ArticleCPT: pharmacometrics & systems pharmacology2017
AFIR: A Dimensionless Potency Metric for Characterizing the Activity of Monoclonal Antibodies.
Article in CPT: pharmacometrics & systems pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Target-Mediated Drug Disposition (TMDD) Revisited: High Versus Low-Affinity Approximations of the TMDD Model.CPT: pharmacometrics & systems pharmacology · 2025Article
- Sabatolimab (MBG453) model-informed drug development for dose selection in patients with myelodysplastic syndrome/acute myeloid leukemia and solid tumors.CPT: pharmacometrics & systems pharmacology · 2023Article
- Mechanistically Weighted Metric to Predict In Vivo Antibody-Receptor Occupancy: An Analytical Approach.The Journal of pharmacology and experimental therapeutics · 2023Article
- Dosing Regimens of Immune Checkpoint Inhibitors: Attempts at Lower Dose, Less Frequency, Shorter Course.Frontiers in oncology · 2022Review
- Estimating drug potency in the competitive target mediated drug disposition (TMDD) system when the endogenous ligand is included.Journal of pharmacokinetics and pharmacodynamics · 2021Article
- Which factors matter the most? Revisiting and dissecting antibody therapeutic doses.Drug discovery today · 2021Review
- Modeling Pharmacokinetics and Pharmacodynamics of Therapeutic Antibodies: Progress, Challenges, and Future Directions.Pharmaceutics · 2021Review
- Guiding dose selection of monoclonal antibodies using a new parameter (AFTIR) for characterizing ligand binding systems.Journal of pharmacokinetics and pharmacodynamics · 2019Article
- Role of Interstitial Fluid Turnover on Target Suppression by Therapeutic Biologics Using a Minimal Physiologically Based Pharmacokinetic Model.The Journal of pharmacology and experimental therapeutics · 2018Article
- Benchmarking QSP Models Against Simple Models: A Path to Improved Comprehension and Predictive Performance.CPT: pharmacometrics & systems pharmacology · 2018Article
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Authors and funding
2 authors.
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Abstract
For monoclonal antibody (mAb) drugs, soluble targets may accumulate several thousand fold after binding to the drug. Time course data of mAb and total target is often collected and, although free target is more closely related to clinical effect, it is difficult to measure. Therefore, mathematical models of this data are used to predict target engagement. In this article, a "potency factor" is introduced as an approximation for the model-predicted target inhibition. This potency factor is defined to be the time-Averaged Free target concentration to Initial target concentration Ratio (AFIR), and it depends on three key quantities: the average drug concentration at steady state; the binding affinity; and the degree of target accumulation. AFIR provides the intuition for how changes in dosing regimen and binding affinity affect target capture and AFIR can be used to predict the druggability of new targets and the expected benefits of more potent, second-generation mAbs.
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