Case Studies

AML drug developer selects Teiko for 500+ specimen trial

Teiko 03/21/2025

Goal:

  • Assess dose-dependent pharmacodynamic effects of the drug on AML blasts and immune cells across multiple timepoints
  • Implement a custom gating strategy to distinguish AML blasts and immune cells in whole blood
  • Replace PBMC isolation with TokuKit whole blood fixation to streamline sample collection

Approach with Teiko:

  • Developed a custom 43-marker CyTOF panel, including 5 drug-specific markers associated with the drug’s mechanism of action
  • Processing ~500 whole blood samples across multiple cohorts, dose levels, and validation studies in the Phase 1 trial
  • Runtime for project: Ongoing

Results:

  • Ongoing sample collection and kit distribution are supporting the continued assessment of dose-dependent drug effects across 700+ subsets, including immune cells and AML blasts
  • Developed a custom 43-marker CyTOF panel, incorporating 5 drug-specific markers to track AML blasts and immune cell populations, and designed a gating strategy to distinguish AML subpopulations and immune cells in whole blood
  • Demonstrated high assay reproducibility, with precision tests meeting acceptance criteria for phenotypic populations, functional subsets, and median channel values
  • Optimized the clinical operations workflow using TokuKits, ensuring the drug effect is not lost due to PBMC isolation and enabling dose-dependent drug effect tracking at frequent sampling points after treatment

Who cares?

  • This drug developer reduced the number of specimens collected per patient from three to one while saving ~$200 per specimen by switching from PBMC to TokuKit. With TokuKit on-site sample collection within 30 minutes, they ensured critical drug response windows were captured, avoiding delays in PBMC shipping and processing that could have missed key pharmacodynamic effects.
  • Now, the developer can track both the immune system and AML blast cells from a single sample, simplifying trial logistics and enhancing data quality.