scholarly journals A computational pipeline to predict cardiotoxicity: From the atom to the rhythm

2019 ◽  
Author(s):  
Pei-Chi Yang ◽  
Kevin R. DeMarco ◽  
Parya Aghasafari ◽  
Mao-Tsuen Jeng ◽  
Sergei Y. Noskov ◽  
...  
Keyword(s):  
Qt Interval ◽  
Cardiac Rhythm ◽  
Spatial Scales ◽  
Surrogate Marker ◽  
Multiscale Model ◽  
Companion Paper ◽  
Computational Pipeline ◽  
Model Framework ◽  
Drug Induced ◽  
Temporal And Spatial

SUMMARYWe simulate and predict cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm.ABSTRACTDrug-induced proarrhythmia is so tightly associated with prolongation of the QT interval that QT prolongation has become widely accepted as a surrogate marker for arrhythmia. The problem is that QT interval as an arrhythmia indicator is too sensitive and not selective, resulting in many potentially useful drugs eliminated early in the drug discovery process. We first set out to predict the fundamental mode of binding for the proarrhythmic drug dofetilide with the promiscuous cardiac drug target, the hERG potassium channel. In a novel linkage between the atomistic and functional scales, computed binding affinities and rates from atomistic simulation are utilized here to parameterize function scale kinetic models of dofetilide interactions with the hERG channel. The kinetic model components are then integrated into predictive models at the cell and tissue scales to expose fundamental arrhythmia vulnerability mechanisms and complex interactions underlying emergent behaviors. Human clinical data from published studies were used to validate model framework and showed excellent agreement, demonstrating feasibility of the approach. The model predictions show that a clinically relevant dose of dofetilide increased arrhythmia vulnerability in all emergent TRIaD-linked parameters including Triangulation, Reverse use-dependence, beat-to-beat Instability and temporal and spatial action potential duration Dispersion. Application of machine learning demonstrated redundancy in the TRIaD linked parameters and suggested that changes in beat-to-beat instability were highly predictive of arrhythmia vulnerability in this setting. Here, we demonstrate the development and validation of a prototype multiscale model framework to predict electro-toxicity in the heart for the proarrhythmic drug dofetilide from the atom to the rhythm.SIGNIFICANCE STATEMENTCardiotoxicity in the form of deadly abnormal rhythms is one of the most common and dangerous risks for drugs in development and clinical use. There is an urgent need for new approaches to screen and predict the effects of chemically similar drugs on the cardiac rhythm and to move beyond the QT interval as a diagnostic indicator for arrhythmia. To this end, we present a computational pipeline to predict cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm. We utilize predicted quantitative estimates of ion channel-drug interactions from our companion paper to simulate cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm.

scholarly journals A Computational Pipeline to Predict Cardiotoxicity

2020 ◽  
Vol 126 (8) ◽  
pp. 947-964 ◽  
Author(s):  
Pei-Chi Yang ◽  
Kevin R. DeMarco ◽  
Parya Aghasafari ◽  
Mao-Tsuen Jeng ◽  
John R.D. Dawson ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Qt Interval ◽  
Channel Model ◽  
Surrogate Marker ◽  
Drug Effects ◽  
Drug Binding ◽  
Herg Channel ◽  
Model Framework ◽  
Drug Induced ◽  
The Impact

Rationale: Drug-induced proarrhythmia is so tightly associated with prolongation of the QT interval that QT prolongation is an accepted surrogate marker for arrhythmia. But QT interval is too sensitive a marker and not selective, resulting in many useful drugs eliminated in drug discovery. Objective: To predict the impact of a drug from the drug chemistry on the cardiac rhythm. Methods and Results: In a new linkage, we connected atomistic scale information to protein, cell, and tissue scales by predicting drug-binding affinities and rates from simulation of ion channel and drug structure interactions and then used these values to model drug effects on the hERG channel. Model components were integrated into predictive models at the cell and tissue scales to expose fundamental arrhythmia vulnerability mechanisms and complex interactions underlying emergent behaviors. Human clinical data were used for model framework validation and showed excellent agreement, demonstrating feasibility of a new approach for cardiotoxicity prediction. Conclusions: We present a multiscale model framework to predict electrotoxicity in the heart from the atom to the rhythm. Novel mechanistic insights emerged at all scales of the system, from the specific nature of proarrhythmic drug interaction with the hERG channel, to the fundamental cellular and tissue-level arrhythmia mechanisms. Applications of machine learning indicate necessary and sufficient parameters that predict arrhythmia vulnerability. We expect that the model framework may be expanded to make an impact in drug discovery, drug safety screening for a variety of compounds and targets, and in a variety of regulatory processes.

scholarly journals Safety and effectiveness of drug therapy for the acutely agitated patient (Part I)

