Evidence map›Paper›PMID 38384246›Full record

ArticleJournal of biosciences2024

Enhancing access to treatment for Gaucher disease in India: The need for indigenous manufacturing.

Nidhi Patel, Heta Pandya, Ganesh Sangle, Mohua Chakraborty Choudhury

Abstract read
PubMed
In one paragraph

Article in Journal of biosciences, 2024. 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
1.0field-weighted citation impact, top 26% of its field
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, 3 citations in OpenAlex.

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 at 1 institution in 1 country.

Nidhi PatelKashiv Biosciences Pvt Ltd, Ahmedabad, India.
Heta Pandya
Ganesh Sangle
Mohua Chakraborty Choudhury
Centre for Policy Research · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gaucher disease (GD) is a prevalent lysosomal storage disorder (LSD) that significantly impacts individuals' lives. However, the exorbitant prices of GD medications pose a major hurdle in ensuring widespread availability and affordability of treatment in India. The country heavily relies on imported medications, leading to high costs and limited access for many patients. This article aims to address this issue by advocating for the establishment of indigenous manufacturing capabilities for GD medicines in India. Through an examination of the current landscape of GD treatment, including the availability, affordability, and challenges associated with imported medications, this article highlights the urgent need for localized production. By focusing on the potential benefits of indigenous manufacturing, such as reduced costs, increased accessibility, and enhanced availability, this research aims to provide insights and recommendations to policymakers, healthcare professionals, and relevant stakeholders. The findings underscore the importance of developing domestic manufacturing capabilities to address the affordability and accessibility challenges faced by GD patients in India. The research also emphasizes the potential positive impact on the healthcare system, the pharmaceutical industry, and the overall well-being of individuals with GD. Ultimately, this article seeks to stimulate discussions and actions towards creating a sustainable framework for indigenous manufacturing of GD medicines, thereby improving the lives of those affected by this rare and debilitating condition.

Indexed as

Gaucher DiseaseCosts and Cost AnalysisHealth Services AccessibilityHumansIndia

Identifiers

PMID38384246
OpenAlexW4391956352

What OpenQuestion holds

Textmetadata
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.