Objective:

To discuss the development and validation challenges of nucleic acid aptamers for use in molecular diagnostics.

Approach:

• Aptamer Development: Aptamers are developed using systematic evolution of ligands by exponential enrichment (SELEX), which involves isolating binding sequences from a large library.
• New Selection Methods: Newer methods like microfluidic platforms, nuclease-assisted techniques, and hydrogel systems aim to improve selection speed and performance.
• AI and Machine Learning: Artificial intelligence and machine learning are utilized to predict aptamer structures and analyze datasets.
• Validation Requirements: Aptamers must undergo rigorous validation, including structure confirmation and performance testing in clinically relevant samples.
• Diagnostic Platform Components: Aptamer-based diagnostics typically include an aptamer, a reporting system, and signal amplification methods.

Key Findings:

• Aptamers can bind a variety of targets and offer advantages over antibodies, such as chemical synthesis and stability.
• Clinical translation of aptamers is limited due to issues like nonspecific binding and susceptibility to degradation.
• Rigorous validation is required for aptamer-based tests to meet the standards of existing diagnostic technologies.

Limitations:

• Aptamers may change shape or bind nonspecifically in complex biological samples.
• Their performance can be influenced by environmental factors such as temperature and pH.
• Limited routine clinical use of developed aptamers despite thousands being created.

Sources:

• Signal Transduction and Targeted Therapy