Evidence map›Paper›PMID 41971099›Full record

ArticleFrontiers in pharmacology2026

Development and pharmacokinetic evaluation of granisetron hydrochloride buccal tablets for optimized chemotherapy-induced nausea and vomiting (CINV) relief.

Chandrashekar Thalluri, Sarad Pawar Naik Bukke, Malliukarjun Vasam, Jharna Medhi, Ananda Kumar Chettupalli, Bharath Kumar Mamilla Mugaiahgari, Bayapa Reddy Narapureddy, Vinod Kumar Yata, Ravi Chander Thatipelli

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In one paragraph

Article in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

9 authors.

Chandrashekar ThalluriFaculty of Pharmaceutical Science, Assam down town University (AdtU), Guwahati, Assam, India.
Sarad Pawar Naik BukkeDepartment of Pharmaceutics and Pharmaceutical Technology, Kampala International University, Western Campus, Kampala, Uganda.
Malliukarjun VasamDepartment of Pharmaceutics, Omega College of Pharmacy, Osmania University, Edulabad, Hyderabad, Telangana, India.
Jharna MedhiFaculty of Pharmaceutical Science, Assam down town University (AdtU), Guwahati, Assam, India.
Ananda Kumar ChettupalliDepartment of Pharmacy, School of Medical and Allied Sciences, Galgotias University, Noida, Uttar Pradesh, India.
Bharath Kumar Mamilla MugaiahgariDepartment of Emergency Medical Services, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia.
Bayapa Reddy NarapureddyDepartment of Public Health, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia.
Vinod Kumar YataDepartment of Pharmacology, School of Allied and Healthcare Sciences, Malla Reddy University, Hyderabad, Telangana, India.
Ravi Chander ThatipelliDepartment of Pharmaceutics, Vaagdevi Pharmacy College, Warangal, Telangana, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Chemotherapy-induced nausea and vomiting (CINV) limits treatment adherence; this study aimed to develop optimized Granisetron hydrochloride buccal tablets to improve therapeutic performance and bioavailability. Methods: Tablets were prepared by direct compression and optimized using response surface methodology with HPMC K4M (X Results: No drug-excipient interactions were observed. The optimized formulation (F3; 50 mg HPMC K4M and 15 mg carbomer 934P) showed adequate mucoadhesion (8.25 ± 0.12 g), prolonged release (t Discussion: The optimized buccal system provides controlled release and enhanced pharmacokinetic performance, suggesting a promising alternative approach for effective CINV management.

Indexed as

chemotherapy-induced nausea and vomiting (CINV)DD solver and controlled releasegranisetron hydrochloridemucoadhesive polymersresponse surface methodology

Identifiers

PMID41971099
PMCPMC13062749

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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 OpenQuestion graph.