Evidence map›Paper›PMID 32454086›Full record

ReviewActa biomaterialia2020

Self-assembling prodrug nanotherapeutics for synergistic tumor targeted drug delivery.

Zhiren Wang, Jiawei Chen, Nicholas Little, Jianqin Lu

Abstract readReview
In one paragraph

Review in Acta biomaterialia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

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

23 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
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  6. Review
  7. Article
  8. Intelligent Drug Delivery by Peptide-Based Dual-Function Micelles.International journal of molecular sciences · 2022
    Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Review
  14. Review
  15. Article
  16. Review
  17. Article
  18. Review
  19. Nanoparticulation of Prodrug into Medicines for Cancer Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021
    Review
  20. Review
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

4 authors.

Zhiren WangSkaggs Pharmaceutical Sciences Center, Department of Pharmacology & Toxicology, College of Pharmacy, The University of Arizona, Tucson, AZ, 85721, United States.
Jiawei ChenSkaggs Pharmaceutical Sciences Center, Department of Pharmacology & Toxicology, College of Pharmacy, The University of Arizona, Tucson, AZ, 85721, United States.
Nicholas LittleSkaggs Pharmaceutical Sciences Center, Department of Pharmacology & Toxicology, College of Pharmacy, The University of Arizona, Tucson, AZ, 85721, United States.
Jianqin LuSkaggs Pharmaceutical Sciences Center, Department of Pharmacology & Toxicology, College of Pharmacy, The University of Arizona, Tucson, AZ, 85721, United States; NCI-designated University of Arizona Comprehensive Cancer Center, Tucson, Arizona, 85721, United States; Southwest Environmental Health Sciences Center, The University of Arizona, Tucson, 85721, United States; BIO5 Institute, The University of Arizona, Tucson, Arizona, 85721, United States. Electronic address: lu6@pharmacy.arizona.edu.

Funding

SOUTHWEST ENVIRONMENTAL HEALTH SCIENCES CENTERP30ES006694 · NIEHS · UNIVERSITY OF ARIZONA · PI DEAN BILLHEIMER · 1994 to 2026
$36.7M
NRF Transcription Factors in Environmental Stress and Disease InterventionR35ES031575 · NIEHS · UNIVERSITY OF FLORIDA · PI Donna D Zhang · 2020 to 2026
$7.1M
NIEHS NIH HHS P30 ES006694NIEHS NIH HHS R35 ES031575
6 · The paper itself

Abstract

Self-assembling prodrugs represents a robust and effective nanotherapeutic approach for delivering poorly soluble anticancer drugs. With numerous intrinsic advantages, self-assembling prodrugs possess the maximum drug loading capacity, controlled drug release kinetics, prolonged blood circulation, and preferential tumor accumulation based on the enhanced permeability and retention (EPR) effect. These prodrug conjugates allow for efficient self-assembly into nanodrugs with the potential of encapsulating other therapeutic agents that have different molecular targets, enabling simultaneous temporal-spatial release of drugs for synergistic antitumor efficacy with reduced systemic side effects. The aim of this review is to summarize the recent progress of self-assembling prodrug cancer nanotherapeutics that are made through conjugating therapeutically active agents to Polyethylene glycol, Vitamin E, or drugs with different physicochemical properties via rational design, for synergistic tumor targeted drug delivery. STATEMENT OF SIGNIFICANCE: All current FDA-approved nanomedicines use inert biomaterials as drug delivery carriers. These biomaterials lack any therapeutic potential, contributing not only to the cost, but may also elicit severe unfavorable adverse effects. Despite the reduction in toxicity associated with the payload, these nanotherapeutics have been met with limited clinical success, likely due to the monotherapy regimen. The self-assembling prodrug (SAP) has been emerging as a powerful platform for enhancing efficacy through co-delivering other therapeutic modalities with distinct molecular targets. Herein, we opportunely present a comprehensive review article summarizing three unique approaches of making SAP for synergistic drug delivery: pegylation, vitamin E-derivatization, and drug-drug conjugation. These SAPs may inevitably pave the way for developing more efficacious, clinically translatable, combination cancer nanotherapies.

Indexed as

Antineoplastic AgentsNanoparticlesNeoplasmsProdrugsCell Line, TumorDrug CarriersDrug Delivery SystemsDrug LiberationHumansAntineoplastic AgentsDrug CarriersProdrugsEnhanced Cancer TherapyNanotherapeuticsSelf-assembling prodrugSynergistic drug delivery

Identifiers

PMID32454086
PMCPMC7245299

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.