ArticleBulletin of mathematical biology2022
A Quantitative Systems Pharmacology Perspective on the Importance of Parameter Identifiability.
Article in Bulletin of mathematical biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The trial behind it
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Who cites it
26 citing papers in PubMed.
- Gradient-based parameter optimization method to determine membrane ionic current composition in human induced pluripotent stem cell-derived cardiomyocytes.Scientific reports · 2022Trial
- On the structural identifiability of nonlinear models of ligand binding dynamics.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- Clinical trial simulation of antiviral drugs.Journal of virology · 2026Review
- A Nonparametric Approach to Practical Identifiability of Nonlinear Mixed Effects Models.Bulletin of mathematical biology · 2026Article
- A Step-by-Step Workflow for Performing In Silico Clinical Trials With Nonlinear Mixed Effects Models.CPT: pharmacometrics & systems pharmacology · 2025Article
- Reproducing Cardiac Ionic Model Properties Using a Discrete-Time Model.Computing in cardiology · 2025Article
- CardioFit: a WebGL-based tool for fast and efficient parametrization of cardiac action potential models to fit user-provided data.Royal Society open science · 2025Article
- The Evolution of Systems Biology and Systems Medicine: From Mechanistic Models to Uncertainty Quantification.Annual review of biomedical engineering · 2025Review
- The Role of Pharmacometrics in Advancing the Therapies for Autoimmune Diseases.Pharmaceutics · 2024Review
- Real-World Application of a Quantitative Systems Pharmacology (QSP) Model to Predict Potassium Concentrations from Electronic Health Records: A Pilot Case towards Prescribing Monitoring of Spironolactone.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Guidelines for mechanistic modeling and analysis in cardiovascular research.American journal of physiology. Heart and circulatory physiology · 2024Review
- Cell-specific models of hiPSC-CMs developed by the gradient-based parameter optimization method fitting two different action potential waveforms.Scientific reports · 2024Article
- Semi-mechanistic modeling of resistance development to β-lactam and β-lactamase-inhibitor combinations.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Evolving Improved Sampling Protocols for Dose-Response Modelling Using Genetic Algorithms with a Profile-Likelihood Metric.Bulletin of mathematical biology · 2024Article
- Article
- Minimally sufficient experimental design using identifiability analysis.NPJ systems biology and applications · 2024Article
- In Silico Clinical Trials: Is It Possible?Methods in molecular biology (Clifton, N.J.) · 2024Article
- Life scientists improve QSP model quality and impact.Frontiers in pharmacology · 2024Article
- Neural network emulation of the human ventricular cardiomyocyte action potential: a tool for more efficient computation in pharmacological studies.bioRxiv : the preprint server for biology · 2023Article
- Immunogenicity of COVID-19 vaccines and their effect on HIV reservoir in older people with HIV.iScience · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
There is an inherent tension in Quantitative Systems Pharmacology (QSP) between the need to incorporate mathematical descriptions of complex physiology and drug targets with the necessity of developing robust, predictive and well-constrained models. In addition to this, there is no "gold standard" for model development and assessment in QSP. Moreover, there can be confusion over terminology such as model and parameter identifiability; complex and simple models; virtual populations; and other concepts, which leads to potential miscommunication and misapplication of methodologies within modeling communities, both the QSP community and related disciplines. This perspective article highlights the pros and cons of using simple (often identifiable) vs. complex (more physiologically detailed but often non-identifiable) models, as well as aspects of parameter identifiability, sensitivity and inference methodologies for model development and analysis. The paper distills the central themes of the issue of identifiability and optimal model size and discusses open challenges.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.