Artificial Intelligence (AI) is rapidly reshaping the healthcare landscape, unlocking new possibilities for diagnosis, treatment, and patient care.
In particular, AI is becoming important in the fight against Parkinson’s disease, with cloud computing platforms such as Amazon Web Services (AWS) playing a central role in a new era of research, diagnosis, and treatment.
Historically, Parkinson’s specialists relied heavily on physical observation, but today, data-driven insights are empowering healthcare providers to better understand the disease, identify its causes, and deliver more effective care.
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With over 10 million people currently living with Parkinson’s worldwide, and the incidence expected to double every 25 years, according to the World Health Organisation, the urgency to enhance diagnosis and treatment is growing.
However, the root cause of Parkinson’s remains unknown, and current therapies primarily focus on replacing lost dopamine rather than preventing neuronal degeneration, highlighting the critical importance of early, accurate diagnosis. Misdiagnosis not only delays appropriate treatment but can also worsen symptoms if incorrect medications are administered.
This is where AI and cloud technologies are proving transformative. By processing vast datasets and applying machine learning models at scale, researchers are uncovering insights into the genetic and biological underpinnings of Parkinson’s that were previously out of reach.
A significant breakthrough comes from Ultima Genomics, a California-based company using AWS infrastructure to power its next-generation DNA sequencing platform. By combining custom algorithms with scalable computing power, the company has reduced the cost of sequencing a full human genome from approximately $1,000 to just $100. This innovation could help identify genetic markers linked to Parkinson’s, which are thought to account for up to 15 percent of all cases, enabling earlier diagnosis and potentially paving the way for preventative gene therapies.
Beyond genetics, AI tools hosted on the cloud are also being used to analyse brain biomarkers. Medical imaging company Icometrix has revamped its deep learning pipeline on AWS to track changes in brain tissue volume using advanced MRI scans. These insights are allowing clinicians to monitor disease progression with greater accuracy while reducing both time and cost in the analysis of neurological data.
Another pioneering initiative is the Brain Knowledge Platform, a project led by the Allen Institute and hosted on AWS. This open-source database seeks to map the brain at a cellular level by profiling the properties of over 200 billion cells. By leveraging AI and high-performance computing tools such as Amazon SageMaker, researchers are decoding the characteristics of different cell types and observing how they change in response to neurological diseases like Parkinson’s.
According to Dr Ed Lein, Senior Investigator at the Allen Institute for Brain Science, this platform will enable scientists to identify which cell types are most vulnerable and how they might be targeted to prevent degeneration, potentially leading to entirely new treatment pathways.
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AI is also enhancing patient-specific therapies. Deep Brain Stimulation (DBS), a technique that delivers electrical pulses to targeted areas of the brain, is increasingly supported by AI to tailor treatment to individual neural activity. This improves outcomes, reduces invasiveness, and minimises side effects, making DBS more accessible to a broader range of patients.
AWS believes that truly addressing Parkinson’s requires a multi-faceted approach: early detection, improved diagnostics, deeper biological understanding, and more effective treatment options. AI and cloud technologies are accelerating progress across all these areas, enabling collaborative research, cutting-edge diagnostics, and real-time data analysis on a global scale.
