Unbiased data analytic strategies to improve biomarker discovery in precision medicine.

Unbiased data analytic strategies to improve biomarker discovery in precision medicine. Drug Discov Today. 2019 May 31;: Authors: Khan SR, Manialawy Y, Wheeler MB, Cox BJ Abstract Omics technologies promised improved biomarker discovery for precision medicine. The foremost problem of discovered biomarkers is irreproducibility between patient cohorts. From a data analytics perspective, the main reason for these failures is bias in statistical approaches and overfitting resulting from batch effects and confounding factors. The keys to reproducible biomarker discovery are: proper study design, unbiased data preprocessing and quality control analyses, and a knowledgeable application of statistics and machine learning algorithms. In this review, we discuss study design and analysis considerations and suggest standards from an expert point-of-view to promote unbiased decision-making in biomarker discovery in precision medicine. PMID: 31158511 [PubMed - as supplied by publisher]
Source: Drug Discovery Today - Category: Drugs & Pharmacology Authors: Tags: Drug Discov Today Source Type: research