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Deep phenotyping: symptom annotation made simple with SAMS.

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Summary
This summary is machine-generated.

SAMS (Symptom Annotation Made Simple) enhances clinical care by enabling sign-based phenotyping using the Human Phenotype Ontology (HPO) and other systems. This tool facilitates better patient characterization for genetic research and clinical trials.

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Area of Science:

  • Medical Informatics
  • Genetics
  • Clinical Research

Background:

  • Precision medicine requires accurate patient phenotyping, with the Human Phenotype Ontology (HPO) being a standard for genetic disorders.
  • Current HPO application is limited, particularly outside human genetics.
  • There is a need to integrate sign-based phenotyping into routine clinical practice.

Purpose of the Study:

  • To introduce SAMS (Symptom Annotation Made Simple), a web-based application designed to facilitate sign-based phenotyping in routine clinical care.
  • To expand the use of HPO and similar annotation systems beyond human genetics.
  • To empower patients in contributing their phenotypic data.

Main Methods:

  • Developed a web-based application, SAMS, providing access to HPO, OMIM, and Orphanet annotation systems.
  • Enabled data storage within the SAMS database and import/export via GA4GH Phenopackets.
  • Designed for easy integration into existing clinical information systems.

Main Results:

  • SAMS offers a user-friendly interface for accessing and managing phenotypic data.
  • The application supports data sharing among users, including patient-contributed information.
  • Phenotypic data can be exchanged using standardized GA4GH Phenopackets.

Conclusions:

  • SAMS promotes more precise patient characterization, aiding in disease mutation discovery and understanding pathophysiology.
  • The tool can improve patient recruitment for clinical studies and trials.
  • SAMS is freely available and aims to enhance clinical care through accessible phenotyping.