Functional titer assays are crucial for assessing vector potency and guiding transduction MOI in cell engineering. However, methodological inconsistencies, particularly in the cell culture component, have posed challenges for both research and industry applications. This study presents a standardized cell-based lentivirus functional titer assay using orthogonal ddPCR and flow cytometry methods for accurate titer confirmation. HEK293 cells were used for transduction in a 10-day procedure. The cells were transduced with viral vectors at varying MOIs (MOI =0.03 ~6.74) after two passages, with a seeding density at 8e4 cells/cm^{<span style="font-size:10.8333px">2</span>}. Polybrene was used to facilitate transduction at a final concentration of 8 µg/mL in each well. The cells were passaged once before being harvested for ddPCR and flow cytometry analysis.
A dose-response analysis showed a linear correlation between infected cell percentage (CAR⁺%) and MOI within MOI 0.08~ 0.84. Comparison slope of dose-response curve between high (8 × 10⁴ cells/cm²) with low (1 × 10⁴ cells/cm²) seeding densities revealed that higher density resulted in 2-fold greater transduction efficiency. Flow and ddPCR titer results for low seeding density were 5 times lower than titer results from vendor. Meanwhile, Flow titers of high seeding density closely aligned with Vendor's titer (% difference=12%). Notably, ddPCR titers at high seeding density were initially 2-fold higher due to multiple gene integrations but matched well with titer results from vendor (% difference=22%) and Flow results (%difference=10%) after one passage. A strong correlation (R²= 0.99) between ddPCR (VCN= 0.052~0.522) and flow cytometry (CAR⁺%=5.8%~35.5%) confirmed the assay's accuracy. This method was qualified at LCGM with good repeatability (RDP between biological replicate = 0.49%~10.64%, run-to-run variation = 0.12log), intermediate precision (analyst-to-analyst variation CV% = 16%). This robust and standardized method offers a reliable approach to evaluate lentivirus functional titers in cell and gene therapy applications.

Qiaoshi Jiang

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