IVF and the AI startup race

Around 180 Million women are struggling with fertility and we are seeing emergence set of startups from various corners of the world to solve this challenge.

I recently got a chance to look at the global fertility treatment market, specifically at IVF, one of the most common Assisted conception routes resorted by millions.

With the latest developments in machine learning and AI, the fertility treatment segment is seeing an inflow of venture capital money targeted at startups promising to create drastic improvements in this space with data.‍

In highlight, I believe this is why investors, operators, and founders should know about this space which is ripe for a technology-driven revolution.  

1. Around 180 Million women are struggling with fertility, and the number is growing at a 10% YoY rate. 
2. One in four couples in developing countries faces infertility, and around 48.5 million couples experience it worldwide.
3. From a methodological standpoint, even after 40 years of existence, IVF hasn't seen any drastic improvement in its process.
4. The couple who utilize IVF usually undergoes 3-5 cycles, which costs upwards of $75,000-$125,000 and is not usually covered by insurance. 
5. With recent development in predictive technologies, leaders in this field are hoping for a new set of data-driven tools to improve decisions making involved in various stages of the IVF cycle and drastically reduce the cost for end customers.

Taking a step back, looking at the broader scenario. When it comes to Fertility treatment today, we primary have three options. 

1. Medical
2. Surgical procedures
3. Assisted conception – including intrauterine insemination (IUI) and in-vitro fertilization (IVF)

‍In the assisted conception method, IVF is one of the most popular routes Each year, clinicians worldwide perform more than 2.5 million IVF cycles, resulting in more than a half-million deliveries annually.

In order to dive deep into the broader landscape, it is necessary to understand what IVF is, who it is for, and IVF falls short today.

What is IVF?

IVF or Inverto fertilization is an Assisted conception route where the egg is collected from the donor and fertilized outside the body. Here, the female takes medications to encourage the development of more eggs than usual. Later these eggs are removed from the ovaries and will be fertilized with the sperm in a laboratory. Thus an embryo is formed.

This newly formed embryo is returned to the womb for further growth and development. 

Who can have IVF?

IVF targets women under the age of 43 who failed to conceive through conventional methods or have tried a combination of artificial insemination and intrauterine insemination (IUI)

Chances of success 

‍The success of IVF primarily depends on the woman's age who is undergoing treatment and the root cause of infertility.‍

Based on 2019 stats from the National Health Service (NHS), UK 

• 32% for women under 35
• 25% for women aged 35 to 37
• 19% for women aged 38 to 39
• 11% for women aged 40 to 42
• 5% for women aged 43 to 44
• 4% for women aged over 44

‍The prolong scenario

Looking at the consumer side, IVF is a costly investment for couples on numerous levels, including financially, physically and emotionally.

IVF is highly effective if the patients can go through multiple cycles - usually 3-5. But the costly nature of the processes averts couples from this treatment.

‍Usually, in the US, this treatment will cost past $75000-125000, including medication, and typically insurance does not cover these expenses. So this price point alone makes sure that only the top majority can afford this,

‍Besides cost, IVF treatments are physically and emotionally demanding - the medications used for suppressing the hormone cycle and the production of additional eggs can have severe side effects on the patient.

‍Along with this, multiple, precisely timed shots and doctors' appointments will make this process even harder for couples.

‍Market dynamics and the future  

Many domain experts and top VC firms like USV are betting on emerging technologies like machine learning and AI to drastically reduce costs while improving decision-making in leverage points involved in IVFso that this market will be more accessible to the masses.

‍All incumbents working to solve this significant challenge focus on a set of crucial areas called leverage points. ‍Typically in IVF, there are 6 leverage points; these are strategic points in the IVF lifecycle where crucial decisions are made.

‍They include - decisions from clinicians on Ovary stimulation medication, the timing of egg retrieval, and analysis of embryo sperm and fertilized egg.

‍Usually, in these distinct points, the outcome directly correlates with the doctor's expertise; the more expert the doctor will be, the higher the chance of success.

‍
Here two elements come into the picture - 

1. As this population of patients drastically increases, this segment will see a higher demand for expert clinicians; this more elevated demand, combined with the limited supply of experts, can further accelerate the expenses and render this option absolute for most.
2. Even though IVF has existed for a while, it still follows a decades-old approach, especially in the decision-making on leverage points where clinicians make the analysis. Here there is a strong use case for data-driven and predictive modelling technologies which can harness data from all the past cases to enhance and bring more visibility to this decision-making process. 

‍With this very appealing market dynamics and rapidly growing market - the global IVF market is set to reach around $36 billion by 2026; we are seeing an emergence set of startups emerging from various corners of the world.

‍Here I'm introducing a few of them I discovered through my brief research.

‍ALife - Newyork, USA

Among these incumbents, Alife's develops a set of products that leverage data and ML to augment major pieces of human decision-making with data-driven insight into the fertility process.

‍Alife is building a set of products that empower doctors to use extensive patterns over millions of data points versus just their learnings from their patients. It equips them to develop personalized treatment plans that create better outcomes per cycle and lower patient costs.

‍Right now, the company focuses on ovarian stimulation (determining the drugs used for each patient to produce the largest number of high-quality eggs in a cycle) and embryo selection (deciding which embryo to transfer once the eggs have been harvested and fertilized.) 

‍Alife wraps the technology in easy-to-use software for the practitioner and an understandable interface for the patient.

‍Alife is backed by some of the best investors out there - recently, Alife raised its Series A from investors including lead by including Lux Capital (Lead and Follow-On), Union Square Ventures Maveron New Investor at an estimated post-money valuation of $102.00M.

‍Fertility -Israel 

‍Fertility develops AI IVF tools to provide accurate embryo classification and implantation prediction. Fairtility's platform offers services that use computer vision and big data to drastically increase the efficiency of IVF and reduce the time to live birth, enabling patients with proper and early data-driven embryo quality assessment leading to improved pregnancy rates with shorter and fewer IVF cycles.

‍They recently raised $15M in growth capital from Gurnet Point Capital, Nacre Capital and other unknown investors.

‍Emrbyonics - Haifa, Isreal 

‍Embryonic develops a suite of artificial intelligence (AI) solutions to revolutionize fertility treatments. The company's solutions save time, money, and emotional and physical turmoil by identifying the key steps to be optimized, thereby enabling medical professionals a reliable system to monitor and select embryos.

‍Embryonic has raised $4 million of seed funding in a deal led by the Shuctermann Family Investment Office.

‍
Mojo - Lyon, France

Mojo develops healthcare assessment devices to monitor and provide artificial intelligence-powered semen assessment. Mojos device provides accurate sperm count, motility, and morphology within a short time by analyzing it through AI and robotics.

‍Mojo raised EUR 1.81 million of venture funding from Clausen Engineering, Crista Galli Ventures, Aligned Ventures and other undisclosed investors on September 28, 2021

I strongly blive that this space is ripe for a change, and some of these new incumbents will be its key driver. I'm excited about this space and do follow Dara for future updates