ReviewThe AAPS journal2019
Systemic Bioequivalence Is Unlikely to Equal Target Site Bioequivalence for Nanotechnology Oncologic Products.
Review in The AAPS journal, 2019. 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.
- Physiologically Based Pharmacokinetic Modeling of Efavirenz Nanoparticles: from Animal Model to Human Extrapolation.ACS omega · 2025Article
- Mechanistic modeling of ophthalmic, nasal, injectable, and implant generic drug products: A workshop summary report.CPT: pharmacometrics & systems pharmacology · 2023Review
- Is It Time to Use Modeling of Cellular Transporter Homeostasis to Inform Drug-Drug Interaction Studies: Theoretical Considerations.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
4 authors.
Funding
Abstract
Approval of generic drugs by the US Food and Drug Administration (FDA) requires the product to be pharmaceutically equivalent to the reference listed drug (RLD) and demonstrate bioequivalence (BE) in effectiveness when administered to patients under the conditions in the RLD product labeling. Effectiveness is determined by drug exposure at the target sites. However, since such measurement is usually unavailable, systemic exposure is assumed to equal target site exposure and systemic BE to equal target site BE. This assumption, while it often applies to small molecule drug products that are readily dissolved in biological fluids and systemically absorbed, is unlikely to apply to nanotechnology products (NP) that exist as heterogeneous systems and are subjected to dimension- and material-dependent changes. This commentary provides an overview of the intersecting and spatial-dependent processes and variables governing the delivery and residence of oncologic NP in solid tumors. In order to provide a quantitative perspective of the collective effects of these processes, we used quantitative systems pharmacology (QSP) multi-scale modeling to capture the physicochemical and biological events on several scales (whole-body, organ/suborgan, cell/subcellular, spatial locations, time). QSP is an emerging field that entails using modeling and computation to facilitate drug development; an analogous approach (i.e., model-informed drug development) is advocated by to FDA. The QSP model-based simulations illustrated that small changes in NP attributes (e.g., size variations during manufacturing, interactions with proteins in biological milieu) could lead to disproportionately large differences in target site exposure, rending systemic BE unlikely to equal target site BE.
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.