Sample-attribute-based selection strategies for AAV %Full determination
Reliable AAV percent-full (%Full) analysis starts with understanding the sample.
From crude harvests to purified drug substance, differences in sample purity and composition can influence analytical performance and data interpretation.
In our latest whitepaper, Samsung Biologics experts compare analytical approaches across AAV development, sharing key findings on:
Method selection: Applying ddPCR to crude harvests and SEC-MALS or mass photometry to suitable purified samples.
AUC comparability: Orthogonal methods showed results within 10% relative deviation of AUC in final drug substance testing.
Data reliability: Indirect VG/VP ratios can introduce variability in %Full estimates.
Read the full whitepaper for a closer look at the implications for measurement reliability, throughput, and sample requirements across AAV development.
Reliable AAV percent-full (%Full) analysis starts with understanding the sample.
From crude harvests to purified drug substance, differences in sample purity and composition can influence analytical performance and data interpretation.
In our latest whitepaper, Samsung Biologics experts compare analytical approaches across AAV development, sharing key findings on:
- Method selection: Applying ddPCR to crude harvests and SEC-MALS or mass photometry to suitable purified samples.
- AUC comparability: Orthogonal methods showed results within 10% relative deviation of AUC in final drug substance testing.
- Data reliability: Indirect VG/VP ratios can introduce variability in %Full estimates.
Read the full whitepaper for a closer look at the implications for measurement reliability, throughput, and sample requirements across AAV development.
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