Evidence map›Paper›PMID 39895194›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2025

Rational Design of Metal-Organic Frameworks for Pancreatic Cancer Therapy: from Machine Learning Screening to In Vivo Efficacy.

Francesca Melle, Dhruv Menon, João Conniot, Jon Ostolaza-Paraiso, Sergio Mercado, Jhenifer Oliveira, Xu Chen, Bárbara B Mendes, João Conde, David Fairen-Jimenez

Abstract read
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. DNA-mimic for Specific Surface Functionalization of Zr-MOFs for Bacterial Targeting.Angewandte Chemie (International ed. in English) · 2026
    Article
  4. Review
  5. Review
  6. Article
  7. Metal-organic frameworks in pharmaceutical research.Pharmaceutical science advances · 2025
    Review
  8. Article
  9. Article
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

10 authors.

Francesca MelleThe Adsorption & Advanced Materials Laboratory (AAML), Department of Chemical Engineering & Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, UK.
Dhruv MenonThe Adsorption & Advanced Materials Laboratory (AAML), Department of Chemical Engineering & Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, UK.
João ConniotNOVA Medical School, Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Lisbon, Portugal.
Jon Ostolaza-ParaisoThe Adsorption & Advanced Materials Laboratory (AAML), Department of Chemical Engineering & Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, UK.
Sergio MercadoThe Adsorption & Advanced Materials Laboratory (AAML), Department of Chemical Engineering & Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, UK.
Jhenifer OliveiraNOVA Medical School, Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Lisbon, Portugal.
Xu ChenThe Adsorption & Advanced Materials Laboratory (AAML), Department of Chemical Engineering & Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, UK.
Bárbara B MendesNOVA Medical School, Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Lisbon, Portugal.
João CondeNOVA Medical School, Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Lisbon, Portugal.
David Fairen-JimenezThe Adsorption & Advanced Materials Laboratory (AAML), Department of Chemical Engineering & Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, UK.ORCID https://orcid.org/0000-0002-5013-1194

Funding

Engineering and Physical Sciences Research Council EP/S009000/1Engineering and Physical Sciences Research Council EP/S022953/1EPSRC EP/S009000/1EPSRC EP/S022953/1European Research CouncilFCT - Fundação Ciência e a Tecnologia LISBOA2030-FEDER-00862500-14998FCT - Fundação Ciência e a Tecnologia UID/04923HORIZON EUROPE European Research Council ERC-2016-COG 726380HORIZON EUROPE European Research Council ERC-StG-2019-848325
6 · The paper itself

Abstract

Despite improvements in cancer survival rates, metastatic and surgery-resistant cancers, such as pancreatic cancer, remain challenging, with poor prognoses and limited treatment options. Enhancing drug bioavailability in tumors, while minimizing off-target effects, is crucial. Metal-organic frameworks (MOFs) have emerged as promising drug delivery vehicles owing to their high loading capacity, biocompatibility, and functional tunability. However, the vast chemical diversity of MOFs complicates the rational design of biocompatible materials. This study employed machine learning and molecular simulations to identify MOFs suitable for encapsulating gemcitabine, paclitaxel, and SN-38, and identified PCN-222 as an optimal candidate. Following drug loading, MOF formulations are improved for colloidal stability and biocompatibility. In vitro studies on pancreatic cancer cell lines have shown high biocompatibility, cellular internalization, and delayed drug release. Long-term stability tests demonstrated a consistent performance over 12 months. In vivo studies in pancreatic tumor-bearing mice revealed that paclitaxel-loaded PCN-222, particularly with a hydrogel for local administration, significantly reduced metastatic spread and tumor growth compared to the free drug. These findings underscore the potential of PCN-222 as an effective drug delivery system for the treatment of hard-to-treat cancers.

Indexed as

Antineoplastic AgentsDrug CarriersMachine LearningMetal-Organic FrameworksPancreatic NeoplasmsAnimalsCell Line, TumorDeoxycytidineDrug LiberationGemcitabineHumansIrinotecanMicePaclitaxelAntineoplastic AgentsDeoxycytidineDrug CarriersGemcitabineIrinotecanMetal-Organic FrameworksPaclitaxeldrug deliverymachine learningmetal–organic frameworkspancreatic cancerporous materials

Identifiers

PMID39895194
PMCPMC12747470

What OpenQuestion holds

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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.