An India-based fertility start-up has secured US$6m in Series A funding to advance its hormone testing kit.
Around 17 per cent of the adult population worldwide, roughly one in six, experience infertility.
Inito, a company that aims to “simplify” healthcare, has come up with a fertility monitor and kit to help women learn more about their fertility directly from home.
The test measures the levels of oestrogen and luteinizing hormone (LH) to predict fertile windows while also measuring progesterone metabolite (PdG) to confirm ovulation. It also measures the follicle-stimulating hormone (FSH) to track follicle growth.
The kit comes with a fertility monitor that attaches to the mobile phone and allows women to access their diagnostic results on the Inito app where they can track their fertile days and ovulation.
“Unlike other products that leave the interpretation of hormone values to the user, our app looks at the evolution of four hormones together and determines if the fertility rating for that day is low, high or peak and if ovulation has indeed occurred in this cycle,” Aayush Rai, Inito CEO, told TechCrunch.
“With the latest advancements in AI, we have taken this one step further by explaining why a result was given in natural language.”
The new funding, which brings Inito’s total funding raised to date to US$15m, is hoped to help the start-up build more advanced analytics and better train its algorithms on the interplay of the four key hormones involved in the menstrual cycle.
The company says it wants to be able to allow users to correlate symptoms, moods, sleep patterns and medications to their hormones. The firm also plans to expand its business operations, invest in R&D and build an Android app.
Rai said: “While fertility hormone testing is our first product, this funding raise will allow us to invest in R&D for new tests that cater to solving problems faced by both patients and practitioners.
“We are building point of care tests for tracking pregnancy health, ovarian reserve and male fertility hormones.
“Our technology uses a combination of hardware, biotechnology and machine learning to improve the accuracy, reliability and density of test strips allowing them to measure multiple parameters on a single testing platform.”
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