Evidence mapPaperPMID 40357783Full record

ReviewCurrent medicinal chemistry2026

Next-generation Approaches in Targeting Polycystic Ovarian Syndrome: Innovative Strategies.

Pavithra Lakshmi Narayanan, Subalakshmi Sugumar, Rapuru Rushendran, Chitra Vellapandian

Abstract readReview
In one paragraph

Review in Current medicinal chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

4 authors.

Pavithra Lakshmi NarayananDepartment of Pharmacology, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, 603203, Chengalpattu District, Tamil Nadu, India.
Subalakshmi SugumarDepartment of Pharmacology, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, 603203, Chengalpattu District, Tamil Nadu, India.
Rapuru RushendranDepartment of Pharmacology, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, 603203, Chengalpattu District, Tamil Nadu, India.
Chitra VellapandianDepartment of Pharmacology, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, 603203, Chengalpattu District, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder that affects millions of women worldwide and is characterized by ovarian dysfunction, hyperandrogenism, and metabolic abnormalities. The traditional diagnostic and therapeutic approaches often fail to address the multifaceted nature of PCOS. Recent advancements in next-generation sequencing (NGS), bioinformatics, and precision medicine have paved the way for innovative research and therapeutic strategies that promise to revolutionize PCOS management. This review focuses on exploring the genetic and molecular mechanisms of PCOS using innovative methodologies, such as genome-wide association studies (GWAS), transcriptomics, and computational approaches. Integrating big data analytics and machine learning algorithms enhances the predictive accuracy of PCOS diagnoses and treatment outcomes. In addition, the emergence of personalized medicine has enabled tailored therapeutic interventions based on individual genetic profiles and phenotypic expression. Furthermore, we explored the development of novel pharmacological agents and combinational therapies to enhance the understanding of PCOS pathophysiology. These approaches also focus on reducing inflammation, improving insulin sensitivity, and optimizing hormonal balance to achieve optimal health outcomes. The potential of digital health tools, including mobile applications and wearable technologies, to support self-monitoring and patient engagement in PCOS management is also highlighted. In conclusion, the integration of next-generation technologies and innovative research is necessary to transform the field of PCOS diagnosis and treatment, offering hope for more effective and individualized care. These underscore the importance of continued investment in advanced research methodologies and the adoption of personalized therapeutic strategies to address the complexities of PCOS.

Indexed as

Polycystic Ovary SyndromeFemaleGenome-Wide Association StudyHigh-Throughput Nucleotide SequencingHumansPrecision MedicineBioinformaticsinnovative researchmachine learningmolecular docking.polycystic ovarian syndrometherapeutic strategies

Identifiers

PMID40357783
PMCPMC12728523

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.