System and method for improving clinical decisions by aggregating, validating and analysing genetic and phenotypic data
First Claim
1. A method for predicting a first phenotypic outcome for a first subject, based on a first set of genetic, phenotypic or clinical data from the first subject, and a second set of genetic, phenotypic or clinical data from a group of second subjects for whom the first phenotypic outcomes are known, the method comprising:
- structuring the second set of data from the group of second subjects according to a first set of data classes that have unambiguous definition and encompass all the relevant genetic, phenotypic or clinical data, termed the first set of standardized data classes;
structuring the first set of data from the first subject according to the first set of standardized data classes;
creating a first statistical model for predicting the feature corresponding to the first phenotypic outcome based on the first set of standardized data classes;
training the first statistical model based on the second set of data from the group of second subjects together with their measured first phenotypic outcome;
applying the trained first statistical model to the first set of data to predict the first phenotypic outcome for the first subject.
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Abstract
The information management system disclosed enables caregivers to make better decisions, faster, using aggregated genetic and phenotypic data. The system enables the integration, validation and analysis of genetic, phenotypic and clinical data from multiple subjects who may be at distributed facilities. A standardized data model stores a range of patient data in standardized data classes that encompass patient profile information, patient symptomatic information, patient treatment information, and patient diagnostic information including genetic information. Data from other systems is converted into the format of the standardized data classes using a data parser, or cartridge, specifically tailored to the source system. Relationships exist between standardized data classes that are based on expert rules and statistical models. The relationships are used both to validate new data, and to predict phenotypic outcomes based on available data. The prediction may relate to a clinical outcome in response to a proposed intervention by a caregiver. The statistical models may be inhaled into the system from electronic publications that define statistical models and methods for training those models, according to a standardized template. Methods are described for selecting, creating and training the statistical models to operate on genetic, phenotypic and clinical data, in particular for underdetermined data sets that are typical of genetic information. The disclosure also describes how security of the data is maintained by means of a robust security architecture, and robust user authentication such as biometric authentication, combined with application-level and data-level access privileges.
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Citations
33 Claims
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1. A method for predicting a first phenotypic outcome for a first subject, based on a first set of genetic, phenotypic or clinical data from the first subject, and a second set of genetic, phenotypic or clinical data from a group of second subjects for whom the first phenotypic outcomes are known, the method comprising:
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structuring the second set of data from the group of second subjects according to a first set of data classes that have unambiguous definition and encompass all the relevant genetic, phenotypic or clinical data, termed the first set of standardized data classes;
structuring the first set of data from the first subject according to the first set of standardized data classes;
creating a first statistical model for predicting the feature corresponding to the first phenotypic outcome based on the first set of standardized data classes;
training the first statistical model based on the second set of data from the group of second subjects together with their measured first phenotypic outcome;
applying the trained first statistical model to the first set of data to predict the first phenotypic outcome for the first subject. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. A method for validating a first datum of genetic, phenotypic or clinical information for a first subject, based on a first set of genetic, phenotypic or clinical data from the first subject together with a second set of genetic, phenotypic or clinical data from a group of second subjects for whom the first datum of information is already known, the method comprising:
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structuring the second set of data from the group of second subjects according to a first set of data classes that have unambiguous definition, and encompass the relevant genetic, phenotypic or clinical data, termed the first set of standardized data classes;
creating based on the second set of genetic, phenotypic or clinical data a computer executable first rule that determines the likelihood of the first datum, given the first set of standardized data classes;
structuring the first set of genetic, phenotypic or clinical data from the first individual according to a first set of data standardized data classes;
applying the first rule to estimate the likelihood of the first datum, based on the first set of data;
flagging the first set of data if the rule determines that the data is unlikely. - View Dependent Claims (21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33)
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Specification