ReviewCPT: pharmacometrics & systems pharmacology2020
Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities.
Review in CPT: pharmacometrics & systems pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 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
17 citing papers in PubMed.
- Ivonescimab: The Next United States Food and Drug Administration Project Optimus Flashpoint?JTO clinical and research reports · 2026Article
- Follow-Up Bias in Tumor Dynamic Modeling: A Comparison of Classical and Neural-ODE Approaches.CPT: pharmacometrics & systems pharmacology · 2026Article
- Optimal Dosage Justification for Datopotamab Deruxtecan in HR-Positive/HER2-Negative Breast Cancer Through Model-Informed Drug Development Approaches.Clinical and translational science · 2026Article
- Cancer interception during treatment: using growth kinetics to create a continuous variable for assessing disease response.The oncologist · 2025Article
- Advancing drug development with "Fit-for-Purpose" modeling informed approaches.Journal of pharmacokinetics and pharmacodynamics · 2025Review
- Disease Modeling and External Model Evaluation Through Clinical Data Sharing Platform for HR+/HER2- Breast Cancer.CPT: pharmacometrics & systems pharmacology · 2025Article
- Development of a Joint Tumor Size-Overall Survival Modeling and Simulation Framework Supporting Oncology Development Decision-Making.CPT: pharmacometrics & systems pharmacology · 2025Article
- CanSeer: a translational methodology for developing personalized cancer models and therapeutics.Scientific reports · 2025Article
- Ten challenges and opportunities in computational immuno-oncology.Journal for immunotherapy of cancer · 2024Review
- Realizing the promise of Project Optimus: Challenges and emerging opportunities for dose optimization in oncology drug development.CPT: pharmacometrics & systems pharmacology · 2024Review
- Assessing immunotherapy response: going beyond RECIST by integrating early tumor growth kinetics.Frontiers in immunology · 2024Article
- Mechanistic characterization of oscillatory patterns in unperturbed tumor growth dynamics: The interplay between cancer cells and components of tumor microenvironment.PLoS computational biology · 2023Article
- A comprehensive regulatory and industry review of modeling and simulation practices in oncology clinical drug development.Journal of pharmacokinetics and pharmacodynamics · 2023Review
- Longitudinal and time-to-event modeling for prognostic implications of radical surgery in retroperitoneal sarcoma.CPT: pharmacometrics & systems pharmacology · 2022Article
- Article
- Article
- Lenvatinib dose, efficacy, and safety in the treatment of multiple malignancies.Expert review of anticancer therapy · 2022Review
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Model-informed drug development (MIDD) approaches have rapidly advanced in drug development in recent years. Additionally, the Prescription Drug User Fee Act (PDUFA) VI has specific commitments to further enhance MIDD. Tumor growth dynamic (TGD) modeling, as one of the commonly utilized MIDD approaches in oncology, fulfills the purposes to accelerate the drug development, to support new drug and biologics license applications, and to guide the market access. Increasing knowledge of TGD modeling methodologies, encouraging applications in clinical setting for patients' survival, and complementing assessment of regulatory review for submissions, together fueled promising potentials for imminent enhancement of TGD in oncology. This review is to comprehensively summarize the history of TGD, and present case examples of the recent advance of TGD modeling (mixture model and joint model), as well as the TGD impact on regulatory decisions, thus illustrating challenges and opportunities. Additionally, this review presents the future perspectives for TGD approach.
Indexed as
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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.