2013 ◽  
pp. 127-136
Author(s):  
Gianluca Airoldi
Keyword(s):  
Heart Rate ◽  
Qt Interval ◽  
Physical Restraint ◽  
Safety Data ◽  
Surrogate Marker ◽  
Diagnostic Procedures ◽  
Torsades De Pointes ◽  
Long Qt ◽  
Drug Induced ◽  
Qt Interval Prolongation

Acute agitation occurs in a variety of medical and psychiatric conditions, and the management of agitated, abusive, or violent patients is a common problem in the emergency department. Rapid control of potentially dangerous behaviors by physical restraint and pharmacologic tranquillization is crucial to ensure the safety of the patient and health-care personnel and to allow diagnostic procedures and treatment of the underlying condition. The purpose of this article (the first in a 2-part series) is to review the extensive safety data published on the antipsychotic medications currently available for managing situations of this type, including older neuroleptics like haloperidol, chlorpromazine, and pimozide as well as a number of the newer atypical antipsychotics (olanzapine, risperidone, ziprasidone). Particular attention is focused on the ability of these drugs to lengthen the QT interval in surface electrocardiograms. This adverse effect is of major concern, especially in light of the reported relation between QT interval and the risk of sudden death. In patients with the congenital long-QT syndrome, a long QT interval is associated with a fatal paroxysmal ventricular arrhythmia knownas torsades de pointes. Therefore, careful evaluation of the QT-prolonging properties and arrhythmogenic potential of antipsychotic drugs is urgently needed. Clinical assessment of drug-induced QT-interval prolongation is strictly dependent on the quality of electrocardiographic data and the appropriateness of electrocardiographic analyses. Unfortunately, measurement imprecision and natural variability preclude a simple use of the actually measured QT interval as a surrogate marker of drug-induced proarrhythmia. Because the QT interval changes with heart rate, a rate-corrected QT interval (QTc) is commonly used when evaluating a drug’s effect. In clinical settings, themost widely used formulas for rate-correction are those of Bazett (QTc=QT/RR^0.5) and Fridericia (QTc=QT/RR^0.33), both of which standardize themeasuredQTinterval to an RRinterval of 1 s (heart rate of 60 bpm).However, QT variability can also be influenced by other factors that are more difficult to measure, including body fat, meals, psycho-physical distress, and circadian and seasonal fluctuations.

scholarly journals Towards a better understanding of QT interval variability

2011 ◽  
Vol 2 (6) ◽  
pp. 245-251 ◽  
Author(s):  
Larisa G. Tereshchenko ◽  
Ronald D. Berger
Keyword(s):  
Qt Interval ◽  
Surrogate Marker ◽  
Polymorphic Ventricular Tachycardia ◽  
Drug Induced ◽  
Technical Requirements ◽  
Qt Interval Prolongation ◽  
Torsades Des Pointes ◽  
Qt Variability ◽  
Life Threatening ◽  
Qt Interval Variability

The International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) Guideline E14 recommends ‘Thorough QT Study’ as a standard assessment of drug-induced QT interval prolongation. At the same time, the value of drug-induced QTc prolongation as a surrogate marker for risk of life-threatening polymorphic ventricular tachycardia known as torsades des pointes remains controversial. Beat-to-beat variability of QT interval was recently proposed as an alternative metric. The following review addresses mechanisms of beat-to-beat QT variability, methods of QT interval variability measurements, and its prognostic value in clinical studies.

scholarly journals Temporal and spatial scales of lake processes. Part 2: interaction of physical and ecological scales and application of scaling concepts to greek lakes

2013 ◽  
Vol 13 (4) ◽  
pp. 354-368
Keyword(s):  
Spatial Scales ◽  
Flow Regimes ◽  
Companion Paper ◽  
Biological Processes ◽  
Northern Greece ◽  
Spatial Scaling ◽  
Ecological Scales ◽  
External Conditions ◽  
Dimensional Parameters ◽  
Temporal And Spatial

The temporal and spatial scaling concepts related to basic physical and ecological lake processes and the associated non-dimensional parameters that govern the various flow regimes, developed in lakes and reviewed in Part 1 of our companion paper (Papadimitrakis, 2011), are applied to lakes Pamvotis and Vegoritis, two water enclosures located in the Northern Greece having different bathymetry and morphology and forced by dissimilar external conditions. This paper begins with a description of the interaction of physical and biological processes in lakes (the latter being described in Part 1) and proceeds with the application of scaling concepts to the above lakes. From these two applications, several interesting conclusions are drawn by comparing the similarities and differences shown in the variation, with time, of these important scales and non-dimensional parameters and how the latter affect the various lake flow regimes.

