Evidence map›Paper›PMID 30167825›Full record

ArticleThe AAPS journal2018

Porcine and Human In Vivo Simulations for Doxorubicin-Containing Formulations Used in Locoregional Hepatocellular Carcinoma Treatment.

Ilse R Dubbelboer, Erik Sjögren, Hans Lennernäs

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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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ilse R DubbelboerDepartment of Pharmacy, Uppsala University, Box 580, 751 23, Uppsala, Sweden.ORCID 0000-0002-7806-0447
Erik SjögrenDepartment of Pharmacy, Uppsala University, Box 580, 751 23, Uppsala, Sweden.
Hans LennernäsDepartment of Pharmacy, Uppsala University, Box 580, 751 23, Uppsala, Sweden. hans.lennernas@farmaci.uu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is important to be able to simulate and predict formulation effects on the pharmacokinetics of a drug in order to optimize effectivity in clinical practice and drug development. Two formulations containing doxorubicin are used in the treatment of hepatocellular carcinoma (HCC): a Lipiodol-based emulsion (LIPDOX) and a loadable microbead system (DEBDOX). Although equally effective, the formulations are vastly different, and little is known about the parameters affecting doxorubicin release in vivo. However, mathematical modeling can be used to predict doxorubicin release properties from these formulations and its in vivo pharmacokinetic (PK) profiles. A porcine semi-physiologically based pharmacokinetic (PBPK) model was scaled to a human physiologically based biopharmaceutical (PBBP) model that was altered to include HCC. DOX in vitro and in vivo release data from LIPDOX or DEBDOX were collected from the literature and combined with these in silico models. The simulated pharmacokinetic profiles were then compared with observed porcine and human HCC patient data. DOX pharmacokinetic profiles of LIPDOX-treated HCC patients were best predicted from release data sets acquired by in vitro methods that did not use a diffusion barrier. For the DEBDOX group, the best predictions were from the in vitro release method with a low ion concentration and a reduced loading dose. The in silico modeling combined with historical release data was effective in predicting in vivo plasma exposure. This can give useful insights into the release method properties necessary for correct in vivo predictions of pharmacokinetic profiles of HCC patients dosed with LIPDOX or DEBDOX.

Indexed as

Drug LiberationAnimalsCarcinoma, HepatocellularChemoembolization, TherapeuticComputer SimulationDoxorubicinDrug CarriersEmulsionsEthiodized OilHumansLiverLiver NeoplasmsMicrospheresModels, BiologicalSwineDoxorubicinDrug CarriersEmulsionsEthiodized OilDC beaddoxorubicinhepatocellular carcinomain vitro-in vivo correlationLipiodolphysiologically based biopharmaceutical modelingphysiologically based pharmacokinetic modelingTACE

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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.