Improving international research with clinical specimens: 5 achievable objectives

Area of Science:

• Biomedical Research
• Translational Science
• Clinical Sample Utilization

Background:

• Translational research demands vast quantities of clinical samples (blood, tissue) for genomics, proteomics, and metabolomics.
• Significant international investment in sample collection, storage, and distribution has not met researcher needs.
• Researchers face obstacles including lack of access, poor sample quality, and inadequate controls, hindering progress in disease and biomarker studies.

Purpose of the Study:

• To identify and address five major challenges hindering the effective use of clinical samples in translational research.
• To propose near-term objectives for improving sample accessibility, quality, and utility.
• To emphasize the critical role of high-quality, standardized, and accessible samples for the future of proteomics.

Main Methods:

• The perspective outlines five key challenges: defining biobanking needs, increasing use of standard operating procedures (SOPs), mapping interobserver diagnostic differences, identifying natural internal protein controls, and redefining the clinical sample paradigm through public partnerships.
• The approach involves exploring potential solutions and tools currently available to achieve these objectives within a 5-year timeframe.

Main Results:

• The study identifies critical areas for improvement in the clinical sample pipeline.
• It proposes actionable objectives to overcome existing barriers to sample utilization.
• The findings highlight the feasibility of achieving significant improvements within five years with available tools.

Conclusions:

• Overcoming challenges in clinical sample access, standardization, annotation, and sharing is essential for advancing translational research and proteomics.
• Establishing partnerships with the public and implementing standardized protocols are key to redefining the clinical sample paradigm.
• The future of scientific discovery, particularly in proteomics, is contingent upon the availability of high-quality, well-annotated clinical samples.