Dr. Enrique Jacome |
In the not so distant future, Dr. Beim predicts things will be very different for women who struggle with infertility. The pairing of "big data" analytics with genomics is helping Celmatix decipher the genetic drivers of infertility and usher in an era of personalized reproductive medicine by determining which treatments work best for individuals and developing targeted therapies and treatment plans, something that is being done in cancer treatment already.
Celmatix uses big data and the power of machine learning analytics to interpret personalized clinical data, such as hormone levels and age, to understand how specific patients compare to millions of other women with similar conditions. By pairing these analytics with the world's first whole genome sequences of women with unexplained infertility and premature menopause, Celmatix is paving the way for personalized treatments and recommendations.
"We're here to celebrate Bob Edwards' dream, and the conviction that it's possible to overcome infertility," said Dr. Beim. "This is a very exciting time for reproductive medicine. Scientists are helping women extend their biological lifespan through gamete and embryo preservation, and the majority of couples who are able to persist with fertility treatments such as IVF achieve the goal of starting a family."
"But challenges still remain," she adds. "The people who are least likely to benefit from current treatments often end up in the system for the longest, with round after round of failed cycles. And even people who succeed often have to go through several failed treatment cycles until physicians determine what finally works through a sequential process of trial and failure."
Dr. Beim says the statistics are compelling: 68% of IVF treatment cycles in women under 40 do not result in a live birth. Of 7.3 million American women with infertility problems, about 40% pursue treatment, while the other 60% avoid what they fear will be an expensive and emotionally taxing process. And, infertility is a global issue. Approximately 56% of assisted reproductive technology (ART) procedures are performed in Europe. In addition to the large European market, roughly 50 million couples in China and India are currently seeking infertility treatment.
However, she says, change is on the horizon. Cancer patients are already benefiting from the use of targeted therapies and companion diagnostics, and the time is ripe for the reproductive medicine field to start leveraging these powerful personalized paradigms. The cost of DNA sequencing and data storage is plummeting and there is widespread adoption of electronic medical records, which not only help collect big data and assist in the development of bio repositories but store a valuable body of personal phenotypic data that can help shape/direct individualized treatment when evaluated through sophisticated analytics.
"Look at what has happened in the 12 short years since the first genome was sequenced," says Dr. Beim. "We now have 30,000 genomes sequenced, and we've all heard that the $1000 genome is just around the corner. But reproductive medicine faces unique challenge, and several pieces of the puzzle need to come together before we solve the riddle of infertility and reduce the 'noise' in our datasets to simplify the problem."
Dr. Beim explained that Celmatix is tackling the problem by pairing big data analytics with genomics; building the FertilomeTM Database as a filtering tool and discovery engine; and looking at possible biomarkers for infertility. This work will lead over the coming years to the development of the world's first noninvasive, companion genetic diagnostic test to guide infertility treatment and identify women at risk for premature menopause.
"Understanding the genetic drivers of infertility is step one in the direction of personalizing reproductive medicine," she says. "Having diagnostics that can differentiate who treatments work for better than others is good first step. But the real promise is then to be able to pair this information with targeted therapies."
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