scholarly journals A mathematical model to identify optimal combinations of drug targets for dupilumab poor responders in atopic dermatitis

Allergy ◽  
2021 ◽  
Author(s):  
Takuya Miyano ◽  
Alan D Irvine ◽  
Reiko J Tanaka
Keyword(s):  
Mathematical Model ◽  
Atopic Dermatitis ◽  
Drug Targets ◽  
Poor Responders

scholarly journals A mathematical model to identify optimal combinations of drug targets for dupilumab poor responders in atopic dermatitis

2021 ◽  
Author(s):  
Takuya Miyano ◽  
Alan D Irvine ◽  
Reiko J Tanaka
Keyword(s):  
Mathematical Model ◽  
Clinical Trials ◽  
Atopic Dermatitis ◽  
Clinical Efficacy ◽  
Drug Targets ◽  
Drug Response ◽  
Predictive Biomarkers ◽  
Poor Responders ◽  
Recombinant Interferon ◽  
Multiple Drugs

AbstractBackgroundSeveral biologic drugs for atopic dermatitis (AD) have demonstrated good efficacy in clinical trials, but with a substantial proportion of patients being identified as poor responders. This study aims to understand the pathophysiological backgrounds of patient variability in drug response, especially for dupilumab, and to identify promising drug targets in dupilumab poor responders.MethodsWe conducted model-based meta-analysis of recent clinical trials of AD biologics and developed a mathematical model that reproduces reported clinical efficacies for nine biological drugs (dupilumab, lebrikizumab, tralokinumab, secukinumab, fezakinumab, nemolizumab, tezepelumab, GBR 830, and recombinant interferon-gamma) by describing systems-level AD pathogenesis. Using this model, we simulated the clinical efficacy of hypothetical therapies on virtual patients.ResultsIL-13 in the skin was affirmed, by the global sensitivity analysis of our model, as a potential predictive biomarker to stratify dupilumab good responders. The model simulation identified simultaneous inhibition of IL-13 and IL-22 as a promising drug target for dupilumab poor responders, whereas inhibition of either IL-13 or IL-22 alone in these non-responders was ineffective.ConclusionWe present a mathematical model of AD pathogenesis developed by integration of clinical efficacy data of multiple drugs. This model will serve as a computational platform for model-informed drug development for precision medicine, as it allows evaluation of the effects of new potential drug targets, including combination therapeutics, at an individual patient level and the mechanisms behind patient variability in drug response. Similar mathematical models can be developed for other diseases and drugs, for patient stratification and identification of predictive biomarkers.

scholarly journals Bifurcation analysis of a mathematical model of atopic dermatitis to determine patient-specific effects of treatments on dynamic phenotypes

2018 ◽  
Vol 448 ◽  
pp. 66-79 ◽  
Author(s):  
Gouhei Tanaka ◽  
Elisa Domínguez-Hüttinger ◽  
Panayiotis Christodoulides ◽  
Kazuyuki Aihara ◽  
Reiko J. Tanaka
Keyword(s):  
Mathematical Model ◽  
Atopic Dermatitis ◽  
Bifurcation Analysis ◽  
Patient Specific ◽  
Specific Effects

scholarly journals Model-based meta-analysis to optimise S. aureus-targeted therapies for atopic dermatitis

2021 ◽  
Author(s):  
Takuya Miyano ◽  
Alan D Irvine ◽  
Reiko J Tanaka
Keyword(s):  
Clinical Trials ◽  
Atopic Dermatitis ◽  
Targeted Therapies ◽  
Time Course ◽  
Model Simulation ◽  
Meta Analysis ◽  
Poor Responders ◽  
Coagulase Negative Staphylococcus ◽  
Model Based ◽  
Severity Scores

Background: Several clinical trials of Staphylococcus aureus (S. aureus)-targeted therapies for atopic dermatitis (AD) have demonstrated conflicting results regarding whether they improve AD severity scores. This study performs a model-based meta-analysis to investigate possible causes of these conflicting results and suggests how to improve the efficacies of S. aureus-targeted therapies. Methods: We developed a mathematical model that describes systems-level AD pathogenesis involving interactions between S. aureus and Coagulase Negative Staphylococcus (CoNS). The model was calibrated to reproduce time course data of S. aureus levels, EASI scores, and EASI-75 in response to dupilumab, S. hominis A9 (ShA9) and flucloxacillin from published clinical trials. We simulated efficacies of hypothetical S. aureus-targeted therapies on virtual patients using the model. Results: Our model simulation reproduced the clinically observed detrimental effects that application of ShA9 and flucloxacillin had on AD severity and showed that these effects disappeared if the bactericidal activity against CoNS was removed. A hypothetical (modelled) eradication of S. aureus by 3.0 log10 CFU/cm2, without killing CoNS, achieved comparable EASI-75 to dupilumab. This efficacy was potentiated if dupilumab was administered in conjunction with S. aureus eradication (EASI-75 at week 16; S. aureus eradication: 66.7%, dupilumab 61.6% and combination: 87.8%). The improved efficacy was also seen for virtual dupilumab poor responders. Conclusion: Our model simulation suggests that killing CoNS worsens AD severity and that S. aureus-specific eradication without killing CoNS could be effective for AD patients, including dupilumab poor responders. This study will contribute to design promising S. aureus-targeted therapy.

scholarly journals Genetics of Atopic Dermatitis: From DNA Sequence to Clinical Relevance

