Evidence map›Paper›PMID 31119521›Full record

ArticleDrug delivery and translational research2019

Total drug quantification in prodrugs using an automated elemental analyzer.

Yingwen Hu, David M Stevens, Sonny Man, Rachael M Crist, Jeffrey D Clogston

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Article in Drug delivery and translational research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yingwen HuNanotechnology Characterization Laboratory, Cancer Research Technology Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
David M StevensNanotechnology Characterization Laboratory, Cancer Research Technology Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
Sonny ManNanotechnology Characterization Laboratory, Cancer Research Technology Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
Rachael M CristNanotechnology Characterization Laboratory, Cancer Research Technology Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
Jeffrey D ClogstonNanotechnology Characterization Laboratory, Cancer Research Technology Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA. Jeffrey.Clogston@nih.gov.ORCID 0000-0003-1860-9271

Funding

NIH HHS HHSN261200800001E
6 · The paper itself

Abstract

Polymeric prodrugs have become an increasingly popular strategy for improving the pharmacokinetic properties of active pharmaceutical ingredients (API). Therefore, identifying a robust method for quantification of the API in these prodrug products is a key part of the drug development process. Current drug quantification methods include hydrolysis followed by reversed phase high-performance liquid chromatography (RP-HPLC), size exclusion chromatography (SEC)-based molecular weight determination, and mass spectrometry. These methods tend to be time-consuming and often require challenging method development. Here, we present a comparative study highlighting the automated elemental analyzer as a facile approach to drug quantification in this up-and-coming class of therapeutics. A polymeric prodrug using poly(L-lysine succinylated) (PLS) and the drug lamivudine (LAM) was prepared and analyzed using the elemental analyzer in comparison to the traditional approaches of hydrolysis followed by RP-HPLC and SEC using multi-angle light scattering (MALS) detection. The elemental analysis approach showed excellent agreement with the conventional methods but proved much less laborious, highlighting this as a rapid and sensitive analytical method for the quantitative determination of drug loading in polymeric prodrug products.

Indexed as

Chromatography, GelChromatography, High Pressure LiquidHydrolysisLamivudinePolylysineProdrugsScattering, RadiationLamivudinePolylysineProdrugsDrug loadingElemental analysisNanomedicineNanoparticlePolymer–drug conjugatesProdrug

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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.