ArticleiScience2019
A Bioluminescence Resonance Energy Transfer-Based Approach for Determining Antibody-Receptor Occupancy In Vivo.
Article in iScience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 17 citations in OpenAlex.
- Dynamic Tracking ofMolecular pharmaceutics · 2025Article
- OptimizediScience · 2024Article
- Integrated PK/PD Modeling Relates Smoothened Inhibitor Biomarkers to The Heterogeneous Intratumor Disposition of Cetuximab in Pancreatic Cancer Tumor Models.Journal of pharmaceutical sciences · 2024Article
- Mechanistically Weighted Metric to Predict In Vivo Antibody-Receptor Occupancy: An Analytical Approach.The Journal of pharmacology and experimental therapeutics · 2023Article
- NanoBRET in C. elegans illuminates functional receptor interactions in real time.BMC molecular and cell biology · 2022Article
- Development of a Human Estrogen Receptor Dimerization Assay for the Estrogenic Endocrine-Disrupting Chemicals Using Bioluminescence Resonance Energy Transfer.International journal of environmental research and public health · 2021Article
- Modeling Pharmacokinetics and Pharmacodynamics of Therapeutic Antibodies: Progress, Challenges, and Future Directions.Pharmaceutics · 2021Review
- Modeling the dynamics of antibody-target binding in living tumors.Scientific reports · 2020Article
- Recent progress in the molecular imaging of therapeutic monoclonal antibodies.Journal of pharmaceutical analysis · 2020Review
- Self-Illuminating Agents for Deep-Tissue Optical Imaging.Frontiers in bioengineering and biotechnology · 2019Review
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 at 1 institution in 1 country.
Funding
Abstract
Elucidating receptor occupancy (RO) of monoclonal antibodies (mAbs) is a crucial step in characterizing the therapeutic efficacy of mAbs. However, the in vivo assessment of RO, particularly within peripheral tissues, is greatly limited by current technologies. In the present study, we developed a bioluminescence resonance energy transfer (BRET)-based system that leverages the large signal:noise ratio and stringent energy donor-acceptor distance dependency to measure antibody RO in a highly selective and temporal fashion. This versatile and minimally invasive system enables longitudinal monitoring of the in vivo antibody-receptor engagement over several days. As a proof of principle, we quantified cetuximab-epidermal growth factor receptor binding kinetics using this system and assessed cetuximab RO in a tumor xenograft model. Incomplete ROs were observed, even at a supratherapeutic dose of 50 mg/kg, indicating that fractional target accessibility is achieved. The BRET-based imaging approach enables quantification of antibody in vivo RO and provides critical information required to optimize therapeutic mAb efficacy.
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.