How a vision of bias-free cancer research
can help you see the future.
At Epic Sciences, we develop clinical solutions that accelerate drug development, and provide valuable insights into the dynamics of cancer growth, evolution and heterogeneity. In fact, Epic Sciences has the world’s leading pipeline of personalized, predictive and proven tests to guide therapy selection across the most impactful drug classes in oncology, including Epic's AR-V7 CTC test — the world’s first predictive liquid biopsy test for metastatic prostate cancer.
No cell left behind™.
Epic was able to achieve these singular advances because we chose a research road less traveled — a bias-free approach that looks at all the cells in a blood sample and thus sees those rare cells that others miss. That insight leads to a proprietary rare-cell detection platform so potent and precise that it can see, identify and characterize all the circulating tumor cells (CTCs) in a sample, and link their response/resistance to a panoply of drug classes. So that doctors can better understand their patient’s cancer and choose with the greatest certainty the drug or combination of therapies that will work best.
In addition to spotting one rare cell amid 50 million normal ones, Epic's engine can also see small and apoptotic cells, epithelial to mesenchymal transition cells and CTC clusters. After analyzing individual CTCs for phenotypic and genomic biomarkers, we link single-cell or aggregated subclonal populations to pharmacodynamic data and, most important, to patient outcomes.
The power of seeing in real time.
While analyzing CTCs as a proxy for a patient's entire metastatic burden, we are the only company in the blood-based testing domain that preserves all the white blood cells in the same condition to better understand what the immune system is doing in real time. Thus we can see, simultaneously, what is driving patterns of response to critical drug classes such as PARP inhibitors and Checkpoint inhibitors.
Poised for the future.
Impelled by bias-free research and best-of-class technology, we are well positioned to help companies expedite trials, reduce time-to-market and explore new opportunities. Our technology platform is remarkably robust. Thus, although our rare-cell detection platform has primarily been focused on prostate cancer, we're now extending its application into breast, lung and bladder cancer. In fact, there's no telling where the science may lead. So we look forward to discussing your present needs, hearing your vision for the future, and helping you get there.
Clinical Trials
Epic Sciences is currently involved in over 60 active clinical trials that aim to evaluate CTCs in a number of different cancer indications. We also participate in research collaborations that allow us to better understand metastatic disease heterogeneity across multiple disease indications and therapeutic settings. Epic Sciences works closely with biotech and pharmaceutical companies around the world as well as academic partners who are interested in integrating CTCs into clinical trials as observational or predictive biomarkers. It’s all about developing diagnostic assays that can empower precision medicine.
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Every time Epic’s AR-V7 test is administered the healthcare system saves about $15,000 per year of life extended. In other words approximately $7,000 to $9,000 per patient tested.
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Of the roughly 30 million cells in a typical blood sample, about 5 are cancer cells on their way to form tumors elsewhere in the body. Modern cancer diagnostics technology can't see them.
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We spend about $100 billion a year on cancer drugs. But because we’re not matching the right drug to the right patient and their disease in a personalized way, about 3/4ths of that drug spend is wasted.
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The Epic approach answers a critical question for a doctor: When is a patient resistant? By answering that question accurately and precisely we increase patient life and save the system money at the same time.
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Today, Epic Sciences is embedded in clinical trials with 48 leading producers of oncology drugs and 35 of the top academic cancer hospitals.
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It takes only 7 minutes to acquire an entire image of 6 million stained cells on a 1 x 3 slide. Then that image, which is about 20GB of data, gets sent up to the cloud where the algorithms run and find the rare events in about 2 more minutes.