生物信息学
计算生物学
药物开发
毒理基因组学
药品
体内
表观遗传学
生物标志物
计算模型
药物发现
生物信息学
生物
计算机科学
机器学习
人工智能
药理学
生物技术
基因
基因表达
遗传学
作者
Daniel E. Di Zeo‐Sánchez,Antonio Segovia‐Zafra,Gonzalo Matilla‐Cabello,José M. Pinazo-Bandera,Raúl J. Andrade,M. Isabel Lucena,Marina Villanueva‐Paz
标识
DOI:10.1080/17425255.2022.2122810
摘要
The future strategy for iDILI modeling should be patient-centered. Future animal and cell-based models, with more predictive value, will be easier to design by using a more translational approach based on mechanisms demonstrated in humans. Genetic and epigenetic information gathered from iDILI patients, together with data from in vitro and in vivo studies, could be used to develop sophisticated predictive in silico models to find compounds with iDILI potential. Collecting genetic, metabolic, and biomarker data from patient cohorts might be another option to create a 'fingerprint' characteristic of people at risk, allowing for the development of new, mechanistic strategies to enhance iDILI in vitro evaluation.
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