Dermatology ◽  
2019 ◽  
Vol 235 (5) ◽  
pp. 355-364 ◽  
Author(s):  
Mari Løset ◽  
Sara J. Brown ◽  
Marit Saunes ◽  
Kristian Hveem
Keyword(s):  
Atopic Dermatitis ◽  
Genetic Risk ◽  
Drug Targets ◽  
Large Scale ◽  
Complex Disease ◽  
Association Studies ◽  
Skin Barrier Function ◽  
Genome Wide Association Studies ◽  
Loss Of Function ◽  
Genetic Sequencing

Atopic dermatitis (AD) is a complex disease that is thought to be triggered by environmental factors in genetically susceptible individuals. Twin studies have estimated the heritability of AD to be approximately 75%, with the null (loss-of-function) mutations of the gene encoding filaggrin (FLG) (chromosome 1q21.3) as the strongest known genetic risk factor. The discovery of the filaggrin gene was important in the emerging model for AD pathogenesis, combining skin barrier function with adaptive and innate immunity. Assisted by the recent development of large-scale high-throughput genomics, more than 30 genetic loci have been linked to AD across different populations. Identification of these loci, together with functional studies, has already provided new insights into disease biology and identified novel drug targets. Further, these susceptibility loci are laying the groundwork for phenome-wide association studies to test their multiple phenotype relationships and application of Mendelian randomization to investigate causal relationships. Despite many known genes, a majority of the genetic risk for AD is yet unexplored. Therefore, studies investigating refined phenotype groups, low-frequency and rare genetic variation, gene-gene and/or gene-environment interactions, epigenetic mechanisms and data from multi-omics technologies are warranted. In this review, we describe genetic discoveries for AD, including results from candidate gene studies, studies of AD-like genetic diseases, genome-wide association studies and genetic sequencing studies. We explain how some of these genetic discoveries have unraveled new mechanistic insights into the pathogenesis of AD and exemplify how personal genetic data could be used for preventive strategies and a tailored treatment regimen (i.e., precision medicine).

scholarly journals Burden of Atopic Dermatitis in Indonesia, Malaysia, and Singapore: Estimates from a Mathematical Model

2014 ◽  
Vol 17 (7) ◽  
pp. A778 ◽  
Author(s):  
A. Bhanegaonkar ◽  
E.G. Horodniceanu ◽  
X. Ji ◽  
P. Detzel ◽  
M.F. Botteman
Keyword(s):  
Mathematical Model ◽  
Atopic Dermatitis

scholarly journals A mathematical model of circadian rhythms and dopamine

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Ruby Kim ◽  
Michael C. Reed
Keyword(s):  
Mathematical Model ◽  
Circadian Rhythms ◽  
Circadian Clock ◽  
Drug Targets ◽  
Dopaminergic System ◽  
Experimental Results ◽  
Dopamine Synthesis ◽  
Orphan Nuclear Receptors ◽  
Genetic Perturbations ◽  
The Mathematical Model

Abstract Background The superchiasmatic nucleus (SCN) serves as the primary circadian (24hr) clock in mammals and is known to control important physiological functions such as the sleep-wake cycle, hormonal rhythms, and neurotransmitter regulation. Experimental results suggest that some of these functions reciprocally influence circadian rhythms, creating a highly complex network. Among the clock’s downstream products, orphan nuclear receptors REV-ERB and ROR are particularly interesting because they coordinately modulate the core clock circuitry. Recent experimental evidence shows that REV-ERB and ROR are not only crucial for lipid metabolism but are also involved in dopamine (DA) synthesis and degradation, which could have meaningful clinical implications for conditions such as Parkinson’s disease and mood disorders. Methods We create a mathematical model consisting of differential equations that express how the circadian variables are influenced by light, how REV-ERB and ROR feedback to the clock, and how REV-ERB, ROR, and BMAL1-CLOCK affect the dopaminergic system. The structure of the model is based on the findings of experimentalists. Results We compare our model predictions to experimental data on clock components in different light-dark conditions and in the presence of genetic perturbations. Our model results are consistent with experimental results on REV-ERB and ROR and allow us to predict the circadian variations in tyrosine hydroxylase and monoamine oxidase seen in experiments. By connecting our model to an extant model of dopamine synthesis, release, and reuptake, we are able to predict circadian oscillations in extracellular DA and homovanillic acid that correspond well with experimental observations. Conclusions The predictions of the mathematical model are consistent with a wide variety of experimental observations. Our calculations show that the mechanisms proposed by experimentalists by which REV-ERB, ROR, and BMAL1-CLOCK influence the DA system are sufficient to explain the circadian oscillations observed in dopaminergic variables. Our mathematical model can be used for further investigations of the effects of the mammalian circadian clock on the dopaminergic system. The model can also be used to predict how perturbations in the circadian clock disrupt the dopaminergic system and could potentially be used to find drug targets that ameliorate these disruptions.

scholarly journals ВАРТІСТЬ МЕДИЧНОЇ ДОПОМОГИ ДІТЯМ З ХРОНІЧНИМИ ДЕРМАТОЗАМИ

2015 ◽  
Author(s):  
H. B. Holyachenko
Keyword(s):  
Mathematical Model ◽  
Atopic Dermatitis ◽  
Cost Of Treatment ◽  
The Cost

According to the developed mathematical model the cost of treatment of psoriasis and atopic dermatitis in children was determined. The incidence of this disease and cost of treating are increasing, which makes the urgency of the problem.

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