Decoding Parkinson’s Disease with AI and the Cloud

(MENAFN- H+K Strategies) When the British surgeon James Parkinson first described “shaking palsy” in 1817, he did so by looking at the way patients’ bodies moved. Two centuries on, most specialists seeking to diagnose Parkinson’s Disease still do the same. They rely on physical symptoms to tell them what’s happening in people’s brains. In other words, they are operating largely in the dark.

This lack of understanding contributes hugely to the growing health burden of Parkinson’s, with over 10 million people living with the disease and incidence doubling every 25 years, according to the World Health Organization (WHO). However, the immense computational capacity of the cloud and the accelerating capabilities of Machine Learning (ML) and Artificial Intelligence are offering new hope. By transforming our understanding of the brain and how Parkinson’s impacts it, they are able to speed diagnosis, develop new treatments and better empower patients themselves.

Parkinson’s is a progressive disease caused by the loss of dopamine-producing neurons in the brain. This condition worsens over time. Because the brain relies on dopamine for motor control, it leads to physical symptoms like stiffness, decreased arm movement, reduced blinking or facial expressions, and involuntary shaking or tremors when the body is at rest. It can also cause less obvious symptoms such as low blood pressure, cognitive impairment, depression, anxiety, hallucinations, and delusion. Research shows that people with Parkinson’s are more likely to develop some forms of dementia, broadening the impact of the disease further still.

Because researchers don’t know what causes patients’ dopamine-producing neurons to start shutting down, they are unable to treat the root cause. Instead, most treatments have focused on replacing the lost dopamine. This can temporarily restore motor function, but can’t prevent the progression of the disease. It also makes misdiagnosis a serious issue, as treatments that boost dopamine and help with Parkinson’s symptoms can worsen those of similar neurological conditions like dementia or essential tremor.

Finding a genuine cure for Parkinson’s involves collecting and analyzing a vast amount of different types of data and using a much deeper and more granular understanding of the brain to enable new forms of treatment.


The biomarkers that speed diagnosis and signpost future treatments

Last year, the PPMI discovered a biomarker for Parkinson’s that can be detected by analyzing a patient’s spinal fluid. The new test enables doctors to detect abnormal alpha-synuclein proteins, which occur in 93% of people with the disease. They can act as an early, objective diagnostic tool, and may well point the way towards the causes that treatments should be targeting.

Proteins aren’t the only potential biomarker for Parkinson’s being investigated with the help of cloud data analysis and AI. Icometrix is using AI imaging solutions to monitor changes in brain tissue volume and explore how these correlate with the advance of the disease. Rebuilding its Deep Learning (inference) pipeline using AWS infrastructure has enabled Icometrix to drive big improvements in accuracy while reducing computation time.

Creating a cellular map of the brain to identify targets for treatment

Connecting changes in the brain to changes in people’s experience will represent a huge advance in understanding Parkinson’s. However, a vast amount of what takes place within the brain remains invisible – even to MRI scans. Mapping changes in the 200 billion cells the brain contains is one of the objectives of the Brain Knowledge Platform, a major new initiative led by the Allen Institute, which is building the world’s largest open-source database of brain cell data on AWS. Combining high-performance AWS computing services with AI and Machine Learning (ML) services, such as Amazon SageMaker, enables the Brain Knowledge Platform to decode the characteristics of different brain cell types and monitor what happens to them as neurological diseases progress.

“Through the Brain Knowledge Platform we're beginning to aggregate information about the properties of vulnerable cell populations in Alzheimer’s disease – what they look like, how they function, and what the consequence of their loss may be in disease,” explains Ed Lein, Ph.D, Senior Investigator at the Allen Institute for Brain Science. “You can imagine that these cells now become targets for therapies to prevent their degeneration. An increasingly rich understanding of these cells will guide new treatments. This same approach will work for any brain disease.”

Through AWS, the Brain Knowledge Platform will become an open registry of neurological data, available to doctors and researchers worldwide. For example, it could enable physicians to better diagnose diseases like Parkinson’s disease, and open the door to new therapies to prevent changes that lead to the loss of dopamine-producing neurons, tackling the root cause of the disease.

Across the Middle East, governments and technology partners are laying the groundwork for large-scale AI adoption. AWS has launched dedicated cloud regions in the United Arab Emirates and Bahrain, with a third region planned for Saudi Arabia. These regions are designed to support high-volume data processing with low latency and strong data residency controls, making them suitable for fields like medical research and neuroscience where performance and privacy are paramount. By offering scalable compute power locally, these regions reduce the barriers to building AI models that can process patient imaging data, track disease progression, or assist in biomarker discovery.

In parallel with infrastructure, AWS is advancing skills and education to help regional institutions tap into the potential of AI in life sciences. Through initiatives like the Amazon Academy, tens of thousands of students and professionals are being trained in cloud and AI technologies. This talent pipeline is essential for scaling advanced research, whether it involves building algorithms to analyze genomic datasets or creating machine learning models that identify patterns in patient-reported outcomes. These programs are also helping local startups and research centers build custom AI tools that can contribute to regional breakthroughs in complex neurological conditions.
Pushing back the burden of Parkinson’s with AI and the cloud

Rolling back the burden of Parkinson’s, and improving the lives of those living with the condition, involves approaching the challenge from a number of different directions, simultaneously. Greater understanding enables earlier diagnosis and a wider range of treatments that significantly enhance quality of life. Wider awareness sweeps away stigma and grows interest in technologies that can better support patients. Collective action through clinical trials and research projects increases patients’ sense of agency while bringing a cure closer.

In all of these areas, immense progress is being made through the efforts of Parkinson’s patients, their families, caregivers and medical practitioners. Every one of these groups is discovering they can do even more through the cloud and AI.

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