Our aim is to enroll 750 people with ALS in our PMP. Our PMP includes
participants from nearly every US state and over 40 other countries. This pioneering
partnership has resulted in the creation of the largest, patient-linked database
integrating voice recordings, movement data, medical histories, family histories,
genetics, biomarkers, and patient cell biology.
Participants actively provide valuable data every month.
As of July 2019, PMP participants have provided:
- More than 13,500 voice recordings.
- More than 15,000 accelerometer activity data sets.
- More than 10,000 ALSFRS-R scores.
- More than 21,000 survey responses related to drug, supplement use and other health topics.
Once a month, participants are encouraged to record sample phrases to help us
interpret changes in speech. To date, we have collected over 13,500 speech
recordings from people with ALS.
We collaborate with researchers at Google to leverage their expertise in artificial
intelligence to analyze the "big data" collected from our PMP. This research
partnership resulted in the development of an algorithm that accurately generates
the ALSFRS-R speech score by simply analyzing the series of short recordings of a
person's voice. Using this algorithm we have made significant strides towards the
development of unbiased, quantitative and sensitive measures of ALS disease
Wearable technology is hugely popular in personal healthcare. In diseases like ALS,
where a person is robbed of their ability to move, wearable technology could play
a significant role in helping to track disease progression
and ultimately be used
as an unbiased and sensitive measurement tool in ALS clinical trials.
For the first time, thanks to the hundreds of people enrolled in the PMP,
scientists at ALS TDI were able to begin to explore the potential of wearable
technology in ALS. They analyzed data from multi-limb accelerometer readings
collected monthly from hundreds of people with ALS and compared the data to
reported ALSFRS-R scores, the standard outcome measure used in
interventional clinical trials.
While additional validation of the model is needed, initial analysis suggests
that the use of accelerometers in an ALS clinical trials may reduce the
length of a trial and number of participants required by half.
Finding The Best Leads To Treat ALS
We are now at a pivotal point in our PMP.
Our Translational Research Team has
been developing a plan to reprogram human induced pluripotent stem cells, or
iPSCs into ALS-related cells in preparation for cell-based drug screening.
Our next goal is to acquire a compound library to screen in these ALS-related
cells. Compound libraries consist of tens of thousands, to hundreds of
thousands, of small molecules, which we could screen rapidly in these
ALS-related cells. We hope to use the data we gather from these experiments
to identify which molecules have a positive impact in the cells, making them
good starting points. Promising leads will be moved on to the next stage of
drug development, involving more tests in other models of ALS to assess toxicity
and, in turn, efficacy.
Screening thousands of small molecules in cells represents a significant
shift in our scope. It has the potential to identify better quality leads,
earlier on in the process, allowing us to pursue great ideas, faster.
As we continue our working partnership with PMP participants, Google
scientists, and other collaborators, we will continue to report on findings
from analyses of genetics, blood based biomarkers, clinical disease
progression metrics, and cell biology experiments to discover therapeutic
targets and streamline clinical development processes for ALS.