Applications and challenges of utilizing digital pathology and AI-enabled workflows in clinical trials.

This is a comprehensive review on current utilization and challenges of digital pathology adoption in clinical trials and aims to provide a broad view on its impact on pathology review processes in clinical trials. In addition, the review delves into the integration of genomics, AI, image analysis, radiology, and advanced computational pathology, to propose measures to enhance clinical trial outcomes.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 It provides an overview of current pathology review practices in clinical trials and unique advantages digital pathology adoption can offer.
• 2 The key areas including existing workflows, use case scenarios in different disease areas in clinical trials, including but not limited to patient identification and pre-screening, and regulatory aspects have been described with relevance.
• 3 In addition, the review delves into the integration of genomics, AI, image analysis, radiology, and advanced computational pathology, to propose measures to enhance clinical trial outcomes.

Understanding this could lead to better treatments, improved diagnostics, or a deeper grasp of how the human body works — benefiting patient care globally.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source: