ArticleCPT: pharmacometrics & systems pharmacology2022
Step-by-step comparison of ordinary differential equation and agent-based approaches to pharmacokinetic-pharmacodynamic models.
Article in CPT: pharmacometrics & systems pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- A hybrid PKPD agent-based model of the tumour immune interaction: effects of anti-cancer combination therapy.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- A scoping review of mathematical modeling techniques for gingival keratinization: A framework for periodontal research.Journal of clinical and experimental dentistry · 2025Review
- Temporal dynamics of angiogenesis: the emerging role of mechanoregulated pathways.Biochemical Society transactions · 2025Review
- A Multiple-Model-Informed Drug-Development Approach for Optimal Regimen Selection of an Oncolytic Virus in Combination With Pembrolizumab.CPT: pharmacometrics & systems pharmacology · 2025Article
- Pharmacokinetics, Dose-Proportionality, and Tolerability of Intravenous Tanespimycin (17-AAG) in Single and Multiple Doses in Dogs: A Potential Novel Treatment for Canine Visceral Leishmaniasis.Pharmaceuticals (Basel, Switzerland) · 2024Article
- The relationship between compartment models and their stochastic counterparts: A comparative study with examples of the COVID-19 epidemic modeling.Journal of biomedical research · 2024Article
- In Silico Studies to Support Vaccine Development.Pharmaceutics · 2023Review
- Step-by-step comparison of ordinary differential equation and agent-based approaches to pharmacokinetic-pharmacodynamic models.CPT: pharmacometrics & systems pharmacology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Mathematical models in oncology aid in the design of drugs and understanding of their mechanisms of action by simulation of drug biodistribution, drug effects, and interaction between tumor and healthy cells. The traditional approach in pharmacometrics is to develop and validate ordinary differential equation models to quantify trends at the population level. In this approach, time-course of biological measurements is modeled continuously, assuming a homogenous population. Another approach, agent-based models, focuses on the behavior and fate of biological entities at the individual level, which subsequently could be summarized to reflect the population level. Heterogeneous cell populations and discrete events are simulated, and spatial distribution can be incorporated. In this tutorial, an agent-based model is presented and compared to an ordinary differential equation model for a tumor efficacy model inhibiting the pERK pathway. We highlight strengths, weaknesses, and opportunities of each approach.
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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.