Genetic susceptibilities and prediction modeling of carbamazepine and allopurinol-induced severe cutaneous adverse reactions in Vietnamese

2020 ◽  
Author(s):  
Dinh van Nguyen ◽  
Hieu Chi Chu ◽  
Christopher Vidal ◽  
Richard B Fulton ◽  
Nguyet Nhu Nguyen ◽  
...  
Keyword(s):  
Adverse Reactions ◽  
Surrogate Marker ◽  
Hypersensitivity Syndrome ◽  
Stevens Johnson Syndrome ◽  
Strongly Correlated ◽  
Drug Induced ◽  
Johnson Syndrome ◽  
Severe Cutaneous Adverse Reactions ◽  
Systemic Symptoms ◽  
Cutaneous Adverse Reactions

Aims: To determine genetic susceptibility markers for carbamazepine (CBZ) and allopurinol-induced severe cutaneous adverse reactions (SCARs) in Vietnamese. Methods: A case control study was performed involving 122 patients with CBZ or allopurinol induced SCARs and 120 drug tolerant controls. Results: HLA-B*58:01 was strongly associated with allopurinol-induced SCARs and strongly correlated with SNP rs9263726. HLA-B*15:02 was associated with CBZ-induced Stevens–Johnson syndrome/toxic epidermal necrolysis but not with drug-induced hypersensitivity syndrome/drug rash with eosinophilia and systemic symptoms. No association was found between HLA-A*31:01 and CBZ-induced SCARs. HLA-B*58:01 and rs3909184 allele A with renal insufficiency were shown to increase the risk of allopurinol-induced SCARs. Conclusion: HLA-B*58:01 and HLA-B*15:02 confer susceptibility to allopurinol-induced SCARs and CBZ-induced SJS/TEN in Vietnamese. Single nucleotide polymorphism rs9263726 can be used as a surrogate marker in identifying HLA-B*58:01.

Larval Feeding: Mechanisms, Rates, and Performance in Nature

2018 ◽  
Keyword(s):  
Marine Invertebrates ◽  
Spatial Scales ◽  
Size Spectrum ◽  
Larval Feeding ◽  
Natural Habitats ◽  
Feeding Mechanism ◽  
Temporal And Spatial ◽  
And Performance ◽  
Bioenergetics Models ◽  
Many Particles

Larvae of many marine invertebrates must capture and ingest particulate food in order to develop to metamorphosis. These larvae use only a few physical processes to capture particles, but implement these processes using diverse morphologies and behaviors. Detailed understanding of larval feeding mechanism permits investigators to make predictions about feeding performance, including the size spectrum of particles larvae can capture and the rates at which they can capture them. In nature, larvae are immersed in complex mixtures of edible particles of varying size, density, flavor, and nutritional quality, as well as many particles that are too large to ingest. Concentrations of all of these components vary on fine temporal and spatial scales. Mechanistic models linking larval feeding mechanism to performance can be combined with data on food availability in nature and integrated into broader bioenergetics models to yield increased understanding of the biology of larvae in complex natural habitats.

Humans and the Environment

2013 ◽  
Keyword(s):  
Spatial Scales ◽  
Empirical Studies ◽  
Human Action ◽  
Cultural Practice ◽  
Environmental Archaeology ◽  
Archaeological Data ◽  
Temporal And Spatial ◽  
Global And Local ◽  
The Relationship ◽  
The Way

The environment has always been a central concept for archaeologists and, although it has been conceived in many ways, its role in archaeological explanation has fluctuated from a mere backdrop to human action, to a primary factor in the understanding of society and social change. Archaeology also has a unique position as its base of interest places it temporally between geological and ethnographic timescales, spatially between global and local dimensions, and epistemologically between empirical studies of environmental change and more heuristic studies of cultural practice. Drawing on data from across the globe at a variety of temporal and spatial scales, this volume resituates the way in which archaeologists use and apply the concept of the environment. Each chapter critically explores the potential for archaeological data and practice to contribute to modern environmental issues, including problems of climate change and environmental degradation. Overall the volume covers four basic themes: archaeological approaches to the way in which both scientists and locals conceive of the relationship between humans and their environment, applied environmental archaeology, the archaeology of disaster, and new interdisciplinary directions.The volume will be of interest to students and established archaeologists, as well as practitioners from a range of applied disciplines.

scholarly journals 8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale

2021 ◽  
Vol 13 (12) ◽  
pp. 2355
Author(s):  
Linglin Zeng ◽  
Yuchao Hu ◽  
Rui Wang ◽  
Xiang Zhang ◽  
Guozhang Peng ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Air Temperature ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Scale Model ◽  
Validation Dataset ◽  
Daily Maximum ◽  
Climate Zone ◽  
Temporal And Spatial

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.

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