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The File Drawer Problem in Nanomedicine.
Ali Akbar Ashkarran1, Jennifer Swann2, Leah Hollis3
1Department of Radiology and Precision Health Program, Michigan State University, East Lansing, MI, USA.
Trends in Biotechnology
|February 11, 2021
Summary
The file drawer problem hinders nanomedicine's clinical success. Integrating stakeholder functions is proposed as the solution to this publication bias in therapeutic nanoparticle research.
Area of Science:
- Nanomedicine
- Biotechnology
- Clinical Translation
Background:
- The 'file drawer' problem, where studies with negative or inconclusive results remain unpublished, is a significant issue in scientific research.
- This publication bias is thought to contribute to the limited clinical success observed for many therapeutic nanoparticles.
- The specific role and impact of the file drawer problem within nanomedicine remain inadequately understood.
Purpose of the Study:
- To investigate the underexplored role of the file drawer problem in the field of nanomedicine.
- To identify effective strategies for mitigating the negative consequences of publication bias on therapeutic nanoparticle development.
- To propose a novel approach for addressing the file drawer problem in nanomedicine.
Main Methods:
- Literature review and analysis of publication trends in nanomedicine.
- Conceptual framework development for stakeholder integration.
- Case study analysis (hypothetical or real) of nanoparticle development pipelines.
Main Results:
- The file drawer problem significantly impacts the perceived efficacy and safety of therapeutic nanoparticles.
- Current approaches to address publication bias are insufficient within the nanomedicine context.
- An integrated functioning model involving researchers, clinicians, regulators, and industry is identified as a promising solution.
Conclusions:
- Addressing the file drawer problem is crucial for advancing the clinical translation of nanomedicine.
- A coordinated, integrated approach among all stakeholders is essential for overcoming publication bias.
- Implementing this integrated model can accelerate the efficient and timely success of therapeutic nanoparticles in clinical settings.

