In Silico Approaches to Study Drug-induced Renal Toxicity

Kidney ◽  
2013 ◽  
pp. 103-120
Author(s):  
Rajiv Govindaraj ◽  
Prasannavenkatesh Durai ◽  
Sangdun Choi
Keyword(s):  
In Silico ◽  
Renal Toxicity ◽  
Study Drug ◽  
Drug Induced ◽  
Approaches To Study

scholarly journals What does not kill a tumour may make it stronger:in silicoInsights into Chemotherapeutic Drug Resistance

2017 ◽  
Author(s):  
Sara Hamis ◽  
Perumal Nithiarasu ◽  
Gibin G Powathil
Keyword(s):  
Drug Resistance ◽  
Cancer Cell ◽  
In Silico ◽  
Treatment Strategies ◽  
Study Drug ◽  
Clinical Problem ◽  
Drug Resistant ◽  
Chemotherapeutic Drug ◽  
Chemotherapy Treatment ◽  
Drug Induced

AbstractTumour recurrence post chemotherapy is an established clinical problem and many cancer types are often observed to be increasingly drug resistant subsequent to chemotherapy treatments. Drug resistance in cancer is a multipart phenomenon which can be derived from several origins and in many cases it has been observed that cancer cells have the ability to possess, acquire and communicate drug resistant traits.Here, anin silicoframework is developed in order to study drug resistance and drug response in cancer cell populations exhibiting various drug resistant features. The framework is based on an on-lattice hybrid multiscale mathematical model and is equipped to simulate multiple mechanisms on different scales that contribute towards chemotherapeutic drug resistance in cancer. This study demonstrates how drug resistant tumour features may depend on the interplay amongst intracellular, extracelluar and intercellular factors. On a cellular level, drug resistant cell phenotypes are here derived from inheritance or mutations that are spontaneous, drug-induced or communicated via exosomes. Furthermore intratumoural heterogeneity and spatio-temporal drug dynamics heavily influences drug delivery and the development of drug resistant cancer cell subpopulations. Chemotherapy treatment strategies are here optimised for variousin silicotumour scenarios and treatment objectives. We demonstrate that optimal chemotherapy treatment strategies drastically depend on which drug resistant mechanisms are activated, and that furthermore suboptimal chemotherapy administration may promote drug resistance.

Obstructive Protein Cast Nephropathy in Cynomolgus Monkeys Treated with Small Organic Molecules

2008 ◽  
Vol 45 (6) ◽  
pp. 945-948 ◽  
Author(s):  
R. E. Guzman ◽  
K. Datta ◽  
N. K. Khan
Keyword(s):  
Renal Toxicity ◽  
Obstructive Nephropathy ◽  
Drug Induced ◽  
Cast Material ◽  
Small Organic Molecules ◽  
Cynomolgus Monkeys ◽  
Cast Nephropathy ◽  
Cynomolgus Macaques ◽  
Species Specific ◽  
Tubular Dilatation

We have observed a renal toxicity consistent with an obstructive protein cast nephropathy in cynomolgus macaques but not in other species treated with different therapeutic candidates having a common carboxylic acid moiety, suggesting a species-specific sensitivity. Here, we present renal toxicity findings consistent with a protein cast nephropathy in a 2–week safety study in cynomolgus monkeys. Light microscopic changes consisted of intratubular cast formation, tubular dilatation, interstitial inflammation, and expansion of the medullary interstitium. Tubular cast material was identified as Tamm-Horsfall protein (THP) and, on ultrastructure, crystalloid material was present in vacuoles of tubular epithelium. It is hypothesized that microcrystal formation in the urinary tubular spaces induces aggregation of THP protein and cast formation in monkeys. Drug-induced obstructive nephropathy is not identified as a major problem in humans; thus, the clinical relevance of the above findings in monkeys is not clear.

Estimation of uncertainty in multi-level in silico models predicting biomarkers of drug-induced proarrhythmic risk

2021 ◽  
Vol 350 ◽  
pp. S64-S65
Author(s):  
K. Kopanska ◽  
J.C. Gómez-Tamayo ◽  
J. Llopis-Lorente ◽  
B.A. Trenor-Gomis ◽  
J. Sáiz ◽  
...  
Keyword(s):  
In Silico ◽  
Drug Induced ◽  
Proarrhythmic Risk ◽  
Multi Level ◽  
In Silico Models ◽  
Estimation Of Uncertainty

