ArticleThe AAPS journal2018
PBPK and its Virtual Populations: the Impact of Physiology on Pediatric Pharmacokinetic Predictions of Tramadol.
Article in The AAPS journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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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.
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Who cites it
21 citing papers in PubMed, 36 citations in OpenAlex.
- Differences in Physiologically Based Pharmacokinetic Predictions between Software Platforms Can Be Clinically Relevant: Cases of Levornestrogel and Ethinylestradiol Concentrations with SIMCYP versus PK-Sim from a User Perspective.European journal of drug metabolism and pharmacokinetics · 2026Article
- Population Physiologically-Based Pharmacokinetic Modeling to Determine Ontogeny: A Quantitative Clinical Pharmacology Example in Pediatric Rare Disease.CPT: pharmacometrics & systems pharmacology · 2026Review
- Leveraging In Silico and Artificial Intelligence Models to Advance Drug Disposition and Response Predictions Across the Lifespan.Clinical and translational science · 2025Review
- Utilizing Physiologically Based Pharmacokinetic Models to Support Rational Medication in Chinese Elderly Population.Drug design, development and therapy · 2025Article
- Recent Progress on Physiologically Based Pharmacokinetic (PBPK) Model: A Review Based on Bibliometrics.Toxics · 2024Review
- Physiologically Based Pharmacokinetic Modeling in Neonates: Current Status and Future Perspectives.Pharmaceutics · 2023Review
- A Physiologically Based Pharmacokinetic Model to Predict Systemic Ondansetron Concentration in Liver Cirrhosis Patients.Pharmaceuticals (Basel, Switzerland) · 2023Article
- The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment.International journal of environmental research and public health · 2023Review
- Review
- Application of Physiologically Based Pharmacokinetic Modeling in Preclinical Studies: A Feasible Strategy to Practice the Principles of 3Rs.Frontiers in pharmacology · 2022Article
- Physiologically Based Pharmacokinetic Modeling to Assess the Impact of CYP2D6-Mediated Drug-Drug Interactions on Tramadol and O-Desmethyltramadol Exposures via Allosteric and Competitive Inhibition.Journal of clinical pharmacology · 2022Article
- SeDeM tool-driven full factorial design for osmotic drug delivery of tramadol HCl: Formulation development, physicochemical evaluation, andFrontiers in pharmacology · 2022Article
- Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development.AAPS PharmSciTech · 2021Review
- The Combination of Cell Cultured Technology and In Silico Model to Inform the Drug Development.Pharmaceutics · 2021Review
- Development and Evaluation of a Physiologically Based Pharmacokinetic Drug-Disease Model of Propranolol for Suggesting Model Informed Dosing in Liver Cirrhosis Patients.Drug design, development and therapy · 2021Article
- Factors Affecting Successful Extrapolation of Ibuprofen Exposure from Adults to Pediatric Populations After Oral Administration of a Pediatric Aqueous Suspension.The AAPS journal · 2020Article
- Successful Extrapolation of Paracetamol Exposure from Adults to Infants After Oral Administration of a Pediatric Aqueous Suspension Is Highly Dependent on the Study Dosing Conditions.The AAPS journal · 2020Article
- Computational Approaches in Preclinical Studies on Drug Discovery and Development.Frontiers in chemistry · 2020Review
- Evaluation of the Effect of CYP2D6 Genotypes on Tramadol andPharmaceutics · 2019Article
- Physiologically Based Pharmacokinetic Modeling of Oxycodone in Children to Support Pediatric Dosing Optimization.Pharmaceutical research · 2019Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In pediatric PBPK models, age-related changes in the body are known to occur. Given the sparsity of and the variability associated with relevant physiological parameters, different PBPK software providers may vary in their system's data. In this work, three commercially available PBPK software packages (PK-Sim®, Simcyp®, and Gastroplus®) were investigated regarding their differences in system-related information, possibly affecting clearance prediction. Three retrograde PBPK clearance models were set up to enable prediction of pediatric tramadol clearance. These models were qualified in terms of total, CYP2D6, and renal clearance in adults. Tramadol pediatric clearance predictions from PBPK were compared with a pooled popPK model covering clearance ranging from neonates to adults. Fold prediction errors were used to evaluate the results. Marked differences in liver clearance prediction between PBPK models were observed. In general, the prediction bias of total clearance was greatest at the youngest population and decreased with age. Regarding CYP2D6 and renal clearance, important differences exist between PBPK software tools. Interestingly, the PBPK model with the shortest CYP2D6 maturation half-life (PK-Sim) agreed best with the in vivo CYP2D6 maturation model. Marked differences in physiological data explain the observed differences in hepatic clearance prediction in early life between the various PBPK software providers tested. Consensus on the most suited pediatric data to use should harmonize and optimize pediatric clearance predictions. Moreover, the combination of bottom-up and top-down approaches, using a convenient probe substrate, has the potential to update system-related parameters in order to better represent pediatric physiology.
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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.