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Relationships Between Pharmacovigilance, Molecular, Structural, and Pathway Data: Revealing Mechanisms for Immune-Mediated Drug-Induced Liver Injury.


ABSTRACT: Immune-mediated drug-induced liver injury (IMDILI) can be devastating, irreversible, and fatal in the absence of successful transplantation surgery. We present a novel approach that combines the methods of pharmacoepidemiology with in silico molecular modeling to identify specific features in toxic ligands that are associated with clinical features of IMDILI. Specifically, from pharmacovigilance data multivariate logistic regression identified 18 drugs associated with IMDILI (P < 0.00015). Eleven of these drugs, along with their known and proposed metabolites, constituted a training set used to develop a four-point pharmacophore model (sensitivity 75%; specificity 85%). Subsequently, this information was combined with information from immune-pathway reviews and genetic-association studies and complemented with ligand-protein docking simulations to support a hypothesis implicating two putative targets within separate, possibly interacting, immune-system pathways: the major histocompatibility complex within the adaptive immune system and Toll-like receptors (TLRs), in particular TLR-7, which represent pattern recognition receptors of the innate immune system.

SUBMITTER: Ho SS 

PROVIDER: S-EPMC4544056 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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Relationships Between Pharmacovigilance, Molecular, Structural, and Pathway Data: Revealing Mechanisms for Immune-Mediated Drug-Induced Liver Injury.

Ho S S SS   McLachlan A J AJ   Chen T F TF   Hibbs D E DE   Fois R A RA  

CPT: pharmacometrics & systems pharmacology 20150618 7


Immune-mediated drug-induced liver injury (IMDILI) can be devastating, irreversible, and fatal in the absence of successful transplantation surgery. We present a novel approach that combines the methods of pharmacoepidemiology with in silico molecular modeling to identify specific features in toxic ligands that are associated with clinical features of IMDILI. Specifically, from pharmacovigilance data multivariate logistic regression identified 18 drugs associated with IMDILI (P < 0.00015). Eleve  ...[more]

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