Leveraging high-resolution omics data for predicting responses and adverse events to immune checkpoint inhibitors.

ABSTRACT: A long-standing goal of personalized and precision medicine is to enable accurate prediction of the outcomes of a given treatment regimen for patients harboring a disease. Currently, many clinical trials fail to meet their endpoints due to underlying factors in the patient population that contribute to either poor responses to the drug of interest or to treatment-related adverse events. Identifying these factors beforehand and correcting for them can lead to an increased success of clinical trials. Comprehensive and large-scale data gathering efforts in biomedicine by omics profiling of the healthy and diseased individuals has led to a treasure-trove of host, disease and environmental factors that contribute to the effectiveness of drugs aiming to treat disease. With increasing omics data,

SUBMITTER: Limeta A 

PROVIDER: S-EPMC10432706 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature