Encrypted Genome Database for Genetic Disease Diagnosis
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Solution Overview
Problem
Current methods for diagnosing genetic diseases are inefficient due to reliance on phenotype-first approaches, high costs of sequential genetic testing, and the challenge of interpreting large amounts of genomic data, which often results in false positives and negatives, and raises concerns about patient autonomy and incidental findings.
Innovation Solution
A computer-implemented diagnostic method and system that analyzes a patient's genome by comparing it to a reference genome, assigning weight scores based on predetermined criteria, and ranking possible genetic diseases using a database of phenotypic and genomic information from other subjects, while keeping patient data encrypted to protect privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If phenotype-first approach with sequential genetic testing is used, then diagnostic accuracy is improved, but diagnostic time and cost increase
Solution Approach 1:
The system performs preliminary genome sequencing and stores it in an encrypted state before clinical diagnosis. This allows the genomic data to be ready and available for immediate analysis when phenotypic symptoms present, eliminating the need for sequential testing and enabling rapid prioritization of genetic diseases based on pre-existing genomic information.
Solution Approach 2:
The patent introduces a database system as an intermediary between phenotypic observation and genetic testing. The database stores encrypted genomes and links them to phenotypic data, allowing automated searching and ranking of genetic diseases without requiring manual sequential testing. This intermediary system bridges the gap between phenotype and genotype efficiently.
2Loss of information
If entire exome/genome sequencing is performed, then comprehensive genetic information is obtained, but cost and data interpretation complexity increase
Solution Approach 1:
The system extracts and stores only the essential genomic information in an encrypted format in a database, rather than requiring full interpretation of entire exome/genome data at the time of diagnosis. This extraction of key genetic data allows comprehensive information to be available while simplifying the interpretation process through automated searching and ranking algorithms.
Solution Approach 2:
The patent creates encrypted copies of genomic data that can be stored and searched without requiring decryption or interpretation of the actual genetic sequences. This copying approach allows comprehensive genetic information to be preserved and queried while maintaining simplicity in the diagnostic process, as the encrypted copies can be searched using phenotypic keywords without complex interpretation.
3Measurement precision
If comprehensive genomic analysis is performed, then diagnostic coverage is improved, but patient privacy exposure increases
Solution Approach 1:
The system applies preliminary encryption to genomic data before storage in the database. This preliminary protective action ensures that patient privacy is protected from the moment genomic data is stored, allowing comprehensive genomic analysis to be performed on encrypted copies without exposing actual patient genetic information. The encryption serves as a preemptive measure against privacy violations.
4Quantity of substance
If sequential genetic testing is performed, then cost is reduced for each individual test, but total diagnostic cost increases
Solution Approach 1:
The patent merges multiple individual genetic testing steps into a single comprehensive approach. By storing encrypted genomes in a database and using automated searching with phenotypic keywords, the system combines what would otherwise be multiple sequential tests into one efficient diagnostic process. This merging eliminates redundant testing and reduces total diagnostic costs while maintaining individual test affordability.
Data Source
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AI summary
Methods and systems of ranking a plurality of possible genetic conditions of a target subject related to assessed phenotypes of this subject comprise respective databases and search steps to provide the ranking. The genome of the target subject is analyzed, encrypted and changes are identified without providing user access to the changes. A database comprising genetic conditions linked at least in part to at least one relevant region in the genome of the subject and at least in part to at least one phenotypic characteristic. This database is searched based on the assessed phenotypes thereby providing a first ranking of possible genetic conditions, each genetic condition being related to at least one genetic change indicative of that condition. Weight scores are assigned to each of the identified changes based on predetermined criteria in order to adjust the first ranking and provide a second ranking of possible genetic conditions. A subjects database of other subjects comprises for each other subject, one or more phenotypic characteristics and the encrypted genome, wherein genetic changes in at least one relevant region in the encrypted genome are indicative of a possible genetic condition or conditions. The subjects database is searched for both phenotypic similarity and similarity of the genetic changes by respectively comparing the assessed phenotypes and the changes in the encrypted genome against the data in the subjects database. The target subject is respectively matched with one or more of the other subjects based on the phenotypic similarity therebetween and on the similarity of the genetic changes therebetween respectively. The matches are respectively ranked based on their respective degree of similarity. Depending on which set of matches was ranked first the other set will adjust the first ranking to provide a second ranking of possible genetic conditions since a given match in the second ranking is indicative of the possibility that the target subject shares the same genetic condition or conditions with the matched other subject.