Transforming Cancer Nanotechnology Data Analysis and User Experience. Part I: Current Challenges and Solutions Provided by caNanoLab.

Abstract

Cancer nanotechnologies have the potential to revolutionize cancer diagnosis and treatment; however, their complexity poses challenges to data analysis and knowledge sharing. caNanoLab, a dedicated cancer nanotechnology data-sharing portal, has emerged as a valuable resource for researchers in this field. However, to fully utilize the wealth of data available in caNanoLab, there is a need for real-time descriptive statistical presentation and an optimized user experience. Herein, we provide an overview of cancer nanotechnologies and federally funded efforts to create data repositories, aiming to improve information flow and data sharing among researchers in the cancer nanotechnology field. We use caNanoLab as a case study to analyze the challenges in this area and highlight how caNanoLab addresses them. We also identify gaps and explore the potential of Large Language Models (LLMs) to improve user experience. A more detailed analysis of LLM and their applications to caNanoLab is provided in the second part of this review. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies.