Research Update
July 2, 2019
Improving rare disease diagnosis and treatment
Award-winning project by the New York Academy of Sciences aims to diagnose rare diseases even before the onset of symptoms.
Project Dates: December 2018 - July 2019
Innovation in genomics, proteomics, and personalized medicine is revolutionizing the healthcare field. While rare disease research has come a long way in the past eight years, there are still significant challenges to rare disease prevention, discovery, and treatment. There are more than 7,000 known rare diseases to date, affecting 350 million people worldwide. Yet, as implied by their name, availability of rare diseases’ data is limited, and there is a need for further advancement. Moreover, datasets currently available lack the diversity that would enable researchers to conduct broader and more elaborate research.
Defining the problem
Rare diseases impact about 350 million globally and tend to affect children in particular, with about 80% of them being genetically based. As IL Ross of the Department of Medicine at the University of Cape Town notes in his article Exploring Rare Diseases in South Africa, “the prevalence of Addison's disease in Western Europe is estimated to vary from 39 to 117 per million, but it has been recorded as high as 144 per million. Even using conservative estimates, this is considerably higher than the 3 per million found in our study [in South Africa].”
What that means is that communities where people do not have access to contemporary information about rare diseases, the diagnosis rate is significantly lower, thus depriving many patients of the suitable treatment. What is more, a movement of distrust against medicine has received a recent popularity boost, as depicted by the anti-vaccine movement. The suspicion about DNA sequencing is much more substantial, with patients citing personal data security risks.
Our four-part solution
Our team developed a solution bringing together best practices, innovations and technologies from the medical, telecommunications and social sciences worlds to address this problem:
iDNA Protocol: iDNA (identifier DNA) is an international barrier-free way to uniquely categorize DNA sequences. The program aims to ensure the security of patients’ data during the consultation process while also providing a concrete way to catalog DNA sequences. The protocol involves the following procedure: Collecting DNA samples > Storing patient’s data > Attribution of iDNA > Sequencing DNA samples > Sending to institutions > Analysis of DNA sequence > Gathering all consultations > Matching iDNA with patient > Delivery of final results. In our solution, blockchain technology is utilized to ensure that the DNA sequence, along with its iDNA code are securely transferred.
PrPSc Antibody Testing Kit (PrAT Kit): We propose an alternative method of detecting rare diseases caused by prions through use of an antibody stick that will allow for the detection of PrPSc oligomers for the diagnosis of prion diseases in blood and other body fluids. This antibody stick is similar to a pregnancy test strip. A blood sample is first collected from the patient and applied to the bottom of the stick. When immobilized anti-PrPSc antibodies bind to alternative sites on PrPSc in the test region, the antibody-complex forms a sandwich with the immobilized capture antibody. This results in formation of a visible line on the strip indicating that the PrPSc protein is present in the sample, pointing to the likelihood that the patient has a prion disease.
Graphical overview of the PrPSc Antibody Testing Kit.
GenePack: GenePack builds on existing testing methods, including blood spots, but provides novel methods of affordable and accurate diagnosis for a number of rare diseases. Our proposed package would be offered for free or at an affordable price to all newborns in low-income areas and will be specific to detecting a number of the gravest rare genetic diseases affecting a certain geographical area. Additionally, in order to encourage people to seek treatment and increase the availability of data, parents whose children test positive in genetic screening using the GenePack will have the option to have their child enrolled in research programs and will receive financial support to pay for treatments in exchange for informed consent to usage of genetic data and for their participation in treatment trials.
Doc2Doc Platform: Doc2Doc is a platform that connects patients, doctors, hospitals and treatment centers around the world so that not only do people get to know about their condition but there is an actual valuable interaction between the 4 elements. To target professionals in remote locations, we based our idea to provide access upon preexisting satellite kits. The kits consist of 3 components: a traditional VSAT (very small aperture terminal) with an antenna, modem with a transceiver, and a device to access the internet. To suit the needs of our targeted audience we propose an origami-based portable VSAT prototype. We also suggest using mesh topology, in which one terminal transmits data to another terminal using a satellite as a hub, to reduce the need of establishing an uplink.
Social impact
We believe that our solution can be implemented effectively in various existing communities globally in a cost-effective manner, as it involves changes in the rare disease diagnosis and treatment process alongside incentives for health insurance companies and research institutions. We recognize that many communities are in desperate need of assistance, and this is a major factor as to why we employed our knowledge, resources and understanding of various global perspectives in creating a solution that is viable for existing areas.
As Ming Li, surgical resident at Tong Ren Wuhan City Hospital No. 3 in China, states, “this solution has great potential to improve the future of rare disease research and healthcare, especially in areas that need it the most.”
Notes
This project was the winner of the Genomics Challenge, organized by the New York Academy of Sciences.
This work was co-developed with the help of my teammates Ana Bonavides-Aguilar, Athena Yao, Monish Singhal, Aditi Gupta, and Ana Stratan.
