Metabolomics in Personalized medicine

1. Lack of making different selections before initiating the discovery phase.

2. Robustness of analysis techniques used in clinical trials.

<p style="&quot;box-sizing:" border-box;="" margin:="" 0px="" 10px;="" color:="" rgb(51,="" 51,="" 51);="" font-family:="" "helvetica="" neue",="" helvetica,="" arial,="" sans-serif;="" font-size:="" 14px;="" background-color:="" rgb(255,="" 255,="" 255);"="">Each of these details is rarely documented and can dramatically affect the predictive outcome of biomarker results. However, the selection of useful biomarkers must be carefully assessed and depends on different important parameters, such as on sensitivity (it should correctly identify a high proportion of true positive rate), specificity (it should correctly identify a high proportion of true negative rate), predictive value etc. Unfortunately, biomarkers with ideal specificity and sensitivity are difficult to find. One potential solution is to use the combinatorial power of different biomarkers, each of which alone may not offer satisfaction in specificity or sensitivity.

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