ReviewPharmaceutics2023
Physiologically Based Pharmacokinetic Modeling in Neonates: Current Status and Future Perspectives.
Review in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 14 citations in OpenAlex.
- Applicability of next-generation risk assessment generic PBK models and their performance within the chemical domain.Archives of toxicology · 2026Article
- Silica based nanocarriers for combination immunotherapy targeting the tumor immune microenvironment.Drug delivery and translational research · 2026Review
- [Research progress in artificial intelligence for the diagnosis and management of diseases in preterm infants].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2026Review
- Pharmacological therapy of neonatal analgosedation: current status, dilemmas, and perspectives.Frontiers in pediatrics · 2026Review
- Impact of Food Physical Properties on Oral Drug Absorption: A Comprehensive Review.Drug design, development and therapy · 2025Review
- Application of Physiologically Based Pharmacokinetic Modeling in the Research of Anti-HIV Drugs.Current drug metabolism · 2025Review
- Physiologically Based Pharmacokinetic Modeling to Assess the Impact of Pathophysiological Changes in Neonates: Strengths, Weaknesses, and Next Steps.Journal of clinical pharmacology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Rational drug use in special populations is a clinical problem that doctors and pharma-cists must consider seriously. Neonates are the most physiologically immature and vulnerable to drug dosing. There is a pronounced difference in the anatomical and physiological profiles be-tween neonates and older people, affecting the absorption, distribution, metabolism, and excretion of drugs in vivo, ultimately leading to changes in drug concentration. Thus, dose adjustments in neonates are necessary to achieve adequate therapeutic concentrations and avoid drug toxicity. Over the past few decades, modeling and simulation techniques, especially physiologically based pharmacokinetic (PBPK) modeling, have been increasingly used in pediatric drug development and clinical therapy. This rigorously designed and verified model can effectively compensate for the deficiencies of clinical trials in neonates, provide a valuable reference for clinical research design, and even replace some clinical trials to predict drug plasma concentrations in newborns. This review introduces previous findings regarding age-dependent physiological changes and pathological factors affecting neonatal pharmacokinetics, along with their research means. The application of PBPK modeling in neonatal pharmacokinetic studies of various medications is also reviewed. Based on this, we propose future perspectives on neonatal PBPK modeling and hope for its broader application.
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.