ReviewThe oncologist2016
Bringing Model-Based Prediction to Oncology Clinical Practice: A Review of Pharmacometrics Principles and Applications.
Review in The oncologist, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Population Pharmacokinetic and Toxicity Analysis of High-Dose Methotrexate in Patients with Central Nervous System Lymphoma.Clinical pharmacokinetics · 2025Article
- Quantitative modeling of tumor dynamics and development of drug resistance in non-small cell lung cancer patients treated with erlotinib.CPT: pharmacometrics & systems pharmacology · 2024Article
- Exposure-response relationship of cabozantinib in patients with metastatic renal cell carcinoma treated in routine care.British journal of cancer · 2024Article
- Empirical methods for the validation of time-to-event mathematical models taking into account uncertainty and variability: application to EGFR + lung adenocarcinoma.BMC bioinformatics · 2023Article
- Delivery of Chemotherapy Agents and Nucleic Acids with pH-Dependent Nanoparticles.Pharmaceutics · 2023Review
- Anti-cancer treatment schedule optimization based on tumor dynamics modelling incorporating evolving resistance.Scientific reports · 2022Article
- Population pharmacokinetic study of pemetrexed in chinese primary advanced non-small cell lung carcinoma patients.Frontiers in pharmacology · 2022Article
- Evaluation of solid tumor response to sequential treatment cycles via a new computational hybrid approach.Scientific reports · 2021Article
- Population Pharmacokinetic and Pharmacogenetic Analysis of Mitotane in Patients with Adrenocortical Carcinoma: Towards Individualized Dosing.Clinical pharmacokinetics · 2021Article
- Integrated Data Analysis of Six Clinical Studies Points Toward Model-Informed Precision Dosing of Tamoxifen.Frontiers in pharmacology · 2020Article
- A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors.CPT: pharmacometrics & systems pharmacology · 2019Review
- Looking beyond the hype: Applied AI and machine learning in translational medicine.EBioMedicine · 2019Review
- Assessing the impact of the addition of dendritic cell vaccination to neoadjuvant chemotherapy in breast cancer patients: A model-based characterization approach.British journal of clinical pharmacology · 2019Article
- Quantitative Systems Pharmacology: An Exemplar Model-Building Workflow With Applications in Cardiovascular, Metabolic, and Oncology Drug Development.CPT: pharmacometrics & systems pharmacology · 2019Review
- Article
- Neoadjuvant therapy for locally advanced gastric cancer patients. A population pharmacodynamic modeling.PloS one · 2019Article
- Pharmacometric Applications and Challenges in the Development of Therapeutic Antibodies in Immuno-Oncology.Current pharmacology reports · 2018Article
- Emerging roles for clinical pharmacometrics in cancer precision medicine.Current pharmacology reports · 2018Article
- In silico cancer research towards 3R.BMC cancer · 2018Review
- Reverse Translation of US Food and Drug Administration Reviews of Oncology New Molecular Entities Approved in 2011-2017: Lessons Learned for Anticancer Drug Development.Clinical and translational science · 2018Review
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
No grant is acknowledged in the PubMed record.
Abstract
unlabelledDespite much investment and progress, oncology is still an area with significant unmet medical needs, with new therapies and more effective use of current therapies needed. The emergent field of pharmacometrics combines principles from pharmacology (pharmacokinetics [PK] and pharmacodynamics [PD]), statistics, and computational modeling to support drug development and optimize the use of already marketed drugs. Although it has gained a role within drug development, its use in clinical practice remains scarce. The aim of the present study was to review the principal pharmacometric concepts and provide some examples of its use in oncology. Integrated population PK/PD/disease progression models as part of the pharmacometrics platform provide a powerful tool to predict outcomes so that the right dose can be given to the right patient to maximize drug efficacy and reduce drug toxicity. Population models often can be developed with routinely collected medical record data; therefore, we encourage the application of such models in the clinical setting by generating close collaborations between physicians and pharmacometricians. IMPLICATIONS FOR PRACTICE: The present review details how the emerging field of pharmacometrics can integrate medical record data with predictive pharmacological and statistical models of drug response to optimize and individualize therapies. In order to make this routine practice in the clinic, greater awareness of the potential benefits of the field is required among clinicians, together with closer collaboration between pharmacometricians and clinicians to ensure the requisite data are collected in a suitable format for pharmacometrics analysis.
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