Speaker of Workshop 3
Will talk about: What we have learned from the patient’s experience
Jamie Heywood is the co-founder and chairman of PatientsLikeMe. An MIT-trained mechanical engineer, Jamie entered the field of translational medicine when his 29-year-old brother Stephen was diagnosed with motor neuron disease (MND)/amyotrophic lateral sclerosis (ALS). Today, Jamie is the chief scientist and architect for PatientsLikeMe, a patient network that helps improve lives and serves as a real-time research platform to advance medicine. Described by CNNMoney as one of the 15 companies that will change the world, Jamie co-founded PatientsLikeMe to ensure patient outcomes become the primary driver of the medical care and discovery process.
Jamie is also the founder and past CEO of the ALS Therapy Development Institute (ALS TDI), the world’s first nonprofit biotechnology company. During his tenure at ALS TDI, Jamie helped pioneer an open research model and industrialized therapeutic validation process that made ALS TDI the world’s largest and most comprehensive ALS research program. Jamie and his brother were the subject of Pulitzer Prize–winning author Jonathan Weiner’s biography His Brother’s Keeper and the documentary So Much So Fast.
PatientsLikeMe is a patient-powered research network that collects both free-text and computable health data from patients with specific diseases. By connecting with each other to share their experiences, PatientsLikeMe members generate data about the real-world nature of disease, treatments, and medical care. These data include tens of thousands of reports on the Multiple Sclerosis Rating Scale (MSRS), a measure of functional disability progression caused by MS, as well as reports on symptoms such as fatigue and spasticity. As part of Orion Bionetworks, PatientsLikeMe performed an exploratory analysis of these phenotypic MS data.
Because many MS patients use PatientsLikeMe to report data much more frequently than the typical clinical interval of 3-6 months, we were able to explore disease dynamics over a relatively short time period. We found that even at a scale of weeks, the disease is highly variable, with few predictive factors for future MSRS status other than the patient’s current MSRS score.
Because PatientsLikeMe includes a large population of MS patients who have had the disease for varying lengths of time, we were also able to explore longer-term trends, which we will discuss in this workshop. One finding is that during the first 20 years after disease onset, progression along the MSRS seems more tied to the accumulation of disease domains than of increasing severity in already-present domains. This finding may have implications for theories about the underlying biophysical mechanisms of MS.