It’s one of medicine’s tragic paradoxes that, collectively, rare diseases have one of the largest impacts on human health. The World Health Organisation defines conditions affecting fewer than 1 in 2,000 people as ‘rare’, and it is estimated that over 300 million people worldwide currently live with one of the 7,000 conditions classified in this way. That’s six times as many as have been diagnosed with cancer in the last five years.
Adding to the issue, patients diagnosed with rare conditions often find themselves on the wrong side of the cost-benefit analysis that’s applied to funding decisions. Resources tend to flow to research and care for conditions with a larger patient population. Low public awareness and a lack of medical studies exacerbate the challenges through the difficulty of diagnosing conditions, which can lead to sufferers being excluded from care. One of the greatest contributions that the cloud and AI can make to healthcare outcomes involves rebalancing this numbers game. AI is transforming genomics and DNA sequencing, enabling researchers to scale their work globally, share insights through the cloud, and develop innovative approaches for deeper understanding of patients’ experiences.
The inherent challenges of diagnosing and treating rare disease
Some of the better-known examples of rare diseases include Motor Neurone Disease, Cystic Fibrosis, Duchenne Muscular Dystrophy, and Haemophilia. As with many rare diseases, these four conditions have one crucial thing in common. They are diseases of DNA which can express themselves in a wide range of different ways, at different stages. In all, an estimated 80% of rare diseases have a genetic component, and this helps to explain both why they are relatively rare, and why they are often so poorly understood. Because they are functions of how genes express themselves rather than how external pathogens and environmental exposures effect the body, they often fall outside of traditional paths to diagnosis.
Not all rare diseases are inherited, and those resulting from rare bacterial or viral infections, autoimmune responses or sporadic genetic mutation come with similar challenges. Because they affect individuals rather than populations, they are less visible. Because they don’t occur in epidemics or pandemics, they generate much less of a public sense of urgency. Because so many rare diseases affect people in childhood, those suffering cannot easily describe symptoms. This further complicates diagnosis while causing great distress to patients and their networks of support.
Taking a granular view of rare disease through genomics
Greater understanding and ongoing research is helping to illuminate the value of genetic testing in helping to diagnose many rare conditions. Genomics England works with AWS and AWS partner Illumina to embed genomic analysis into the diagnostics journey and transform the speed with which suspected cases of rare conditions may be confirmed. Genomics England’s 100,000 Genomes Project laid the foundations for whole genome sequencing for patients with suspected rare conditions through the NHS Genomic Medicine Service. The NHS GMS, which is supported by Genomics England, has sequenced more than 100,000 genomes and made the NHS the first national health system in the world to offer whole genome sequencing as part of routine care.
The difference that accurate diagnosis can make
For those affected by rare conditions and their families, the impact of ready access to diagnosis through genomics can be profound. For one mother, Mel, the NHS Genomic Medicine Service led to the discovery that two of her children, including one previously diagnosed with autism and dyspraxia, were actually suffering from an ultra-rare neurodegenerative condition, caused by a variant in the DHDDS gene. Although there were only 59 documented cases of this condition worldwide, Mel was able to reach out to specialists working on it for suggestions of specific vitamins that could help with tremor symptoms.
In a feature on the Genomics England website, she explained at the time that “tremors have reduced by 20-30% since they started taking them.” However, she’s also clear that support managing symptoms is just the start. As founder of the charity Cure DHDDS, she is focused on raising funds for research, holding scientific conferences and building an international patients registry. “We juggle so many balls because we need to act quickly,” she says. “The aim is to find a drug that can slow down the disease whilst we wait for tomorrow’s treatments, such ASO or RNA therapies.”
Enabling treatments to target gene expression
Antisense oligonucleotides (ASO) and ribonucleic acids (RNA) are treatments that use specific molecules to regulate disease-causing genes by changing the way the genes are expressed. Cloud computing is lowering barriers to developing these therapies for rare diseases by democratising access to computing power and generative AI capabilities, and providing highly secure, federated data sets to enable development of novel treatments and accelerate drug discovery. These technologies also transform the economics of rare disease therapies, making treatments viable even for conditions affecting smaller populations.
AI and the cloud bring other scaling benefits to initiatives tackling rare diseases, as well. AWS has worked with the National Library of Medicine’s National Centre for Biotechnology Information in the United States, to make the Sequence Read Archive (SRA), one of the world’s largest repositories of genome sequencing data, freely accessible from Amazon S3 via the AWS Open Data Sponsorship Programme (ODP). The SRA includes about 40PB of data that include about 40 million run accessions on AWS ODP. Access through the ODP enables researchers worldwide to locate and retrieve sequencing data from those experiments, enabling smoother global collaboration and producing game-changing insights faster.
Detecting the early signals of rare conditions
One of the greatest challenges involved in diagnosing and treating rare diseases is the difficulty decoding the experiences of the very young children who make up a significant share of sufferers. The Children’s National Hospital in the United States, one of the first recipients of a new $10 million AWS funding programme to support research into pediatric health and rare diseases, has built AI technology that can analyse smartphone camera images to identify subtle changes in newborns’ facial features and detect rare genetic disorders. In many cases, these signals are identified late, when preventive care is less effective. However, when identified early with AI technology, they can save children from years of misdiagnosis and ensure they receive the treatment and support they need from the start.
Rady Children’s Hospital and its Institute for Genomic Medicine is one of the first recipients of the AWS Imagine Grant Children’s Health Innovation Award, which supports organisations accelerating innovation in children’s health through advanced cloud services. The hospital is using LLMs to help further accelerate diagnosis and make genomics testing available to the children that need it as soon as possible.
“Leveraging AI and cloud computing is a critical step as we work towards making genetic testing more equitable, inexpensive and widely available,” said Matthew Bainbridge, Ph.D, Supervising Research Scientist at Rady Genomics, a nonprofit research institute at Rady Children’s Hospital San Diego. “Working with AWS allows us to utilise their expertise in AI and cloud computing to improve the speed and access to pediatric genetic testing, ultimately shortening a child’s diagnostic odyssey.”
Giving rare disease patients the recognition and support they deserve
For millions of people with rare diseases, the experience often feels like an endless journey, causing tremendous distress for them and their loved ones. Until now, healthcare systems have simply lacked the necessary funding, data, and understanding to properly identify these conditions and address them with the urgency their life-changing impact deserves. While this absence of support may feel like indifference to patients, the real obstacle has been technological limitations. By continuing to fill this gap, AI and cloud computing can dramatically transform the experience of living with a rare disease, finally giving these conditions the attention they require.
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