Stability Analysis Services for Small Nucleic Acid Drugs

Advantages

Proven methodology for consistent results

Highly developed extraction and
detection methods enabling
consistent recovery and eliminating
sources of error

Comprehensive Analysis Results

Degradation analysis of sense, antisense, and modified strands
Degradation curves and metabolite identification

Efficient and Cost-effective Evaluation

Serum or culture conditions to
approximate the in vivo environment
Rapid stability evaluation

Modification Strategies for Enhanced Stability

Customized modifications to
improve stability
AI tools to predict knockdown
efficiency of modified siRNA

Service Information

Through in vitro stability and metabolism assessments in biological matrices (such as serum) or solvents, we identify candidate molecules with higher stability and evaluate their metabolic profiles.

Case Studies

• Optimizing extraction & detection protocols to avoid interference in the extraction process

  Method:

  Three experiments were conducted at three different time points to extract samples in a simulated metabolic environment (serum) and detect the metabolism of candidate molecules.

  Results:

  • The extraction recovery rate was stable across all three experiments (Fig. 1).
  • The optimized extraction process and reagents did not interfere with detection results (Fig. 2).
  • These data demonstrate that the extraction and detection methods are precise and stable, ensuring that subsequent analysis results accurately reflect the actual metabolic conditions of the samples, without being influenced by methodological factors.

  

  
• Performing a comprehensive analysis through detailed metabolic reports of sense/antisense strands

  Method: The metabolism of marketed siRNA drug X (without GalNAc modification) in bovine serum was investigated. Sequence identification and sample residue quantification by LC-MS/MS.

  Results:

  • The antisense strand showed almost no metabolic activity, while the sense strand exhibited significant metabolic activity. After four hours, 60% of the sense strand remained.
  • After four hours, the identified metabolites showed that the antisense strand had a slight N-1 degradation (<1%) on the 3' end, while the sense strand metabolites were primarily N-1/N-2 on the 3'-end.

  

  

  Method: The metabolism of marketed siRNA drug X (with GalNAc modification) in bovine serum was investigated.Sequence identification and sample residue quantification by LC-MS/MS.

  Results:

  • Neither the sense nor the antisense strand exhibited significant metabolic activity. The sense strand also became stable after adding the GalNAc modification at the 3' end, showing no significant metabolic activity.
  • After four hours, the identified metabolites showed that the antisense strand had a slight N-1 degradation (<1%) at the 3' end, while no metabolites were observed for the sense strand, demonstrating that the GalNAc modification enhanced its stability.

  

  
• Comparing the degree of metabolism to efficiently select candidates with longer half-lives and greater stability

  Method: For different modification schemes, the metabolic rate and metabolites in a serum environment were analyzed to select the most stable modification schemes for subsequent optimization and development. This experimental method can also be used to screen different sequences to identify the most stable candidate samples.

  Results:

  • siRNAs with modifications from groups GS1 to GS6 exhibited lower degradation levels and better stability compared to unmodified siRNA (sense strand SS/antisense strand AS).
  • Among these, the GS6 modification scheme demonstrated the lowest degradation level and the highest stability, making it the most optimal modification scheme.

  

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