The complexity of the tumor microenvironment represents a significant challenge to the personalized medicine movement in the field of oncology. While genetic and genomic analyses enable an understanding of the patient’s genotype, this does not necessarily translate to active tumor microenvironment expression – phenomics – through which pharmacodynamic pathways are modulated by targeted therapies. Similarly, while single biomarker immunohistochemistry (IHC) can effectively quantify expression of a particular biomarker, it fails to evaluate the entire picture of the tumor microenvironment, where a myriad of potentially confounding factors exists to distort the causal relationship between expression of a single marker and treatment response.Enter context-based analysis of biomarker expression – quantitative, multiplex IHC technology leveraging “big data” capabilities to overcome the inherent limitations of existing diagnostic techniques and more precisely assess the tumor microenvironment. Applied as a companion diagnostic (CDx), quantitative IHC or IF (qIHC/IF) using image analysis (IA) technology represents a potentially paradigm-shifting approach to predict patient response to oncologics and thus bring the movement of personalized medicine to fruition. Read More
Topics: image analysis, personalized medicine, biomarker, immuno-oncology, tissue diagnostics, companion diagnostics, tissue biomarkers, diagnostics, diagnostic test, precision medicine, biomarker signature
As healthcare continues its transition towards precision medicine, physicians are eager to maximize both the quantity and quality of data obtained from their patients’ tissue samples. In the current “one drug, one test” paradigm, physicians struggle to balance the number of tests required to make a treatment decision with the limited amount of tissue that is available. Further complicating treatment decisions is the use of imperfect biomarkers associated with targeted therapies, as the patients who are identified to be ideal candidates for a targeted therapy respond only some of the time while patients who are not expected to respond do. This dilemma is of great concern for those who are responsible for paying for these expensive therapies - payers and patients – who would like to avoid unnecessary expenses for drugs that may not work and possibly cause debilitating side effects. Of course, of even greater concern is helping the patient identify the best therapeutic option that allows them the best opportunity to treat their disease and maximize their quality and quantity of life.Read More
Personalized v. Standard Care
Why do Pharma companies care about personalized medicine given that this might limit the population for which their drug is approved?
Low response rates to therapy and lack of patient benefit compared to the standard of care can put success of a clinical trial and overall drug development at risk. Therefore pharma companies are invested in diagnostic programs to:
- select the right patients for their drug
- minimize the risk of drug failure
- get drugs to market faster
One way to develop prognostic and predictive tests in oncology is through the use of genomic biomarkers. And as more diagnostics companies are recognizing the potential benefits of this method, we’re seeing an increase in the number of companion diagnostic tests relying on gene-based biomarkers. Another reason for this continued trend towards personalized medicine is the continually decreasing costs of whole-genome sequencing.Read More
Biomarkers are critical to pharmaceutical and diagnostic companies developing novel therapies and diagnostics for oncology. Being able to discover and validate the best biomarkers forms the basis of any successful cancer diagnostic test.
Types of cancer diagnostic tests
• Companion diagnostics for new therapies – this type of diagnostic test is used for patient stratification in clinical trials. Successful companion diagnostics at this stage of drug development can increase the medical value of a therapy by selecting for responders or excluding patients at risk for severe side effects. Thus, they can facilitate regulatory approval, while keeping clinical trials smaller and cost effective.
• Companion diagnostics for existing drugs – this type of diagnostic test is developed after a cancer therapy has already been on the market in order to better select the right patients for the therapy. Successful companion diagnostics for existing drugs aim to reduce overall healthcare costs and the experience of unnecessary side effects by identifying patients that will benefit from treatment.Read More