Evidence map›Paper›PMID 40034433›Full record

ArticleResearch square2025

Rational Design of Safer Inorganic Nanoparticles via Mechanistic Modeling-informed Machine Learning.

Joseph Cave, Anne Christiono, Carmine Schiavone, Henry J Pownall, Vittorio Cristini, Daniela I Staquicini, C Jeffrey Brinker, Matthew J Campen, Zhihui Wang, Hien Van Nguyen and 2 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in Research square, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Joseph CaveMathematics in Medicine Program, Department of Medicine, Houston Methodist Research Institute, Houston, TX, USA.
Anne ChristionoDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
Carmine SchiavoneMathematics in Medicine Program, Department of Medicine, Houston Methodist Research Institute, Houston, TX, USA.
Henry J PownallDepartment of Medicine, Houston Methodist, Houston, TX, USA.
Vittorio CristiniMathematics in Medicine Program, Department of Medicine, Houston Methodist Research Institute, Houston, TX, USA.
Daniela I StaquiciniRutgers Cancer Institute, Newark, NJ, USA.
C Jeffrey BrinkerDepartment of Chemical and Biological Engineering, University of New Mexico, Albuquerque, NM, USA.ORCID https://orcid.org/0000-0002-7145-9324
Matthew J CampenCollege of Pharmacy, University of New Mexico, Albuquerque, NM, USA.
Zhihui WangMathematics in Medicine Program, Department of Medicine, Houston Methodist Research Institute, Houston, TX, USA.
Hien Van NguyenDepartment of Electrical and Computer Engineering, University of Houston, Houston, TX, USA.
Achraf NoureddineDepartment of Chemical and Biological Engineering, University of New Mexico, Albuquerque, NM, USA.ORCID https://orcid.org/0000-0001-9530-5963
Prashant DograMathematics in Medicine Program, Department of Medicine, Houston Methodist Research Institute, Houston, TX, USA.ORCID https://orcid.org/0000-0001-6722-7371

Funding

Nanoparticle delivery of miRNA-based therapeutics to overcome clinical challenges in triple negative breast cancerR01CA253865 · NCI · METHODIST HOSPITAL RESEARCH INSTITUTE · PI OZPOLAT, BULENT, WANG, ZHIHUI · 2021 to 2025
$2.0M
Artificial intelligence-integrated mechanistic modeling for rational design of nanoparticles to improve organ targeting and safetyR01EB035545 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Prashant Dogra, Achraf Noureddine · 2024 to 2026
$1.3M
NCI NIH HHS R01 CA253865NIBIB NIH HHS R01 EB035545
6 · The paper itself

Abstract

The safety of inorganic nanoparticles (NPs) remains a critical challenge for their clinical translation. To address this, we developed a machine-learning (ML) framework that predicts NP toxicity both

Indexed as

artificial intelligencecytotoxicitymachine learningmathematical modelingnanoparticlenanotoxicityPBPK

Identifiers

PMID40034433
PMCPMC11875313

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.