ReviewJournal of pharmacokinetics and pharmacodynamics2015
Integrated PK-PD and agent-based modeling in oncology.
Review in Journal of pharmacokinetics and pharmacodynamics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
39 citing papers in PubMed.
- Mechanistic model of phase-transitioning therapeutics injected into poroelastic tissue for improved targeting of superficial tumors.Scientific reports · 2026Article
- Deep learning for adaptive chemotherapy: A DDPG-based approach to optimizing tumor-immune dynamics.PloS one · 2026Article
- Virtual Biomarkers and Simplified Metrics in the Modeling of Breast Cancer Neoadjuvant Therapy: A Proof-of-Concept Case Study Based on Diagnostic Imaging.Medical sciences (Basel, Switzerland) · 2025Article
- Vancomycin dosing in neonates: enhancing outcomes using population pharmacokinetics and simulation.Frontiers in antibiotics · 2025Article
- Digital twins in healthcare: a comprehensive review and future directions.Frontiers in digital health · 2025Review
- A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.NPJ systems biology and applications · 2024Review
- ABCD of IA: A multi-scale agent-based model of T cell activation in inflammatory arthritis.Biomaterials science · 2024Article
- Immune-checkpoint inhibitor therapy response evaluation using oncophysics-based mathematical models.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology · 2023Review
- Examining the efficacy of localised gemcitabine therapy for the treatment of pancreatic cancer using a hybrid agent-based model.PLoS computational biology · 2023Article
- Mathematical modeling of cancer immunotherapy for personalized clinical translation.Nature computational science · 2022Article
- Computational analysis of 5-fluorouracil anti-tumor activity in colon cancer using a mechanistic pharmacokinetic/pharmacodynamic model.PLoS computational biology · 2022Article
- Article
- Translational Modeling Identifies Synergy between Nanoparticle-Delivered miRNA-22 and Standard-of-Care Drugs in Triple-Negative Breast Cancer.Pharmaceutical research · 2022Article
- Step-by-step comparison of ordinary differential equation and agent-based approaches to pharmacokinetic-pharmacodynamic models.CPT: pharmacometrics & systems pharmacology · 2022Article
- A mathematical model for the quantification of a patient's sensitivity to checkpoint inhibitors and long-term tumour burden.Nature biomedical engineering · 2021Article
- Modeling Pharmacokinetics and Pharmacodynamics of Therapeutic Antibodies: Progress, Challenges, and Future Directions.Pharmaceutics · 2021Review
- Image-guided mathematical modeling for pharmacological evaluation of nanomaterials and monoclonal antibodies.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology · 2020Review
- A Multiscale Agent-Based Model of Ductal Carcinoma In Situ.IEEE transactions on bio-medical engineering · 2020Article
- A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery.Computational and structural biotechnology journal · 2020Article
- Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis.Frontiers in bioengineering and biotechnology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.
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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.