Evidence map›Paper›PMID 39503808›Full record

ReviewBlood research2024

Recent advances in and applications of ex vivo drug sensitivity analysis for blood cancers.

Haeryung Lee, Nahee Ko, Sujin Namgoong, Seunghyok Ham, Jamin Koo

Abstract readReview
In one paragraph

Review in Blood research, 2024. 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. Article
  2. Review
  3. Progression of primary mediastinal T-cell lymphoma to a multicentric form in a young dog.The Canadian veterinary journal = La revue veterinaire canadienne · 2026
    Article
  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

5 authors.

Haeryung Lee *Department of Chemical Engineering, Hongik University, Seoul, 04066, Republic of Korea.
Nahee Ko *Department of Chemical Engineering, Hongik University, Seoul, 04066, Republic of Korea.
Sujin Namgoong *Department of Chemical Engineering, Hongik University, Seoul, 04066, Republic of Korea.
Seunghyok HamImpriMedKorea, Inc., Seoul, 03920, Republic of Korea.
Jamin KooDepartment of Chemical Engineering, Hongik University, Seoul, 04066, Republic of Korea. jaminkoo@alumni.stanford.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blood cancers, including leukemia, multiple myeloma, and lymphoma, pose significant challenges owing to their heterogeneous nature and the limitations of traditional treatments. Precision medicine has emerged as a transformative approach that offers tailored therapeutic strategies based on individual patient profiles. Ex vivo drug sensitivity analysis is central to this advancement, which enables testing of patient-derived cancer cells against a panel of therapeutic agents to predict clinical responses. This review provides a comprehensive overview of the latest advancements in ex vivo drug sensitivity analyses and their application in blood cancers. We discuss the development of more comprehensive drug response metrics and the evaluation of drug combinations to identify synergistic interactions. Additionally, we present evaluation of the advanced therapeutics such as antibody-drug conjugates using ex vivo assays. This review describes the critical role of ex vivo drug sensitivity analyses in advancing precision medicine by examining technological innovations and clinical applications. Ultimately, these innovations are paving the way for more effective and individualized treatments, improving patient outcomes, and establishing new standards for the management of blood cancers.

Indexed as

Blood cancersDrug sensitivityMachine learningPrecision medicinePrognosis

Identifiers

PMID39503808
PMCPMC11541977

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.