ArticleJournal of pharmacokinetics and pharmacodynamics2015
A PBPK workflow for first-in-human dose selection of a subcutaneously administered pegylated peptide.
Article in Journal of pharmacokinetics and pharmacodynamics, 2015. 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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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.
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Who cites it
10 citing papers in PubMed, 22 citations in OpenAlex.
- Pharmacokinetic Time Course Scaling of a Subcutaneously Administered Pegylated Peptide Conjugate for a First-in-Human Investigation.European journal of drug metabolism and pharmacokinetics · 2017Trial
- Best Practices in Physiologically Based Pharmacokinetic (PBPK) Modeling.CPT: pharmacometrics & systems pharmacology · 2026Review
- Utilization of Physiologically Based Pharmacokinetic Modeling in Pharmacokinetic Study of Natural Medicine: An Overview.Molecules (Basel, Switzerland) · 2022Review
- Monoclonal Antibody Pharmacokinetics in Cynomolgus Monkeys Following Subcutaneous Administration: Physiologically Based Model Predictions from Physiochemical Properties.The AAPS journal · 2022Article
- Mathematical Models to Characterize the Absorption, Distribution, Metabolism, and Excretion of Protein Therapeutics.Drug metabolism and disposition: the biological fate of chemicals · 2022Review
- Current and prospective computational approaches and challenges for developing COVID-19 vaccines.Advanced drug delivery reviews · 2021Review
- Sampling Site Has a Critical Impact on Physiologically Based Pharmacokinetic Modeling.The Journal of pharmacology and experimental therapeutics · 2020Article
- A generic whole body physiologically based pharmacokinetic model for therapeutic proteins in PK-Sim.Journal of pharmacokinetics and pharmacodynamics · 2018Article
- Population physiologically-based pharmacokinetic model incorporating lymphatic uptake for a subcutaneously administered pegylated peptide.In silico pharmacology · 2016Article
- A Bottom-Up Whole-Body Physiologically Based Pharmacokinetic Model to Mechanistically Predict Tissue Distribution and the Rate of Subcutaneous Absorption of Therapeutic Proteins.The AAPS journal · 2016Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predicting the pharmacokinetic (PK) time course of a subcutaneously (SC) administered novel therapeutic protein using in silico approaches offers an opportunity to streamline the drug development process by facilitating selection of starting and target doses in initial human trials. Herein, we propose a workflow for predicting the human exposure time course following SC administration. Leveraging knowledge obtained following both intravenous and SC administration in monkeys, this workflow employs the development of a whole body physiologically-based pharmacokinetic (PBPK) model incorporating vascular circulation, lymphatic uptake and both renal and non-specific clearance mechanisms to predict the PK of a novel pegylated peptide. Optimization of the model was initially performed in monkeys, after which the model was scaled up to human proportion. Inclusion of a SC depot compartment allowed for precise simulation of the SC time course in monkeys. Simulated human exposure after SC administration was within approximately 20 % of the observed values and successfully predicted the time course of two subsequent dosing levels. This workflow represents one of the first publications of a PBPK workflow to predict the time course of a SC administered therapeutic protein based off of a single, non-human primate species and shows promise in facilitating the dose selection in first-in-human dose escalation studies for novel protein therapeutics.
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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.