Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology

Brief Bioinform. 2024 Mar 27;25(3):bbae131. doi: 10.1093/bib/bbae131.ABSTRACTUnderstanding the intricate interactions of cancer cells with the tumor microenvironment (TME) is a pre-requisite for the optimization of immunotherapy. Mechanistic models such as quantitative systems pharmacology (QSP) provide insights into the TME dynamics and predict the efficacy of immunotherapy in virtual patient populations/digital twins but require vast amounts of multimodal data for parameterization. Large-scale datasets characterizing the TME are available due to recent advances in bioinformatics for multi-omics data. Here, we discuss the perspectives of leveraging omics-derived bioinformatics estimates to inform QSP models and circumvent the challenges of model calibration and validation in immuno-oncology.PMID:38557676 | DOI:10.1093/bib/bbae131
Source: Briefings in Bioinformatics - Category: Bioinformatics Authors: Source Type: research