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Patient Selection Testing
Cancer cells proliferate through the activation and interaction of complex
biological pathways, stimulated by both extracellular signals and intracellular
changes.
The current methods of classifying different types of cancer by the tissue of
origin (e.g., breast cancer or lung cancer), are relatively crude and imprecise,
and better methods of categorizing an individual's cancer or tumor are possible.
For instance, tumor samples from different lung cancer patients may appear to be
similar by CT scan or histopathology, but very different biological processes
can be responsible for tumor cell proliferation at the molecular level.
To cure a patient's cancer, or to control it and limit its progression, healthcare
providers must understand these complex processes, and determine which pathways
have been activated and are driving cancer cell growth. New molecular methods and
analytical techniques are being developed to provide this information. These new
technologies hold the potential to revolutionize cancer diagnosis and treatment.
Predictive tests able to measure cancer drug targets in their activated state
(i.e., those target proteins actively involved in the disease process or mechanism
affected by the drug) will be especially valuable. For example, different members
of the EGFR/HER receptor family are active in many types of cancer, but not in all
patients with a particular type of cancer. The ability to detect activated drug
targets, such as EGFR/HER receptor complexes or dimers, is essential to understanding whether
particular drugs are likely to be effective.
Incorporating VeraTag™ assays in the clinical development of targeted
cancer therapeutics offers the following potential benefits:
- Selection of patient populations most likely to respond to particular targeted cancer therapies
- Fewer patients needed for a clinical trial and resultant cost savings
- Shorter clinical trials and resultant reduced costs
- Decrease in undesirable side effects
- Optimization of clinical efficacy outcomes
- Increased probability of regulatory approval
- Reduced time to market and resultant economic benefit
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