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R&D productivity and product lifecycle needs

R&D productivity and product lifecycle needs

R&D productivity and product lifecycle needs

R&D productivity and product lifecycle needs

Featured on the cover of Nature

Results from the first 100 patients in the Cancer Research UK-funded TRACERx study (Tracking Cancer Evolution Through Therapy [Rx]) demonstrated that an early version of the Signatera (RUO) technology was able to:1

 

Detect residual disease and measure tumor response to treatment in patients with early-stage non-small cell lung cancer (NSCLC)

Predict recurrence post-surgery with a lead time of up to 347 days (mean = 132 days; median = 70 days) before imaging confirmation

 

Adapted from Figure 4h and 4f in Abbosh C. et al. Nature 545, 446–451. (2017)


93% sensitivity for early relapse detection

An early version of Signatera (RUO) produced no false positives in the control group1

 

 

The potential of ctDNA analysis in predicting relapse has also been demonstrated through multiple research studies across a number of other solid tumors (colon, breast, ovarian, bladder).2,3,4,5

 

 

Expand claims and improve pipeline productivity

We believe the Signatera (RUO) technology has the potential (after further research) to:

  • Extend effective treatment by enabling early initiation of therapy and expand labels for marketed products
  • Increase probability of trial success and facilitate earlier “go/no-go” decisions for pipeline products

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References

  1. Abbosh C. et al. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature 545, 446–451. (2017)
  2. Tie J. et al. Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with stage II colon cancer. Science Translational Medicine 8, 346ra92. (2016)
  3. Garcia-Murillas I. et al. Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Science Translational Medicine 7, 302ra133. (2015)
  4. Pereira E. et al. Personalized Circulating tumor DNA biomarkers dynamically predict treatment response and survival in gynecologic cancers. PLoS ONE 10, e0145754. (2015)
  5. Birkenkamp-Demtröder K. et al. Genomic alterations in liquid biopsies from patients with bladder cancer. European Urology 70, 75-82. (2016)
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