About Friends

Diagnostics Partnerships Portfolio

Diagnostic tests play a crucial role in developing oncology drugs and determining the best treatment options for cancer patients. It’s important that these tests are reliable and consistent across the industry.

Friends Diagnostics Partnerships Portfolio focuses on standardizing these tests by generating evidence to understand variability, ensuring that different testing methods provide accurate and consistent results for patients.

Digital Pathology Project

Patients rely on accurate and efficient analysis from pathologists to interpret results from routine tests like imaging scans to determine important treatment decisions. Currently, a shortage of pathologists and risk of routine human error poses issues for patients across various cancers, yet Artificial Intelligence (AI) may be able to help address these problems.

Computational and digital pathology uses artificial intelligence (AI) to aid pathologists by providing greater accuracy, reproducibility, and expediency of biomarker assessment. However, whether the AI models provide similar results to one another is unknown.   

Friends’ Digital PATH Project aims to assess the level of variability in digital pathology platforms that analyze HER2 in breast cancer. Understanding the level of variability in outputs from different models that were established using AI can support alignment and is a foundational step forward in applying AI to improve patient outcomes in cancer care.   

ctMoniTR Project

CtDNA, a tumor DNA shed by cancer cells, can be detected in the bloodstream through a blood test. This offers a quick and scientifically valid method for assessing treatment effectiveness and could be linked to long-term outcomes such as overall survival. 

As new treatments rapidly evolve, the clinical trial process can struggle to keep pace. Although detecting and measuring ctDNA can help providers identify treatment effectiveness sooner and more efficiently, it is not yet being used to make regulatory decisions in drug development.

The Friends ctMoniTR project combines data from more than 3,000 patients to show that circulating tumor DNA (ctDNA) can be a reliable early endpoint in cancer clinical trials. Our ctMoniTR Project aims to bridge this gap, establishing ctDNA as an indicator of treatment response faster than if any single organization tried to do so alone.

Real-World Evidence Portfolio

Real-world data and evidence have the potential to provide valuable insights into the real-world performance of cancer treatments and diagnostics, including characterizing use in a broader patient population receiving standard of care. Currently, there is a lack of standardization in analyzing and reporting these data, and traditional clinical trial models do not leverage these findings.

Friends’ Real-World Evidence Portfolio works to align best practices and frameworks when analyzing real-world data. The aim is that by having alignment, real-world data can be used to support the generation of evidence in more diverse populations to inform standard-of-care treatment and long-term safety for patients.