Trial reportThe AAPS journal2016
Examining the Use of a Mechanistic Model to Generate an In Vivo/In Vitro Correlation: Journey Through a Thought Process.
Trial report in The AAPS journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- A critical review on approaches to generate and validate virtual population for physiologically based pharmacokinetic models: Methodologies, case studies and way forward.European journal of clinical pharmacology · 2024Review
- Physiologically based pharmacokinetic modeling and simulations to inform dissolution specifications and clinical relevance of release rates on elagolix exposure.Biopharmaceutics & drug disposition · 2022Article
- Biopharmaceutics Applications of Physiologically Based Pharmacokinetic Absorption Modeling and Simulation in Regulatory Submissions to the U.S. Food and Drug Administration for New Drugs.The AAPS journal · 2021Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The attention and interest in establishing in vivo/in vitro correlations (IVIVCs) is grounded in its tremendous utility as a prognostic tool. It can be used to support formulation optimization, predict in vivo drug exposure across a potential patient population, select a biologically relevant in vitro dissolution test condition, and support the use of in vitro dissolution data as a surrogate for in vivo bioequivalence trials. The pharmacological and statistical implications of this correlation are linked to the method by which the IVIVC was determined and to the assumptions and optimization approaches integrated into the estimation procedure. Using previously published data generated in normal healthy volunteers, an IVIVC for metoprolol was established using a mechanistic modeling approach. Within that framework, we explored the consequences of (1) our method of fitting a single Weibull function to the in vivo dissolution, (2) our selection of weighting scheme and optimization approaches, (3) the impact of applying a fixed versus fitted gastric emptying time, and 4) the importance of factoring population variability into our IVIVC estimation and profile reconvolution. We identified those factors found to be critical in terms of their influence on the accuracy of our predicted systemic metoprolol concentration-time profiles. We considered the strengths and weaknesses of our approach and discussed how the results of this study may impact efforts to generate IVIVCs with compounds presenting physicochemical characteristics different from that of metoprolol.
Indexed as
Identifiers
27312260What 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.