Scientists are coming closer and closer to identifying Parkinson’s disease at its very early stages with new diagnostic tools, like smart pens that use artificial intelligence and analysis of earwax. These technologies still in their infancy could finally open the way to more effective treatments by allowing doctors to recognize the neurodegenerative disorder much earlier than now. Up to 10 million people around the globe might benefit from these advancements.
Parkinson’s disease is a long-term degenerative brain disorder that mainly results in motor symptoms. It occurs because the brain cells that make dopamine are slowly dying, which is why the symptoms of Parkinson’s relate to lack of or low dopamine. The main features include involuntary shaking of parts of the body (tremors) rigidity slowness of movements, impairment of posture and balance, and changes in voice. Currently, drugs mainly focus on alleviating the symptoms, but the disease cannot be stopped or reversed so early diagnosis can mean better disease management.
Until recently, identifying Parkinson’s has been a matter of clinical judgment. This includes a review of patient’s condition, a neurological workup together with looking at physical signs. Yet, the symptoms can be mild at first which complicates diagnosis. Besides, it is well known that the brain damage precedes the onset. So, the researchers have made it their mission to find a dependable, easy-to-perform test which will detect the disease long before the first symptoms.
Among the most exciting developments is a smart pen of sorts. At first glance, the pens look like any other ordinary one; Still, they are actually packed with tiny motion sensors which can pick up very small changes in hand movements as someone writes or draws. Since Parkinson’s symptoms most evidently manifest in changes to fine motor skills, the pen can reveal imperceptible variations in handwriting pressure speed, and movement that even a doctor may not notice.
AI is very instrumental in these gadgets. A sophisticated machine learning algorithm is trained on a database of thousands of movements of people with and without Parkinson’s disease. The potential is there for the AI system, after repeated learning, to detect those movement features that are attributed to the disorder and alert the specialists to prodromal Parkinson’s.
But it does not stop here, scientists have taken a totally different direction of research by studying earwax. Though it may seem weird, different biological elements in earwax have been isolated which may indicate what is happening in the body in total. Preliminary work shows that the Parkinson’s earwax specimens have a pattern of chemicals which could be used as biomarker.
The presence of volatile organic compounds, other molecular components in earwax, by advanced methods of analysis characterize the study of biochemical properties of earwax. The goal is to identify distinctive volatile organic compounds related to Parkinson’s disease and to create a non-invasive easy-to-use test with reliable results for Parkinson’s patients.
New diagnostic methods discussed here are the hallmark of the broader concept of “personalized medicine, ” whereby biological markers are used to diagnose diseases long before symptoms appear. Being diagnosed earlier can cause a shift in patient behavior including, offering them new treatment options, opening the door to clinical trials, and making lifestyle changes that help to maintain their quality of life.
Physicians caution that the new methods still need validation before they can be recommended to replace standard neurological examination techniques. It is more likely that they may turn out to be useful, adjunct screening tools which will help doctors to pick out those who need further scrutiny.
