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Precision medicine relies on the use of biological indicators called biomarkers to classify patients by their risk for certain diseases and/or response to treatment and to precisely characterize their genotype, or genetic code, and phenotype, or physical traits.

The emergence of next-generation DNA sequencing technologies has revolutionized the use of human genetics for pharmaceutical R&D by providing the ability to conduct a deeper analysis of genotype in the context of detailed phenotypes. This has generated unprecedented insight into the genetics of human disease and a wealth of novel drug targets and biomarkers.

Phenotyping technologies allow better understanding of human physiology and disease in unprecedented detail, for identifying and validating better biomarkers and response to treatment. These include high throughput omics technologies (e.g., transcriptomics, proteomics, metabolomics), microbiome profiling, flow cytometry, and electronic biomarkers such as actigraphy (i.e., the measurement of patient movement in real time using mobile sensors).

Digital biomarkers are gaining increasing importance as an approach to defining more precise outcome measures and clinical research endpoints. These can include, for example, cognitive tests in the form of games on tablets, mood and disease progression by voice recording, and actigraphy, among other measures.

Health information technology platforms refer to systems that help collect, store, and analyze vast amounts of health data with a particular focus on correlating phenotypic and genotypic information (sometimes referred to as “big data”), which are becoming more readily available to the research community.

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