About Univfy®

Univfy is dedicated to helping individuals and couples realize their dream of becoming parents. We are IVF and fertility analytics experts passionate about providing you with the tools to choose IVF with greater confidence, success and cost-success transparency.

The Univfy AI Platform enables fertility doctors to provide accurate, personalized IVF treatment success prediction to help more patients qualify for special pricing plans such as IVF refund programs. The company was founded by Stanford University researchers in 2009.

Our Founders

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Mylene Yao, M.D.
Co-Founder and CEO

Dr. Yao has led Univfy® from founding through stages of technology invention and commercialization. She is now leading the team to scale Univfy's business. Her vision is to combine healthcare AI, fintech, and scientific validation to power women's access to fertility treatments that are safe and highly effective.
Dr. Yao has over 20 years of experience in clinical and scientific research in reproductive medicine. Prior to founding Univfy, she was on the faculty at Stanford University, where she led NIH-funded fertility and embryo genetics research, and developed the Univfy® technology with the academic founding team.

Dr. Yao graduated from medical school at the University of Toronto and completed her obstetrics and gynecology residency training at McGill University. She received her clinical subspecialty training in reproductive endocrinology and infertility at Brigham and Women’s Hospital at Harvard University. Dr. Yao received multiple research awards for her fertility research work, including pre-implantation embryo development, the role of stem cell genes in the embryo, and uterine receptivity at implantation. She is co-author of the chapter on Infertility in Berek and Novak's Gynecology, the top medical textbook for obstetricians and gynecologists.

Dr. Yao has been honored with The Bump - Moms: Movers and Makers (2016) and MM&M's Top 40 Healthcare Transformers (2017).

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Wing H. Wong, Ph.D.
Co-Founder and Advisor

Professor Wong is the Stephen R. Pierce Family Goldman Sachs Professor in Science and Human Health and Professor in the Departments of Statistics (former chairman) and Biomedical Data Science at Stanford University.
Professor Wong's seminal contributions to theoretical statistics — most notably, Bayesian network structures, machine learning, Monte Carlo, and applied statistics in computational biology — have been recognized with numerous awards and honors.

In 2009, he was elected to the National Academy of Sciences for developing innovative high-throughput genomics analysis tools, pivotal in driving genomics research in the past decade. Professor Wong is Chairman of the International Advisory Committee of the Center for Statistical Sciences at Peking University.

Univfy® Timeline

Univfy founding team began their academic research in IVF prediction modeling at Stanford University.

2005

Univfy founding team published their first validated IVF prediction model.

2008
  • Univfy researchers identified powerful IVF success predictors.

In their research, Univfy's founding team identified several powerful predictors of IVF success. Specifically, four variables--the total number of embryos, number of 8-cell embryos, percentage of embryos arrested at cleavage stages, and Day 3 FSH level-- were more powerful predictors of IVF success than measures associated with individual transferred embryos. Three of the four predictors above describe the embryo group (or embryo cohort), rather than individual embryos.

Defining human embryo phenotypes by cohort-specific prognostic factors.

Jun SH§, Choi B§, Shahine L, Westphal LM, Behr B, Reijo Pera, Wong WH, Yao MWM. PLoS ONE 2008; 3(7):e2562. doi: 10.1371/journal.pone.002562. §Co-first authors.

Dr. Mylene Yao and Professor Wing H. Wong co-founded Univfy.

2009

Univfy began operating as a company and focused on R&D in 2010-2012.

2010
  • Univfy IVF prediction models are 1,000 times more accurate than age-based estimates when you use patients’ personal profiles.*

More than 80% of patients tested by Univfy’s prediction models were proven to have higher probabilities of IVF success, compared to age-based estimates. Further, nearly 60% of patients were found to have a better chance of having a baby than was estimated by age.

Why the discrepancy? Because age-based predictions fail to consider important reproductive factors that more reliably predict IVF success. Likewise, other methods that analyze fertility factors independently do not consider the patient’s entire reproductive profile either. Univfy IVF Prediction Tests analyze an entire profile of reproductive factors to deliver the most accurate estimate of having a baby, whether from a first IVF or subsequent IVF treatment.

