Evidence map›Paper›PMID 39065655›Full record

ArticlePharmaceutics2024

Investigation of Stabilized Amorphous Solid Dispersions to Improve Oral Olaparib Absorption.

Taehan Yun, Sumin Lee, Seowan Yun, Daeyeong Cho, Kyuho Bang, Kyeongsoo Kim

Abstract read
In one paragraph

Article in Pharmaceutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Taehan YunDepartment of Pharmaceutical Engineering, Gyeongsang National University, 33 Dongjin-ro, Jinju 52725, Republic of Korea.
Sumin LeeDepartment of Pharmaceutical Engineering, Gyeongsang National University, 33 Dongjin-ro, Jinju 52725, Republic of Korea.
Seowan YunDepartment of Pharmaceutical Engineering, Gyeongsang National University, 33 Dongjin-ro, Jinju 52725, Republic of Korea.
Daeyeong ChoDepartment of Pharmaceutical Engineering, Gyeongsang National University, 33 Dongjin-ro, Jinju 52725, Republic of Korea.
Kyuho BangDepartment of Pharmaceutical Engineering, Gyeongsang National University, 33 Dongjin-ro, Jinju 52725, Republic of Korea.
Kyeongsoo KimDepartment of Pharmaceutical Engineering, Gyeongsang National University, 33 Dongjin-ro, Jinju 52725, Republic of Korea.ORCID 0000-0001-7469-3215

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we investigated the formulation of stable solid dispersions to enhance the bioavailability of olaparib (OLA), a therapeutic agent for ovarian cancer and breast cancer characterized as a BCS class IV drug with low solubility and low permeability. Various polymers were screened based on solubility tests, and OLA-loaded solid dispersions were prepared using spray drying. The physicochemical properties of these dispersions were investigated via scanning electron microscopy (SEM), differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD), and Fourier Transform Infrared Spectroscopy (FT-IR). Subsequent dissolution tests, along with assessments of morphological and crystallinity changes in aqueous solutions, led to the selection of a hypromellose (HPMC)-based OLA solid dispersion as the optimal formulation. HPMC was effective at maintaining the supersaturation of OLA in aqueous solutions and exhibited a stable amorphous state without recrystallization. In an in vivo study, this HPMC-based OLA solid dispersion significantly enhanced bioavailability, increasing AUC

Indexed as

bioavailabilityHPMColaparibsolid dispersionsolubility

Identifiers

PMID39065655
PMCPMC11280475

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Registered trials

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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.