The Scope for Diagnosis of Rare Diseases Using Technology
Rare diseases are frequently life-threatening, chronic illnesses. A rare disease is a debilitating lifelong disease or disorder with a prevalence of 1 or less per 1000 people, as defined by the World Health Organization. The definition may differ in different countries, based on population, healthcare system, and resources. A disease is considered rare in the European Union if it affects fewer than 1 in 2,000 people (5 in 10,000 people), few than 200,000 people in the U.S. (6.4 in 10,000 people), and in Japan, a disease is considered rare if it affects fewer than 50,000 prevalent cases (0.04 percent) of the population.
Rare diseases create challenges that are fundamentally different from the most prevalent diseases. The small number of patients, the practicalities of reaching globally dispersed patients, the lack of validated biomarkers and surrogate endpoints, and the unavailability of clinical knowledge and expert centers are all hurdles toward treating rare diseases.
The possible measures that could be applied are as follows:
● Creation of classified system that includes globally accepted rare diseases can be of help. It can aid in the generation of epidemiological data that is globally available. This system would provide a starting point for studies in the history and origins of rare diseases. It can help monitor the safety and clinical effectiveness of medicines.
● Prototype studies may serve as a framework for translating rare disease research into novel drug development. Making a disease easier to diagnose at an early stage will allow the creation of early prevention that can have a substantial positive influence on a patient’s life even if there is no underlying treatment.
● Using optimal delivery strategies (such as regulated or site-specific distribution) could improve the pharmacokinetic characteristics of existing orphan medications, resulting in increased efficacy, safety, or patient convenience.
Global Rare Disease Diagnostics Market with Technology
Since the commercialization of technology with whole-genome and exome sequencing, rare disease diagnosis has grown significantly, but it is necessary to measure the growth and explain future patterns. The genomic testing market is expanding, and it’s likely to keep growing at a faster rate. However, there are significant difficulties that, if not solved, could stifle future growth.
The global rare diseases diagnosis is one of the most rapidly growing technologies, and the market is estimated to increase at a CAGR of 8.57 percent over the forecast period of 2020-2030.
Many patients with rare diseases go through lengthy trials and tribulations until their issues are correctly diagnosed. Eventually, it results in a loss of valuable time needed for early therapy to avert progressive damage.
Technologies Used for Diagnosis
The technologies used for diagnosing rare diseases are next-generation sequencing (NGS), whole exome sequencing (WES), whole-genome sequencing (WGS), microarrays, and several other technologies.
Effective therapies are essential to minimize RDs healthcare costs and maximize patient aid, necessitating the research with new methodologies.
Recent improvements in next-generation sequencing (NGS) have already provided a tremendous opportunity; whole exome or whole genome techniques have greatly improved diagnosis and shortened the “diagnostic odyssey”, as well as assisted in molecular disease characterization.
Data from cutting-edge technologies, such as advanced imaging techniques, multi-omics, gait studies, and others (depending on the therapeutic field), are valuable resources.
Exome sequencing is immensely beneficial for rare Mendelian diseases research because it provides an efficient technique to find genetic variants in all of an individual’s genes.
Rare genetic variants that affect a small number of people are the most common cause of many disorders; by contrast, tools like SNP arrays can only detect shared genetic variants that affect numerous people in the population.
AI Platforms that Support Diagnosis
Cognitive Genomics Intelligence from Emedgene
Emedgene, an Israeli firm, has developed a technology that scans DNA data of people with rare diseases. Natural language processing (NLP) evaluates medical material and finds a link between a patient’s disorder and the genetic variants. It helps doctors diagnose them faster.
Face2Gene is a smartphone software that classifies distinct facial traits of people’s images with neurodevelopmental and congenital problems using machine learning algorithms and brain-like neural networks. The patterns in the photographs generate possible diagnoses and a list of options.
Even though Face2Gene does not give a definite diagnosis, doctors utilize it as a resource.
Fabric GEM is a platform that uses advanced artificial intelligence to automate the diagnosis of rare diseases. It looks at sequencing data alongside clinical data and other complicated structural forms for a patient. Fabric GEM reduces the time of genetic diagnosis from days to minutes by empowering healthcare teams to focus on the most probable scenario.
It meets the demand for rapid genomic interpretation results for NICU patients. Furthermore, the technology scales genomic testing for people with rare diseases.
The platform undergoes four phases: phenotyping, genotyping, phenotype refinement, and final evaluation to facilitate rare disease analysis and diagnosis.
Dx29 will recommend additional symptoms for the physician to consider. Finally, the platform will produce a categorized list of possible diseases, each with a specific score.
Medical professionals and patients with rare diseases are entitled to an accurate and quick diagnosis. Accepting artificial intelligence for diagnosing rare diseases could go a long way toward attaining this goal.