ReviewJournal of pharmacokinetics and pharmacodynamics2016
Array of translational systems pharmacodynamic models of anti-cancer drugs.
Review in Journal of pharmacokinetics and pharmacodynamics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 17 citations in OpenAlex.
- Chemical Epigenetics: Small Molecules Targeting Chromatin Modifiers in Disease Modulation.Cell biochemistry and biophysics · 2026Review
- A Systematic Comparative Analysis of Tumor Size Models Based on Erlotinib Clinical Data in Advanced NSCLC.CPT: pharmacometrics & systems pharmacology · 2025Article
- Practical Pharmacokinetic-Pharmacodynamic Models in Oncology.Pharmaceutics · 2025Review
- Anatomical Targeting of Anticancer Drugs to Solid Tumors Using Specific Administration Routes: Review.Pharmaceutics · 2023Review
- How translational modeling in oncology needs to get the mechanism just right.Clinical and translational science · 2022Review
- Translational Modeling of Anticancer Efficacy to Predict Clinical Outcomes in a First-in-Human Phase 1 Study of MDM2 Inhibitor HDM201.The AAPS journal · 2021Article
- Progress and Opportunities to Advance Clinical Cancer Therapeutics Using Tumor Dynamic Models.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020Review
- Disease progression model of 4T1 metastatic breast cancer.Journal of pharmacokinetics and pharmacodynamics · 2020Article
- Translational Framework Predicting Tumour Response in Gemcitabine-Treated Patients with Advanced Pancreatic and Ovarian Cancer from Xenograft Studies.The AAPS journal · 2019Article
- Utility of a Novel Three-Dimensional and Dynamic (3DD) Cell Culture System for PK/PD Studies: Evaluation of a Triple Combination Therapy at Overcoming Anti-HER2 Treatment Resistance in Breast Cancer.Frontiers in pharmacology · 2018Article
- Knockdown of HOXA transcript at the distal tip suppresses the growth and invasion and induces apoptosis of oral tongue squamous carcinoma cells.OncoTargets and therapy · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is a complex disease that is characterized by an uncontrolled growth and spread of abnormal cells. Drug development in oncology is particularly challenging and is associated with one of the highest attrition rates of compounds despite substantial investments in resources. Pharmacokinetic and pharmacodynamic (PK/PD) modeling seeks to couple experimental data with mathematical models to provide key insights into factors controlling cytotoxic effects of chemotherapeutics and cancer progression. PK/PD modeling of anti-cancer compounds is equally challenging, partly based on the complexity of biological and pharmacological systems. However, reliable mechanistic and systems PK/PD models for anti-cancer agents have been developed and successfully applied to: (1) provide insights into fundamental mechanisms implicated in tumor growth, (2) assist in dose selection for first-in-human phase I studies (e.g., effective dose, escalating doses, and maximal tolerated doses), (3) design and optimize combination drug regimens, (4) design clinical trials, and (5) establish links between drug efficacy and safety and the concentrations of measured biomarkers. In this commentary, classes of relevant mechanism-based and systems PK/PD models of anti-cancer agents that have shown promise in translating preclinical data and enhancing stages of the drug development process are reviewed. Specific features of such models are discussed including their strengths and limitations along with a prospectus of using these models alone or in combination for cancer therapy.
Indexed as
Identifiers
What OpenQuestion holds
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.