Evidence map›Paper›PMID 38674402›Full record

ReviewGenes2024

Review of Personalized Medicine and Pharmacogenomics of Anti-Cancer Compounds and Natural Products.

Yalan Zhou, Siqi Peng, Huizhen Wang, Xinyin Cai, Qingzhong Wang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Genes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
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  5. Review
  6. Review
  7. Review
  8. Review
  9. Correlative study ofFrontiers in microbiology · 2026
    Article
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  12. Review
  13. Review
  14. Review
  15. A Systematic Review of Cardio-Metabolic Properties ofAntioxidants (Basel, Switzerland) · 2024
    Review
  16. 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.

Yalan ZhouInstitute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Siqi PengInstitute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Huizhen WangInstitute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Xinyin CaiShanghai R&D Centre for Standardization of Chinese Medicines, Shanghai 202103, China.
Qingzhong WangInstitute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.ORCID 0000-0001-7472-996X

Funding

National Natural Science Foundation of China 31871281
6 · The paper itself

Abstract

In recent years, the FDA has approved numerous anti-cancer drugs that are mutation-based for clinical use. These drugs have improved the precision of treatment and reduced adverse effects and side effects. Personalized therapy is a prominent and hot topic of current medicine and also represents the future direction of development. With the continuous advancements in gene sequencing and high-throughput screening, research and development strategies for personalized clinical drugs have developed rapidly. This review elaborates the recent personalized treatment strategies, which include artificial intelligence, multi-omics analysis, chemical proteomics, and computation-aided drug design. These technologies rely on the molecular classification of diseases, the global signaling network within organisms, and new models for all targets, which significantly support the development of personalized medicine. Meanwhile, we summarize chemical drugs, such as lorlatinib, osimertinib, and other natural products, that deliver personalized therapeutic effects based on genetic mutations. This review also highlights potential challenges in interpreting genetic mutations and combining drugs, while providing new ideas for the development of personalized medicine and pharmacogenomics in cancer study.

Indexed as

Antineoplastic AgentsBiological ProductsNeoplasmsPharmacogeneticsPrecision MedicineHumansMutationAntineoplastic AgentsBiological Productsanticancernatural productspersonalized medicinepersonalized therapypharmacogenomics

Identifiers

PMID38674402
PMCPMC11049652

What OpenQuestion holds

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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 OpenQuestion graph.