better Predicting Changes in Patients
Two new studies help to explain more than half of the variability in disease progression seen in Duchenne muscular dystrophy (DMD) patients, and carry important implications for the design of new and effective clinical trials to test potential DMD drugs.
“Without [the] understanding of the natural clinical progression of the various genetic causes for DMD, it would be extremely difficult to design the clinical trials or choose the appropriate endpoints necessary to develop novel drugs to use for DMD,” Dr. Edward Kaye, president, CEO, and chief medical officer of Sarepta Therapeutics, said in a press release.
Both studies used statistical methods to measure and predict disease progression, and are based on data from more than 1,000 boys with DMD obtained during more than 10,000 clinic visits.
The first study, “Categorizing natural history trajectories of ambulatory function measured by the 6-minute walk distance in patients with Duchenne muscular dystrophy,” was published in the journal Neuromuscular Disorders and identified statistically distinct groups of patients with similar trajectories in the ability to walk over time. Based on its findings, patients can be classified into distinct group when designing clinical trials, which could make the interpretation of trial results much more meaningful.
Following on these results, a team from Belgium and the U.S. developed a model that can predict one-year changes in the walking ability of boys with DMD. The model uses a composite of patient characteristics and functional measures, and can explain more than twice as much variability in walking ability than can measures used to date to determine eligibility for Duchenne trials. The results were published in the study, “Individualized Prediction of Changes in 6-Minute Walk Distance for Patients with Duchenne Muscular Dystrophy,” in the scientific journal PLOS One.
Currently, considerable differences in the rate at which DMD patients lose their ability to walk cloud study outcomes, making it difficult for researchers to interpret how well a therapy works.
Both studies were conducted through The Collaborative Trajectory Analysis Project (cTAP), a partnership between the private and public sectors that uses data science to design better clinical trials, with the goal of bringing effective new therapies to patients sooner.
“cTAP is one of the best examples of international academic collaboration that has advanced the clinical understanding of Duchenne Muscular Dystrophy,” said Kaye.