ArticleClinical and translational science2020
Predicting In Vivo Efficacy from In Vitro Data: Quantitative Systems Pharmacology Modeling for an Epigenetic Modifier Drug in Cancer.
Article in Clinical and translational science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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
15 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Natural Killer Cell-Derived Extracellular Vesicles as a Promising Immunotherapeutic Strategy for Cancer: A Systematic Review.International journal of molecular sciences · 2023Pooled it
- Recent applications of quantitative systems pharmacology and machine learning models across diseases.Journal of pharmacokinetics and pharmacodynamics · 2022Pooled it
- Innovative horizons: harnessing drug repositioning for targeted therapeutics in colorectal cancer.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Inhibition Effects of Patchouli Alcohol, Carvacrol, p-Cymene, Eucalyptol and Their Formulations Against Influenza Virus Pneumonia Through TLR4/NF-κB/NLRP3 Signaling Pathway.Chemical biology & drug design · 2025Article
- Carotenoids Modulate FoxO-Induced Cell Cycle Awrrest in Human Cancer Cell Lines: A Scoping Review.Food science & nutrition · 2025Article
- Demonstrating the Absence of Correlation Between Molecular Docking and in vitro Cytotoxicity in Anti-Breast Cancer Research: Root Causes and Practical Resolutions.Breast cancer (Dove Medical Press) · 2025Review
- Ivermectin Strengthens Paclitaxel Effectiveness in High-Grade Serous Carcinoma in 3D Cell Cultures.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Applying quantitative and systems pharmacology to drug development and beyond: An introduction to clinical pharmacologists.Indian journal of pharmacology · 2024Review
- Role of midazolam on cancer progression/survival - An updated systematic review.Indian journal of anaesthesia · 2023Article
- Size-Dependent Polymeric Nanoparticle Distribution in a Static versus Dynamic Microfluidic Blood Vessel Model: Implications for Nanoparticle-Based Drug Delivery.ACS applied nano materials · 2023Article
- Cell state-directed therapy - epigenetic modulation of gene transcription demonstrated with a quantitative systems pharmacology model of temozolomide.CPT: pharmacometrics & systems pharmacology · 2023Article
- Differential Effects of Cytokine Versus Hypoxic Preconditioning of Human Mesenchymal Stromal Cells in Pulmonary Sepsis Induced by Antimicrobial-ResistantPharmaceuticals (Basel, Switzerland) · 2023Article
- Growth-rate model predicts in vivo tumor response from in vitro data.CPT: pharmacometrics & systems pharmacology · 2022Article
- Leveraging modeling and simulation to optimize the therapeutic window for epigenetic modifier drugs.Pharmacology & therapeutics · 2022Review
- Approaches for evaluation of novel CPP-based cargo delivery systems.Frontiers in pharmacology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Reliably predicting in vivo efficacy from in vitro data would facilitate drug development by reducing animal usage and guiding drug dosing in human clinical trials. However, such prediction remains challenging. Here, we built a quantitative pharmacokinetic/pharmacodynamic (PK/PD) mathematical model capable of predicting in vivo efficacy in animal xenograft models of tumor growth while trained almost exclusively on in vitro cell culture data sets. We studied a chemical inhibitor of LSD1 (ORY-1001), a lysine-specific histone demethylase enzyme with epigenetic function, and drug-induced regulation of target engagement, biomarker levels, and tumor cell growth across multiple doses administered in a pulsed and continuous fashion. A PK model of unbound plasma drug concentration was linked to the in vitro PD model, which enabled the prediction of in vivo tumor growth dynamics across a range of drug doses and regimens. Remarkably, only a change in a single parameter-the one controlling intrinsic cell/tumor growth in the absence of drug-was needed to scale the PD model from the in vitro to in vivo setting. These findings create a framework for using in vitro data to predict in vivo drug efficacy with clear benefits to reducing animal usage while enabling the collection of dense time course and dose response data in a highly controlled in vitro environment.
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.