Early Detection of Drug Resistance
Resistance to chemotherapy is one of the serious problems that currently clinicians and researchers are facing in cancer treatment. It can arise as the result of one or more mutations in the genome of the cancer cells that give it the advantage of being able to evade the effects of a drug. Detecting these mutations is a crucial step to improve the efficacy of many treatments. Our unique and accurate methodologies and algorithms can determine the mutation locations and their associated drug sensitivity or responsiveness to many therapeutic drugs that are used in the clinical treatment, including mutations in BRAF, KRAS, ALK and other genes that affect treatment by Sorafenib, Imatinib and many other drugs.
Acurate Cancer Diagnosis
Our analysis uses a comprehensive set of algorithms for research or clinical grade next-generation sequencing to assess routine cancer specimens and detect gene alterations. The analysis is performed by a cluster of cloud-based supercomputers operating in a secure and trusted environment, with quick turnaround time to determine the specific tumor classifications and the potential prognoses. The test results are delivered to the clinician and the end-user through a user-friendly, interpretive reporting system that serves as a reference for the patient's genomic health, disease diagnosis, prognosis and possible targeted therapies
Personalized Treatment Strategies
Clinical trials are widely used to predict the effectiveness of a
specific drug across a patient population. However, an individual patient¹s
reaction to a drug, dosing regimen, or drug toxicity may not follow the
prediction made for the general patient population. The use of more complicated
DNA testing methods, such as whole exome sequencing, can reveal a patient’s germline and somatic mutations. Knowledge of these mutations can be used to identify disease susceptibility, treatment effectiveness or preferred treatment approaches for a specific patient. Using our unique computational approach, we are well positioned to take on this challenge and help clinicians and researchers plan treatment strategies and translational research.
specific drug across a patient population. However, an individual patient¹s
reaction to a drug, dosing regimen, or drug toxicity may not follow the
prediction made for the general patient population. The use of more complicated
DNA testing methods, such as whole exome sequencing, can reveal a patient’s germline and somatic mutations. Knowledge of these mutations can be used to identify disease susceptibility, treatment effectiveness or preferred treatment approaches for a specific patient. Using our unique computational approach, we are well positioned to take on this challenge and help clinicians and researchers plan treatment strategies and translational research.