In silico trials: Verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products

Viceconti, Marco; Pappalardo, Francesco; Rodriguez, Blanca; Horner, Marc; Bischoff, Jeffrey E.; Tshinanu, Flora Musuamba

doi:10.1016/j.ymeth.2020.01.011

Cited by 206 publications

(129 citation statements)

References 37 publications

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“…Human-based computational approaches have now built momentum beyond academia, reaching clinical, industrial, and regulatory environments. They provide virtual tools, embedding our knowledge on human physiology, to investigate disease, and develop and evaluate therapeutic interventions ( Rodriguez et al., 2016 ; Morrison et al., 2018 ; Viceconti et al., 2020 ). Recent studies have, for example, demonstrated the ability of biophysical human-based modelling and simulation for the assessment of the safety and efficacy of pharmacological therapies ( Sarkar and Sobie, 2011 ; Passini et al., 2017 , 2019 ; Li et al., 2019 ).…”

Section: Introductionmentioning

confidence: 99%

In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment

Margara

Wang

Levrero-Florencio

et al. 2021

Progress in Biophysics and Molecular Biology

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Human-based computational modelling and simulation are powerful tools to accelerate the mechanistic understanding of cardiac patho-physiology, and to develop and evaluate therapeutic interventions. The aim of this study is to calibrate and evaluate human ventricular electro-mechanical models for investigations on the effect of the electro-mechanical coupling and pharmacological action on human ventricular electrophysiology, calcium dynamics, and active contraction. The most recent models of human ventricular electrophysiology, excitation-contraction coupling, and active contraction were integrated, and the coupled models were calibrated using human experimental data. Simulations were then conducted using the coupled models to quantify the effects of electro-mechanical coupling and drug exposure on electrophysiology and force generation in virtual human ventricular cardiomyocytes and tissue. The resulting calibrated human electro-mechanical models yielded active tension, action potential, and calcium transient metrics that are in agreement with experiments for endocardial, epicardial, and mid-myocardial human samples. Simulation results correctly predicted the inotropic response of different multichannel action reference compounds and demonstrated that the electro-mechanical coupling improves the robustness of repolarisation under drug exposure compared to electrophysiology-only models. They also generated additional evidence to explain the partial mismatch between in-silico and in-vitro experiments on drug-induced electrophysiology changes. The human calibrated and evaluated modelling and simulation framework constructed in this study opens new avenues for future investigations into the complex interplay between the electrical and mechanical cardiac substrates, its modulation by pharmacological action, and its translation to tissue and organ models of cardiac patho-physiology.

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Section: Introductionmentioning

confidence: 99%

In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment

Margara

Wang

Levrero-Florencio

et al. 2021

Progress in Biophysics and Molecular Biology

Self Cite

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“…While model validation is always limited to a given set of inputs and outputs, using models or methodologies outside their validation range is where computational modelling can become useful, providing new information. This should be performed with clear identification of the context of use (Viceconti et al 2020), justifying using appropriate variation in inputs or outputs with respect to the validation study. Systematically providing comprehensive information on model methodologies ("the art of modelling") and on the physical data used in validation studies (input and output data) would provide better confidence in the context of use of "valid" models and increase the possibility to directly compare model methodologies against the same physical data.…”

Section: Discussionmentioning

confidence: 99%

“…Validation of in silico model is the process of making sure that the right equations are solved, and the correct parameters are used for a given scenario. A model is never "valid" for all possible scenarios and applications; a validation process is linked to a specific question of interest (Viceconti et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Biomechanical modelling of the facet joints: a review of methods and validation processes in finite element analysis

Mengoni

2020

Biomech Model Mechanobiol

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There is an increased interest in studying the biomechanics of the facet joints. For in silico studies, it is therefore important to understand the level of reliability of models for outputs of interest related to the facet joints. In this work, a systematic review of finite element models of multi-level spinal section with facet joints output of interest was performed. The review focused on the methodology used to model the facet joints and its associated validation. From the 110 papers analysed, 18 presented some validation of the facet joints outputs. Validation was done by comparing outputs to literature data, either computational or experimental values; with the major drawback that, when comparing to computational values, the baseline data was rarely validated. Analysis of the modelling methodology showed that there seems to be a compromise made between accuracy of the geometry and nonlinearity of the cartilage behaviour in compression. Most models either used a soft contact representation of the cartilage layer at the joint or included a cartilage layer which was linear elastic. Most concerning, soft contact models usually did not contain much information on the pressure-overclosure law. This review shows that to increase the reliability of in silico model of the spine for facet joints outputs, more needs to be done regarding the description of the methods used to model the facet joints, and the validation for specific outputs of interest needs to be more thorough, with recommendation to systematically share input and output data of validation studies.

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“…They will transform the research and medical device industry, reduce the need for in-vivo tests and be a complementary part of the product life cycle. However, computer models need to be verified, validated, and analysed for uncertainties [14]. There are still challenges in computer models such as scaling and merging to describe an entire organism or at least a significant part of it before we can use them to as pre-clinical test tools [15].…”

Section: Opening Statementmentioning

confidence: 99%

Computer simulations can replace in-vivo experiments for implantable medical devices

2021

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In silico trials: Verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products

Cited by 206 publications

References 37 publications

In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment

In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment

Biomechanical modelling of the facet joints: a review of methods and validation processes in finite element analysis

Computer simulations can replace in-vivo experiments for implantable medical devices

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