In silico assessment of drug-induced liver injury in humans

2016 ◽  
Vol 258 ◽  
pp. S118
Author(s):  
C. Yang ◽  
S. Thakkar ◽  
A. Mostrag ◽  
V. Gombar ◽  
B. Bienfait ◽  
...  
Keyword(s):  
Liver Injury ◽  
In Silico ◽  
Drug Induced ◽  
Drug Induced Liver Injury

scholarly journals Modulating the voltage sensor of a cardiac potassium channel shows antiarrhythmic effects

2021 ◽  
Author(s):  
Yangyang Lin ◽  
Sam Z. Grinter ◽  
Zhongju Lu ◽  
Xianjin Xu ◽  
Hong Zhan Wang ◽  
...  
Keyword(s):  
Action Potential ◽  
In Silico ◽  
Therapeutic Efficacy ◽  
Torsade De Pointes ◽  
Computational Prediction ◽  
Chemical Library ◽  
Drug Induced ◽  
Voltage Dependent ◽  
Life Threatening ◽  
Approved Drugs

AbstractCardiac arrhythmias are the most common cause of sudden cardiac death worldwide. Lengthening the ventricular action potential duration (APD) either congenitally or via pathologic or pharmacologic means, predisposes to a life-threatening ventricular arrhythmia, Torsade de Pointes. IKs, a slowly activating K+ current plays a role in action potential repolarization. In this study, we screened a chemical library in silico by docking compounds to the voltage sensing domain (VSD) of the IKs channel. Here we show that C28 specifically shifted IKs VSD activation in ventricle to more negative voltages and reversed drug-induced lengthening of APD. At the same dosage, C28 did not cause significant changes of the normal APD in either ventricle or atrium. This study provides evidence in support of a computational prediction of IKs VSD activation as a potential therapeutic approach for all forms of APD prolongation. This outcome could expand the therapeutic efficacy of a myriad of currently approved drugs that may trigger arrhythmias.Significance statementC28, identified by in silico screening, specifically facilitated voltage dependent activation of a cardiac potassium ion channel, IKs. C28 reversed drug-induced prolongation of action potentials, but minimally affected the normal action potential at the same dosage. This outcome supports a computational prediction of modulating IKs activation as a potential therapy for all forms of action potential prolongation, and could expand therapeutic efficacy of many currently approved drugs that may trigger arrhythmias.

scholarly journals New Frontiers: Approaches to Understand the Mechanistic Basis of Renal Toxicity

2018 ◽  
Vol 46 (8) ◽  
pp. 1002-1005
Author(s):  
Mary B. Nabity ◽  
Joseph W. Polli ◽  
Vishal Vaidya ◽  
Andrzej Krolewski ◽  
Warren E. Glaab
Keyword(s):  
Renal Toxicity ◽  
Kidney Injury ◽  
Scientific Session ◽  
Diabetic Patients ◽  
Drug Induced ◽  
Research Areas ◽  
Novel Biomarkers ◽  
Mechanistic Basis ◽  
New Research

A scientific session entitled “New Frontiers: Approaches to Understand the Mechanistic Basis of Renal Toxicity” focused on novel biomarkers to monitor kidney injury both preclinically and clinically, as well as providing mechanistic insight of the induced injury. Further, the role and impact of kidney membrane transporters in drug-induced kidney toxicity provided additional considerations when understanding kidney injury and the complex role of drug transporters in either sensitivity or resistance to drug-induced injury. The onset of nephropathy in diabetic patients was also presented, focusing on the quest to discover novel biomarkers that would differentiate diabetic populations more susceptible to nephropathy and renal failure. The session highlighted exciting new research areas and novel biomarkers that will enhance our understanding of kidney injury and provide tools for ensuring patient safety clinically.

In silico QT assay for preclinical assessment of drug-induced proarrhythmicity

2018 ◽  
Vol 93 ◽  
pp. 142
Author(s):  
Lucía Romero ◽  
Jordi Cano ◽  
Julio Gomis-Tena ◽  
Beatriz Trenor ◽  
Ferran Sanz ◽  
...  
Keyword(s):  
In Silico ◽  
Drug Induced

scholarly journals Drug-induced diabetes type 2: In silico study involving class B GPCRs

PLoS ONE ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. e0208892 ◽  
Author(s):  
Dorota Latek ◽  
Ewelina Rutkowska ◽  
Szymon Niewieczerzal ◽  
Judyta Cielecka-Piontek
Keyword(s):  
In Silico ◽  
Diabetes Type 2 ◽  
Diabetes Type ◽  
Drug Induced ◽  
In Silico Study ◽  
Class B
Sign in / Sign up

Export Citation Format

Share Document