🤰🏾 Does tech generate more birth defects? 📱
Optimizing the cultivation of embryo with deep learning
Hello and welcome to Careviser by Marie Loubiere, the weekly newsletter that cuts through the healthcare noise with a single focus: productization of the latest research and tech breakthroughs.
There is an increasing number of babies born thanks to assisted reproductive technology. Since the first IVF baby in 1978, it has become more and more common as the technology is more mature and affordable.
Assisted reproductive technology and birth defects in a Chinese birth cohort study by Hong Lv, Feiyang Diao, Jiangbo Du, Ting Chen, Qingxia Meng, Xiufeng Ling et al. in The Lancet Regional Health Western Pacific
🗝️ Why it matters: In the span of three decades, assisted reproductive technology went from being experimental to being used on millions of women. However side effects on women and their babies are not yet fully understood.
🔎 The study: The objective of the study is to explore the common conception that there are more birth defects associated with assisted reproductive technology than with spontaneous pregnancies. The study brought together a cohort of women in China between 2016 and 2019 and followed them from 20 weeks of gestation until their baby was a year old.
✅ Findings: At each stage of the follow-up (prenatal screening, delivery, baby at 6 months old, at 1 year of age), the study found that women pregnant through assisted reproductive technology were almost twice as likely to suffer from a defect. There is a higher rate of twins among assisted reproduction technology pregnancies which explained about a third of the increase in birth defect risk.
🚀 Opportunities ahead: At this stage, it is unclear which factors lead to higher risks for Assisted Reproductive Technology:
Infertility characteristics of the mother
Hormonal medication
In general, assisted reproductive technology is a fascinating field of medicine with many variables that can impact the outcome. The association between all these factors need to be further studied to optimize these variables:
Hormonal medication
Mother and father subfertility factors
Mother age and health condition
Quality of the oocytes
Type of oocytes used (fresh or cryopreserved)
There are quite a few companies tackling the Assisted Reproduction industry through the angle of optimizing outcomes with technology, and more specifically AI. A lot of them are still at a very early stage.
Alife Health is one of them, created just last year. Founded by a former PM at Auris Health (a surgical robotics company that was acquired by J&J), they aim to assist physicians at every step of the journey by helping them make better decisions with AI. The scope of their product remains to be defined.
ImVitro has a more concrete use case for AI in assisted reproduction. Founded by a team from the Entrepreneur First incubator two years ago, they apply deep learning on embryo images to predict the probability of a successful implementation and pregnancy. Indeed during the IVF process, embryos are cultivated in a lab for up to 5 days. During this time, their growth and survival are under the supervision of a team of embryologists. The Im Vitro software enables embryologists to ensure the best quality control of embryos. At this stage, they are focused on building the product through data-sharing partnerships they have established with IVF centers. They have quietly raised a small round with Fly Ventures.
Apricity has reached a more advanced stage. Spin-off from the health incubator from the insurer Axa (Kamet), it was founded in 2018. They essentially provide a concierge fertility service for patients enabling them to book online fertility consultations, contract selected clinics, and have the assisted reproduction process as digital as possible. The service comes with an app that allows the patient to receive their test results, track their medication, and so on. They used to put forward the fact that their treatment recommendations are based on Artificial Intelligence, however, that’s not something they mention that much in the new version of their website. However, one of their lead generation tools is a fertility predictor that aggregates all the fertility data to predict the probability of success of assisted reproduction treatments for a given patient.
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