ReviewClinical pharmacology and therapeutics2020
Integration of Omics Data Sources to Inform Mechanistic Modeling of Immune-Oncology Therapies: A Tutorial for Clinical Pharmacologists.
Review in Clinical pharmacology and therapeutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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.
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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
27 citing papers in PubMed, 35 citations in OpenAlex.
- From Prediction to Decision Making: PBPK and QSP as Regulatory-Grade NAMs.Clinical pharmacology and therapeutics · 2026Review
- High-Dose Sunitinib Accelerates Triple-Negative Breast Cancer Metastasis by Modulating an Immunosuppressive Microenvironment: A Preclinical 4T1 Model Study.Pharmaceutical research · 2026Article
- AI-driven big data analysis and predictive modeling of infectious disease immunity: from correlates to causal, multiscale understanding.Archives of microbiology · 2026Review
- Model-Informed Drug Development: Addressing the Critical Need for Training in the Promising New Field.Delaware journal of public health · 2026Article
- Multi-physiology modeling of the immune system in the era of precision immunotherapy.Frontiers in immunology · 2025Review
- Combining mechanistic modeling with machine learning as a strategy to predict inflammatory bowel disease clinical scores.Frontiers in pharmacology · 2025Article
- Quantitative Systems Pharmacology Modeling in Immuno-Oncology: Hypothesis Testing, Dose Optimization, and Efficacy Prediction.Handbook of experimental pharmacology · 2025Review
- Role of Data in Development and Application of Quantitative Systems Pharmacology Models.Handbook of experimental pharmacology · 2025Review
- Advancing cancer drug development with mechanistic mathematical modeling: bridging the gap between theory and practice.Journal of pharmacokinetics and pharmacodynamics · 2024Review
- Towards a comprehensive assessment of QSP models: what would it take?Journal of pharmacokinetics and pharmacodynamics · 2024Review
- From virtual patients to digital twins in immuno-oncology: lessons learned from mechanistic quantitative systems pharmacology modeling.NPJ digital medicine · 2024Review
- Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology.Briefings in bioinformatics · 2024Article
- A transcriptome-informed QSP model of metastatic triple-negative breast cancer identifies predictive biomarkers for PD-1 inhibition.Science advances · 2023Article
- Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition.NPJ precision oncology · 2023Article
- Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition.bioRxiv : the preprint server for biology · 2023Article
- Accelerating robust plausible virtual patient cohort generation by substituting ODE simulations with parameter space mapping.Journal of pharmacokinetics and pharmacodynamics · 2022Article
- Article
- Systems biology of angiogenesis signaling: Computational models and omics.WIREs mechanisms of disease · 2022Review
- Quantitative systems pharmacology modeling provides insight into inter-mouse variability of Anti-CTLA4 response.CPT: pharmacometrics & systems pharmacology · 2022Article
- Model-informed target identification and validation through combining quantitative systems pharmacology with network-based analysis.CPT: pharmacometrics & systems pharmacology · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Application of contemporary molecular biology techniques to clinical samples in oncology resulted in the accumulation of unprecedented experimental data. These "omics" data are mined for discovery of therapeutic target combinations and diagnostic biomarkers. It is less appreciated that omics resources could also revolutionize development of the mechanistic models informing clinical pharmacology quantitative decisions about dose amount, timing, and sequence. We discuss the integration of omics data to inform mechanistic models supporting drug development in immuno-oncology. To illustrate our arguments, we present a minimal clinical model of the Cancer Immunity Cycle (CIC), calibrated for non-small cell lung carcinoma using tumor microenvironment composition inferred from transcriptomics of clinical samples. We review omics data resources, which can be integrated to parameterize mechanistic models of the CIC. We propose that virtual trial simulations with clinical Quantitative Systems Pharmacology platforms informed by omics data will be making increasing impact in the development of cancer immunotherapies.
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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.