Olga Chabr Grillova
CEO, Leeaf
Prof Rita Vassena, PhD
Member, Leeaf Scientific Board
A medical female technology (FemTech) startup is developing a data-driven patient management software to improve treatment decision-making for in vitro fertilisation (IVF).
By translating available technological solutions and capabilities to the fertility sector, MedTech companies can contribute to the improvement of fertility treatments on a larger scale. These can come in the form of health software and tech-enabled products and solutions that support women’s health.
Data-driven FemTech supporting fertility treatment
Leeaf is a fertility health portal for physicians and white label-ready mobile app for patients offering a solution that ties together algorithms of patient data and oocyte evaluation technology. Patient data is based largely on digital at-home hormone and lifestyle anamnesis (medical history-taking that can expand diagnostic possibilities).
The platform aims to elevate fertility diagnostics, streamline the IVF process and improve patient outcomes for clinics to level with the increasing global demand for fertility treatment. “FemTech and emerging medical solutions improve diagnostics and fertility treatment to solve infertility for future generations,” states Olga Chabr Grillova, CEO of Leeaf.
FemTech and emerging medical solutions
Olga Chabr Grillova
improve diagnostics and fertility treatment.
Empowering patients and physicians
Patients can store all fertility-related information within the mobile app and make it accessible to their physicians, providing them a 360-degree patient view of their current health. It also provides fertility insights as well as lifestyle and nutrition recommendations. With the data input by patients, physicians are given the ability to make data-driven decisions and come up with a treatment plan — based on real-time information.
“We need to develop evidence-based solutions using solid patient data in order to advance fertility treatments,” explains Associate Prof Rita Vassena, PhD., member of the Leeaf Scientific Board.
Personalised treatment and human autonomy
The platform uses two types of algorithms — rule-based and ML-based — that work together to ensure scientific and clinical validity to provide hyper-personalisation. Holistic data collection in female health and thorough research on medical, lifestyle, environmental and genetic information will make it possible to cater to the unique predispositions of every single fertility patient.
“Our dedicated research study on biomarkers that affect the outcomes of ovarian stimulation for IVF contributes to closing the data gap in women’s health. It improves diagnostics and treatment selection for future IVF patients,” concludes Grillova.
