Closing the therapeutic loop

Campbell, Kenneth S.; Yengo, Christopher M.; Lee, Lik Chuan; Kotter, John; Sorrell, Vincent L.; Guglin, Maya; Wenk, Jonathan F.

doi:10.1016/j.abb.2019.01.006

Cited by 10 publications

(5 citation statements)

References 31 publications

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“…For example, Figure 6 illustrates how sensitivity analysis can be used to identify molecular-level interventions that have a particularly large impact on cardiovascular function. Similar calculations, perhaps based on more sophisticated models, might prove useful for in silico screens designed to identify potential therapeutic targets ( Campbell et al, 2019 ).…”

Section: Discussionmentioning

confidence: 99%

“…Multiscaled computer modeling could accelerate this process. Indeed, a recent paper ( Campbell et al, 2019 ) outlined a potential approach that creates patient-specific computer models that integrate genomic, proteomic, imaging, and functional data and then runs the models forward in time to predict how each patient will respond to possible therapeutic interventions. The authors went on to describe a moonshot goal of running a clinical trial to test whether implementing the model-optimized therapy helps patients more than the current standard of care.…”

Section: Introductionmentioning

confidence: 99%

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Multiscale Modeling of Cardiovascular Function Predicts That the End-Systolic Pressure Volume Relationship Can Be Targeted via Multiple Therapeutic Strategies

2020

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Most patients who develop heart failure are unable to elevate their cardiac output on demand due to impaired contractility and/or reduced ventricular filling. Despite decades of research, few effective therapies for heart failure have been developed. In part, this may reflect the difficulty of predicting how perturbations to molecularlevel mechanisms that are induced by drugs will scale up to modulate system-level properties such as blood pressure. Computer modeling might help with this process and thereby accelerate the development of better therapies for heart failure. This manuscript presents a new multiscale model that uses a single contractile element to drive an idealized ventricle that pumps blood around a closed circulation. The contractile element was formed by linking an existing model of dynamically coupled myofilaments with a well-established model of myocyte electrophysiology. The resulting framework spans from molecular-level events (including opening of ion channels and transitions between different myosin states) to properties such as ejection fraction that can be measured in patients. Initial calculations showed that the model reproduces many aspects of normal cardiovascular physiology including, for example, pressurevolume loops. Subsequent sensitivity tests then quantified how each model parameter influenced a range of system level properties. The first key finding was that the End Systolic Pressure Volume Relationship, a classic index of cardiac contractility, was ∼50% more sensitive to parameter changes than any other system-level property. The second important result was that parameters that primarily affect ventricular filling, such as passive stiffness and Ca 2+ reuptake via sarco/endoplasmic reticulum Ca 2+-ATPase (SERCA), also have a major impact on systolic properties including stroke work, myosin ATPase, and maximum ventricular pressure. These results reinforce the impact of diastolic function on ventricular performance and identify the End Systolic Pressure Volume Relationship as a particularly sensitive system-level property that can be targeted using multiple therapeutic strategies.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiscale Modeling of Cardiovascular Function Predicts That the End-Systolic Pressure Volume Relationship Can Be Targeted via Multiple Therapeutic Strategies

2020

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“…Both sarcomere ( 83 – 85 ) and organ-level ( 85 , 86 ) modeling have rich histories but screening cMyBPC VUS is particularly challenging. In particular, the computer model will need to span from molecular events that occur with timescales of milliseconds to organ-level growth that takes place over weeks and months ( 87 ). Numerous challenges will need to be overcome.…”

Section: Mathematical Modeling and Simulation To Explore Effects Of V...mentioning

confidence: 99%

Basic science methods for the characterization of variants of uncertain significance in hypertrophic cardiomyopathy

Doh,

Kampourakis,

Campbell

et al. 2023

Front. Cardiovasc. Med.

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With the advent of next-generation whole genome sequencing, many variants of uncertain significance (VUS) have been identified in individuals suffering from inheritable hypertrophic cardiomyopathy (HCM). Unfortunately, this classification of a genetic variant results in ambiguity in interpretation, risk stratification, and clinical practice. Here, we aim to review some basic science methods to gain a more accurate characterization of VUS in HCM. Currently, many genomic data-based computational methods have been developed and validated against each other to provide a robust set of resources for researchers. With the continual improvement in computing speed and accuracy, in silico molecular dynamic simulations can also be applied in mutational studies and provide valuable mechanistic insights. In addition, high throughput in vitro screening can provide more biologically meaningful insights into the structural and functional effects of VUS. Lastly, multi-level mathematical modeling can predict how the mutations could cause clinically significant organ-level dysfunction. We discuss emerging technologies that will aid in better VUS characterization and offer a possible basic science workflow for exploring the pathogenicity of VUS in HCM. Although the focus of this mini review was on HCM, these basic science methods can be applied to research in dilated cardiomyopathy (DCM), restrictive cardiomyopathy (RCM), arrhythmogenic cardiomyopathy (ACM), or other genetic cardiomyopathies.

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“…The status and location of individual myosin heads and actin binding sites can also be dynamically tracked to allow the exploration of the biophysical interactions of sarcomere components [ 103 ]. Cell models with resolution at the protein level provide a framework to investigate drug action pathways [ 107 ]. In particular, genetic mutations with a role in cardiomyopathies can serve as therapeutic targets [ 108 ].…”

Section: Active Cell Mechanicsmentioning

confidence: 99%

Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways

Rodero,

Baptiste,

Barrows

et al. 2023

Front. Phys.

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Cardiac mechanics models are developed to represent a high level of detail, including refined anatomies, accurate cell mechanics models, and platforms to link microscale physiology to whole-organ function. However, cardiac biomechanics models still have limited clinical translation. In this review, we provide a picture of cardiac mechanics models, focusing on their clinical translation. We review the main experimental and clinical data used in cardiac models, as well as the steps followed in the literature to generate anatomical meshes ready for simulations. We describe the main models in active and passive mechanics and the different lumped parameter models to represent the circulatory system. Lastly, we provide a summary of the state-of-the-art in terms of ventricular, atrial, and four-chamber cardiac biomechanics models. We discuss the steps that may facilitate clinical translation of the biomechanics models we describe. A well-established software to simulate cardiac biomechanics is lacking, with all available platforms involving different levels of documentation, learning curves, accessibility, and cost. Furthermore, there is no regulatory framework that clearly outlines the verification and validation requirements a model has to satisfy in order to be reliably used in applications. Finally, better integration with increasingly rich clinical and/or experimental datasets as well as machine learning techniques to reduce computational costs might increase model reliability at feasible resources. Cardiac biomechanics models provide excellent opportunities to be integrated into clinical workflows, but more refinement and careful validation against clinical data are needed to improve their credibility. In addition, in each context of use, model complexity must be balanced with the associated high computational cost of running these models.

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Closing the therapeutic loop

Cited by 10 publications

References 31 publications

Multiscale Modeling of Cardiovascular Function Predicts That the End-Systolic Pressure Volume Relationship Can Be Targeted via Multiple Therapeutic Strategies

Multiscale Modeling of Cardiovascular Function Predicts That the End-Systolic Pressure Volume Relationship Can Be Targeted via Multiple Therapeutic Strategies

Basic science methods for the characterization of variants of uncertain significance in hypertrophic cardiomyopathy

Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways

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