In-vitro fertilization represents a significant hope for the scores of families who struggle to have children. But the procedures – which often aren’t covered by insurance – can be prohibitively expensive and emotionally trying.
Dr. Mylene Yao experienced these challenges first-hand with her patients while practicing as an Ob/Gyn. In 2010, she co-founded a startup called Univfy to lower the financial burden of IVF treatments and increase the chances of success for participants.
Based in Los Altos, California, the company uses machine learning-based analysis of clinical data to help fertility clinics provide personalized patient reports with success probabilities for potential IVF participants.
Earlier this year, the company received a $6 million Series A funding round, which it has used to continue to build out its platform and grow its customer base to around 20 clinics across 15 states.
More accurate assessment of IVF success has proven to be a boon for fertility clinics who often see patient drop after failing one cycle even if they have the financial means to continue treatment.
“Each treatment its like flipping a coin, but you’re not actually sure what the chances are, whether it’s 50-50 or 80-20,” Yao said in an interview.
Still, a major barrier for potential IVF participants remains the high cost. On average the cost for a single IVF treatment program is around $12,000. But that number can vary widely depending on the market and many women require multiple treatments before getting pregnant.
Univfy helps to defray the cost of treatment by enabling more women to take part in clinic rebate or refund programs where participants are entitled to partial or full refunds if IVF efforts fail.
Using the company’s platform fertility clinics can get a better picture of their own success and practices, while also having higher confidence to offer financial guarantees to patients.
“Fundamentally these providers want to find a way to be more data driven and they care about giving people their personalized prognosis,” Yao said.
“Our modeling process is very exciting to them because you’re talking about years of their work being presented back to them in way that produces brand new insights into the patients they’re treating.”
As the startup continues to grow Yao said the company is looking closely at potentially developing medication discount programs and also working more closely with consumer lenders to offer financial products informed by Univfy’s data infrastructure.
But just having data is not the ultimate goal.
Where Yao said the company is now focused is on building out holistic programs that can help fertility clinics communicate Univfy’s results and support the patients they serve with the data.
“In medicine as a whole this type of approach is still uncommon and requires a lot of explanation, training and coaching,” Yao said. “Our core differentiator is machine learning, but it takes a lot of effort to translate that math into normal language and support someone’s emotional well-being through that challenging time.”
Picture: Rost-9D, Getty Images