Evidence map›Paper›PMID 38918993›Full record

ReviewCurrent medicinal chemistry2025

Hybrid Nanoparticles for Cancer Theranostics: A Critical Review on Design, Synthesis, and Multifunctional Capabilities.

Saurabh Raka, Sateesh Belemkar, Sankha Bhattacharya

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current medicinal chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. 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

3 authors.

Saurabh RakaDepartment of Pharmaceutics, School of Pharmacy and Technology Management, SVKM'S NMIMS Deemed-to-be University, Shirpur, Maharashtra, 425405, India.ORCID 0009-0002-2164-6479
Sateesh BelemkarDepartment of Pharmacology, Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKMs NMIMS Deemed-to-be University, V L Mehta Road, Vile Parle (West), Mumbai, Maharashtra, 400 056, India.ORCID 0000-0003-2160-6653
Sankha BhattacharyaDepartment of Pharmaceutics, School of Pharmacy and Technology Management, SVKM'S NMIMS Deemed-to-be University, Shirpur, Maharashtra, 425405, India.ORCID 0000-0002-0771-9582

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Theranostics, a method that combines targeted therapy and diagnostic imaging, has emerged as a viable route for enhancing cancer treatment, and hybrid nanoparticles (HNPs) are at the forefront of this field. Metallic, polymeric, lipid-based, and silica- based HNPs are studied for targeting and biocompatibility. Using HNPs, chemotherapeutic drugs, small interfering RNA, and therapeutic genes can be given precisely and controlled. This enhances therapeutic efficacy and reduces adverse effects. With fluorescence dyes, MRI contrast agents, and PET tracers, real-time therapy response monitoring is conceivable. A nano platform with therapeutic and diagnostic capabilities holds great promise for personalized medicine and precision oncology. The present study discusses HNPs' biocompatibility, stability, immunogenicity, and long-term biosafety, which are crucial to the clinical translation of cancer theranostics. Further, in this in- -depth investigation, we investigated the design, synthesis, and multifunctional activities of HNPs for use in cancer theranostics.

Indexed as

Antineoplastic AgentsDrug DesignNanoparticlesNeoplasmsTheranostic NanomedicineAnimalsHumansAntineoplastic Agentscancer theranosticsdiagnostic imagingHybrid nanoparticles (HNPs)immunotherapy.precision oncologytargeted therapy

Identifiers

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.