Evidence map›Paper›PMID 40908691›Full record

ReviewAnti-cancer agents in medicinal chemistry2026

Microbial-Derived Anti-Cancer Compounds: Advances in Drug Discovery, Bioengineering, and Therapeutic Applications.

Ekta Tyagi, Divya Jain, Rajabrata Bhuyan, Anand Prakash

Abstract readReview
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In one paragraph

Review in Anti-cancer agents in medicinal chemistry, 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
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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

4 authors.

Ekta TyagiDepartment of Bioscience and Biotechnology, Banasthali Vidyapith, Rajasthan-304022, India.
Divya JainDepartment of Microbiology, School of Applied and Life Sciences, Uttaranchal University, Dehradun-248007, Uttarakhand, India.
Rajabrata BhuyanDepartment of Bioscience and Biotechnology, Banasthali Vidyapith, Rajasthan-304022, India.
Anand PrakashDepartment of Bioscience and Biotechnology, Banasthali Vidyapith, Rajasthan-304022, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMicrobial metabolites represent a valuable source of bioactive compounds with promising anticancer properties. However, conventional drug discovery approaches are time-intensive and resource-demanding.

methodsRecent developments in artificial intelligence (AI), machine learning (ML), molecular docking, and quantitative structure-activity relationship (QSAR) modeling have been examined for their role in the identification and optimization of microbial metabolites.

resultsAI-driven approaches have significantly enhanced compound screening and prediction of therapeutic efficacy. Nanocarrier-based drug delivery systems have improved the bioavailability, specificity, and stability of microbial metabolites while minimizing systemic toxicity. Despite these advancements, challenges remain in clinical translation due to the lack of DISCUSSION: This review highlights the integration of advanced computational tools and nanotechnology in accelerating the discovery and delivery of microbial-derived anticancer agents.

conclusionFuture directions should focus on integrating AI with synthetic biology to engineer microbial strains capable of producing enhanced bioactive compounds. Additionally, leveraging nanotechnology could refine targeted delivery mechanisms. A deeper understanding of molecular pathways and drug resistance mechanisms is essential to support the development of combination therapies. Overall, microbialderived compounds hold substantial potential in advancing precision oncology.

Indexed as

Antineoplastic AgentsBacteriaBioengineeringDrug DiscoveryNeoplasmsAnimalsArtificial IntelligenceCell ProliferationHumansQuantitative Structure-Activity RelationshipAntineoplastic AgentsAI-driven drug discoveryCRISPR-Cas9Genome miningMicrobial anti-cancer compoundsmicrobial metabolitesNanotechnology drug delivery

Identifiers

PMID40908691

What Socratic holds

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Registered trials

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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.