*Univfy IVF prediction models have 1,000 times bigger likelihood than age-based estimates. Alternatively, we measured the percentage improvement in predictive power by comparing the posterior log-likelihoods of each prediction model and its age-based prediction, against the baseline model. Univfy PreIVF shows a 36% improvement in predictive power over age-based prediction, while Univfy PredictIVF shows a 77% improvement in predictive power over age-based prediction.

Deep phenotyping to predict live birth outcomes in in vitro fertilization.

Banerjee P§, Choi B§, Shahine LK, Jun SH, O’Leary K, Lathi RB, Westphal LM, Wong WH, Yao MWM. PNAS 2010;107(31):13559-60. doi: 10.1073/pnas.1002296107. Epub 2010 Jul 19. §Co-first authors.

Univfy began providing customized IVF prediction tools to support eSET counseling to providers.

2012
  • Univfy researchers found that the probability of having twin births with IVF is specific to each patient’s profile and can be predicted.*

Univfy has developed and tested a prediction model that can calculate a woman’s probability of having twins from IVF (when two embryos are transferred). The model uses a woman’s reproductive history, laboratory tests, response from her current IVF treatment, and embryo quality to determine her probability of having twins if two fresh embryos are transferred instead of just one. Personalized predictions of multiple birth risk can support physicians when counseling their patients about the benefits of elective single embryo transfer (eSET).

Predicting personalized multiple birth risks after in vitro fertilization-double embryo transfer.

Lannon BM§, Choi B§, Hacker MR, Dodge LE, Malizia BA, Barrett CB, , Wong WH, Yao MWM, Penzias AS. Fertil Steril 2012;98(1):69-76. doi:10.1016/j.fertnstert.2012.0411. Epub 2012 Jun 4. §Co-first authors.

Univfy launched Univfy PreIVFTM and Univfy PredictIVF® for both IVF providers and fertility patients.

2013

These Univfy IVF Prediction Tests* were designed to be ready-to-use and did not require customization to a specific IVF provider.

  • Univfy PreIVF is the most accurate predictor of IVF success for patients before they start their first IVF cycle.

We have found that patient data can be used to accurately predict a woman’s probability of IVF success from a first cycle. Univfy PreIVF analyzes each individual’s fertility profile -- including age; body mass index, (BMI) comprising height and weight; ovarian reserve tests (e.g. serum anti-mullerian hormone or Day 3 FSH tests); semen analysis; and prior fertility and medical history. We then compare that information to profiles of thousands of others who have completed first IVF cycles to deliver a personalized prediction of IVF success instantly. More than half of first-time IVF cases tested by Univfy PreIVF had a significantly higher likelihood of IVF success than estimated by age.

Personalized prediction of first-cycle in vitro fertilization.

Choi B, Bosch E, Lannon BM, Leveille MD, Wong WH, Leader A, Pellicer A, Penzias AS, Yao MWM. Fertil Steril 2013;99(7):1905-11. doi: 10.1016/j.fertnstert.2013.02.016. Epub 2013 Mar 21.

Univfy is customizing a visually intuitive Univfy IVF prediction report to each IVF center.

2015
  • Univfy and collaborators show the accuracy and power of a prediction model that uses the ovarian reserve marker, AMH, together with other predictors, to give accurate predicted probabilities of IVF success and the IVF success distribution of patients within a top IVF center.

Antimüllerian hormone levels and antral follicle count as prognostic indicators in a personalized prediction model of live birth.

Nelson SM, Fleming R, Gaudoin M, Choi B, Santo-Domingo K, Yao MWM. Fertil Steril 2015. doi: 10.1016/j.fertnstert.2015.04.032

Univfy launched the Univfy-Powered IVF Refund Program**

2016
  • Univfy Voted Winner in Consumer Electronic Show 2016 The Bump Best of Baby Tech Awards in the Fertility Category
  • Univfy CEO and Cofounder Dr. Mylene Yao honored at The Bump Moms: Movers + Makers Awards Luncheon, Los Angeles
  • Univfy Selected To Join Springboard Tech Hub 2016
  • Patent Issued in US, Israel: Methods and Systems for Assessment of Clinical Infertility
  • Patent Issued in US, China: Method of Assessing Risk of Multiple Births in Infertility Treatments

Univfy profiles IVF providers using the Univfy PreIVF Report*

2017
  • Dr. Mylene Yao honored among MM&M's Top 40 Healthcare Transformers