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 can 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 delusions. 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.

Decoding genomes at scale, in search of causes

Up to 15% of Parkinson’s cases can currently be linked to deletions or mutations in people’s genes.

The more DNA data that researchers have to work with, the more of these links they may discover, revealing genetic markers that can help warn of susceptibility to the condition. These enable earlier diagnosis and can signpost the way to treatments.

The California-based company Ultima Genomics has developed software, algorithms and trained its AI models on AWS for its next-generation DNA sequencer. This scalable architecture reduces the cost of sequencing an entire human genome from roughly $1,000 to just $100.

This can help broaden genetic understanding of the disease, and enable the development of gene therapy treatments that can edit DNA to prevent it.

Turning patients’ experiences into actionable data

The immense diversity of Parkinson’s symptoms and experiences means that patients themselves have an invaluable role in advancing medical understanding. The Michael J Fox Foundation (MJFF) runs The Parkinson’s Progression Markers Initiative (PPMI), a landmark citizen science study, which uses wearable devices to gather more than 4 million data points from each participant, every day.

PPMI monitors people’s movement, tremors, sleep quality and more, and stores this data securely on AWS. By combining it with patient brain scans, DNA, bio-samples and clinical assessments, it can use AI to search for patterns and correlations. 

 “We realized there’s an entire untapped pool of people who could do self-reporting of their own data to give us greater insights into the lived experience of disease,” says Deborah W. Brooks, Chief Executive Officer (CEO) and Co-Founder of The Michael J. Fox Foundation for Parkinson’s Research (MJFF). “When we match this phenotypic data with the three terabytes of data in an individual’s genome scan, we’re connecting big data in a way that can speed progress against Parkinson’s.”

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 advancement 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.

AI that works with each patient’s brain through DBS

Precise mapping of a patient’s brain can enable a wider range of treatments, beyond pharmaceutical approaches. Deep Brain Stimulation (DBS) electrically stimulates carefully selected areas of the brain to treat neurological movement disorders.

AI and the cloud can help to make this treatment option accessible to wider numbers of patients, by making treatment more precise and less invasive while reducing side effects.

This includes using AI to adjust stimulation therapy to each patient’s brain activity. 

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 several 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.