Category: Parkinson’s

A small, early stage trial (with no control group) at Georgetown has  found that a small dose of the leukemia drug nilotinib (brand name “Tasigna” by Novartis) produced “meaningful clinical improvements” in 10 out of 11 patients.

The potential impact is significant, and the researchers believe that expanded studies will validate the  promising results. During the trial, participant dopamine levels increased so much that they were advised to reduce or stop taking other drugs.

The investigators reported that one participant, who was confined to a wheelchair,  was able to walk again, and three participants who could not speak were able to hold conversations.

The study marks the first time a therapy appears to reverse the “cognitive and motor decline in patients with these neuro-degenerative disorders,” according to Professor Fernando Pagan, who led the study with Charbel Moussa.

There has been some success with stimulation treatments for Parkison’s symptoms, and advances in early diagnosis and monitoring, but there is no known cure for this debilitating disease.  (See ApplySci Parkinson’s coverage, 2013-2015.)

Click to view Georgetown University Medical Center video.

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MIT researchers have developed a digital assessment tool based on the Anoto Live Pen that they believe will improve the accuracy of Alzheimer’s and Parkinson’s Disease diagnosis.  A paper demonstrates a machine learning based predictive model that might detect neurodegenerative diseases earlier than current methods.

According to lead author William Souillard-Mandar,  the technology “allows us to extract thousands of features from the drawing process that give hints about the subject’s cognitive state, and our algorithms help determine which ones can make the most accurate prediction.”

UCSF professor Philip Starr published a paper suggesting that Deep Brain Stimulation works by reducing overly synchronized motor cortex activity. He believes that this explains why surgically implanted electrodes improve movement, tremor, and rigidity in Parkinson’s patients.

Little is known about why and how DBS works.   This has held back efforts to improve the therapy. Customizing the stimulation delivered to maximally reduce symptoms is challenging.  A better understanding of the effect of DBS on brain circuits could make it more effective.

ApplySci hopes that this research will also lead to equally effective, non-invasive, future treatments.

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Madrid-MIT M+Vision Consortium researchers used keystroke patterns to diagnose motor function impairing conditions, such as Parkinson’s disease.  In a Scientific Reports paper, they described their algorithm’s ability to distinguish keystroke patterns of sleep deprived typers, and rested typers.   A study of 24 Parkinson’s patients suggested that the keystroke algorithm can also distinguish people who have the disease from those who don’t.  A larger study of Parkinson’s patients is now being planned.

Keystroke patterns have been used as a biometric signature for security purposes, but this is the first time that diagnostic information has been extracted from typing. The primary feature analyzed was “key hold time” — how long a key is pressed before being released.

According to study lead Luca Giancardo, people are usually diagnosed five to 10 years after the beginning of the disease, after much damage has been done.   He hopes that this research could  lead to earlier Parkinson’s diagnosis and better treatments.  Giancardo believes that keystroke patterns could also be used to screen for other diseases, such as rheumatoid arthritis.

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