ReviewACS nano2022
Integration of In Vitro and In Vivo Models to Predict Cellular and Tissue Dosimetry of Nanomaterials Using Physiologically Based Pharmacokinetic Modeling.
Review in ACS nano, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis 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
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-Analysis of Nanoparticle Distribution in Tumors and Major Organs in Tumor-Bearing Mice.ACS nano · 2023Pooled it
- Nanomedicine-based cancer immunotherapy: translational barriers, mechanistic strategies, and future perspectives.Drug delivery · 2026Review
- Enhancing the Antitumor Efficacy of Nisin Through Advanced Nanosystems: A Systematic Review of In Vitro Studies.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Application of 3D Cell Culture Techniques in Nanotoxicology: How Far Are We?Stem cell reviews and reports · 2026Review
- Machine learning models for drug-drug interaction prediction from computational discovery to clinical application.NPJ digital medicine · 2026Review
- Applications of Nanomaterials in Chronic Wound Healing and Scar Prevention.International journal of nanomedicine · 2026Review
- Advancements in dual-targeting nanoparticle strategies for enhanced atherosclerosis therapy: Overcoming limitations of single-targeting approaches.Bioactive materials · 2026Review
- Transformative roles of digital twins from drug discovery to continuous manufacturing: pharmaceutical and biopharmaceutical perspectives.International journal of pharmaceutics: X · 2025Review
- Recent Advances in Machine Learning Models for Predicting Toxicity of Inorganic Nanoparticles.Chem & bio engineering · 2025Review
- Applications of PBPK Models to Predict Tissue Residues and Extralabel Withdrawal Times of Drugs in Food Animals: Perspectives from the Food Animal Residue Avoidance Databank (FARAD) Program.The AAPS journal · 2025Review
- Challenging Traditional ADME Assumptions for Physiologically Based Pharmacokinetic Models for Intravenous Administration of Iron-Carbohydrate Nanomedicines: Potential Utility of Gold Nanoparticle Models as a Roadmap.Clinical pharmacokinetics · 2025Review
- Mechanistic Modeling of Size and Surface Charge Changes of Gold and Silver Nanoparticles during In Vitro Nanoparticle Protein Corona Formation.ACS pharmacology & translational science · 2025Article
- Advances in medical devices using nanomaterials and nanotechnology: Innovation and regulatory science.Bioactive materials · 2025Review
- Advances in nanomaterials for precision drug delivery: Insights into pharmacokinetics and toxicity.BioImpacts : BI · 2025Review
- Predicting tissue distribution and tumor delivery of nanoparticles in mice using machine learning models.Journal of controlled release : official journal of the Controlled Release Society · 2024Article
- Antimicrobial activity of metal-based nanoparticles: a mini-review.Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine · 2024Review
- Advancing Toxicity Predictions: A Review onEnvironment & health (Washington, D.C.) · 2024Review
- A Comprehensive Study on Nanoparticle Drug Delivery to the Brain: Application of Machine Learning Techniques.Molecular pharmaceutics · 2024Article
- Surface Geometry of Cargo-less Gold Nanoparticles Is a Driving Force for Selective Targeting of Activated Neutrophils to Reduce Thrombosis in Antiphospholipid Syndrome.Nano letters · 2023Article
- An artificial intelligence-assisted physiologically-based pharmacokinetic model to predict nanoparticle delivery to tumors in mice.Journal of controlled release : official journal of the Controlled Release Society · 2023Article
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
Abstract
Nanomaterials (NMs) have been increasingly used in a number of areas, including consumer products and nanomedicine. Target tissue dosimetry is important in the evaluation of safety, efficacy, and potential toxicity of NMs. Current evaluation of NM efficacy and safety involves the time-consuming collection of pharmacokinetic and toxicity data in animals and is usually completed one material at a time. This traditional approach no longer meets the demand of the explosive growth of NM-based products. There is an emerging need to develop methods that can help design safe and effective NMs in an efficient manner. In this review article, we critically evaluate existing studies on in vivo pharmacokinetic properties, in vitro cellular uptake and release and kinetic modeling, and whole-body physiologically based pharmacokinetic (PBPK) modeling studies of different NMs. Methods on how to simulate in vitro cellular uptake and release kinetics and how to extrapolate cellular and tissue dosimetry of NMs from in vitro to in vivo via PBPK modeling are discussed. We also share our perspectives on the current challenges and future directions of in vivo pharmacokinetic studies, in vitro cellular uptake and kinetic modeling, and whole-body PBPK modeling studies for NMs. Finally, we propose a nanomaterial in vitro to in vivo extrapolation via physiologically based pharmacokinetic modeling (Nano-IVIVE-PBPK) framework for high-throughput screening of target cellular and tissue dosimetry as well as potential toxicity of different NMs in order to meet the demand of efficient evaluation of the safety, efficacy, and potential toxicity of a rapidly increasing number of NM-based products.
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.