Evidence map›Paper›PMID 42693244›Full record

ReviewJournal of neuro-oncology2026

Integrating ex vivo platforms with AI to guide glioblastoma treatment.

Mainak Bardhan, Samanta Paul, Sirjana Pun, Manish Raj Aryal, Pier Paolo Claudio, Jason Binder, Riccardo Barrile, Daniel A Pomeranz Krummel

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of neuro-oncology, 2026. 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

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

8 authors.

Mainak Bardhan *The Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA.ORCID http://orcid.org/0000-0002-4106-409X
Samanta Paul *Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH, USA.ORCID http://orcid.org/0009-0008-1834-2849
Sirjana Pun *Department of Neurology, Tufts Medical Center, Boston, MA, USA.ORCID http://orcid.org/0000-0002-2090-8804
Manish Raj AryalDepartment of Mechanical Engineering, University of Cincinnati, Cincinnati, OH, USA.ORCID http://orcid.org/0000-0002-0894-0182
Pier Paolo ClaudioDepartment of Pharmacology & Toxicology, University of Mississippi Medical Center, Jackson, MS, USA.ORCID http://orcid.org/0000-0001-7790-1622
Jason BinderEmber Health Inc, Summerfield, NC, USA.ORCID http://orcid.org/0009-0003-9813-9966
Riccardo BarrileDepartment of Biomedical Engineering, University of Cincinnati, Cincinnati, OH, USA.ORCID http://orcid.org/0000-0002-7301-3959
Daniel A Pomeranz KrummelDepartment of Neurosurgery, Tufts Medical Center, Boston, MA, USA. daniel.krummel@tuftsmedicalcenter.org.ORCID http://orcid.org/0000-0003-3928-0786

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeEx vivo platforms can rapidly and cost-effectively screen patient-derived tumor cells or tissue. Artificial intelligence (AI) algorithms can search and identify patterns in large datasets and provide predictions. This review focuses on integrating microphysiological platforms with AI to inform physician and patient decision-making. METHODS AND

resultsCombining efficacy, safety, and pharmacology results from drug screens with the output of extensive AI searches can yield insights to guide physician and patient decision-making and potentially improve a patient's prognosis. We detail ex vivo platforms at different stages of development that represent the diversity of approaches: a microphysiological system and a high-throughput screen that assesses drug cytotoxicity in both bulk and drug-tolerant tumor cells. We review AI approaches that can enhance the utility of microphysiological platforms.

conclusionIntegrating emerging microphysiological platforms with AI is expected to significantly impact physician and patient choice of treatment.

Indexed as

Artificial IntelligenceBrain NeoplasmsGlioblastomaPrecision MedicineAnimalsAntineoplastic AgentsHumansMicrophysiological SystemsAntineoplastic AgentsArtificial IntelligenceBrain tumorFunctional precision medicineGlioblastomaMicrophysiological systemsPersonalized medicine

Identifiers

PMID42693244

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.