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Disrupting the fertility industry with AI-powered technology

Artificial intelligence will likely transform the fertilization field and significantly increase the chances of success for women across the world.

Illustration of digital reproductive science educational interface.
Image: KnowTechie

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Infertility is a prevalent issue, affecting one in six women globally throughout their lifetimes. A woman is diagnosed with infertility if she fails to conceive after 12 months or more of regular unprotected sexual intercourse.

Aside from the inability to get pregnant, infertility can also mean the inability to maintain pregnancy after successful conception. Among various methods of reproducing after receiving this diagnosis is in vitro fertilization (IVF). 

IVF is a fertility treatment involving the implantation of a fertilized egg directly into the uterus via a simple surgery.

Not only is the process emotionally taxing and expensive, but it’s also not as effective as people are led to believe.

According to the NHS, while women under 35 have a 32% success rate, those who are 40 and older are faced with much more devastating odds of 4% to 11%. 

How does IVF work?

Microscopic view of a developing embryo at early stage.
Image: Pexabay

At first, the female patient is injected with synthetic hormones to produce multiple eggs as opposed to just one per ovulatory cycle.

A clinician then harvests the eggs to inseminate the patient with the partner’s and donor’s sperm and create embryos.

The next step is embryo implantation which is a simple outpatient procedure that takes place a few days later. The remaining embryos are frozen to preserve them for future transfers. 

Why does IVF sometimes fail?

Medical studies have shown that one of the most ubiquitous reasons for failed IVF treatments is the poor quality of eggs and embryos. Unfortunately, the methods of delineating between embryos are quite limited.

Specialists apply three basic criteria: cell stage, embryo grade, and rate of cell division. However, manual embryo selection remains highly unreliable and leads to many failed conceptions. 

How much does IVF cost?

The cost of a single IVF treatment varies depending on the country and even the state.

In the United States, the overall cost to the patient can go up to $15,000 and higher, while countries with universal healthcare partially or fully cover IVF cycles.

However, since the odds are relatively low, most women have to go through multiple treatments, which inevitably raises the final cost to hundreds of thousands.  

Aside from the high cost, the procedure takes a huge toll on patients’ mental and physical health. Studies have shown that undergoing and failing multiple IVF leads to depression and lower self-esteem and confidence.

Female patients also experience various side effects including hot flashes and headaches. The most severe outcomes of IVF treatments are ectopic pregnancy and ovarian hyperstimulation syndrome (OHSS). 

Having observed a specific mistrust in the healthcare industry regarding technological implementations, I am determined to demonstrate the boundless benefits that tech can bring to IVF.

My goal is to change this mistrust to help the industry make quantum leaps easily.

What’s the solution?

Illustration of digital analytics and data icons on screens.
Image: KnowTechie

Although oftentimes hard to adopt, various technologies have played major roles in the healthcare industry over the last decades.

Artificial intelligence is one of the most significant contributors, automating internal processes for physicians and making healthcare more accessible for patients.

Unsurprisingly, AI solutions are also being implemented in the fertility sector. AI’s power allows engineers to develop solutions that can increase the accuracy of a single IVF cycle, making it safer and more affordable.

The pivotal benefits of applying AI in fertilization treatments include embryo selection and regimen personalization. 

By collaborating with our client, we have invented a groundbreaking methodology for identifying the best embryos to maximize success rates.

By leveraging AI-driven image recognition algorithms, the solution can detect an embryo with the highest potential to successfully implant and lead to pregnancy.

Using this technology can revolutionize fertilization efforts and help women everywhere. 

Deliverables

My team and I were prepared to address this ambitious task, relying on our technical expertise in digital platform engineering, as well as AI and machine learning.

Our deliverables are threefold: an AI engine for image recognition, a backend for data processing, and a user interface. 

AI engine

Based on 250 GB of data sourced from fertility clinics, we developed a production-ready AI engine capable of identifying and classifying embryo images to aid clinicians in decision-making.

As a result, the number of embryos for implantation dropped by half, from 3-4 to 1-2 per standard IVF cycle.

The system is also built using the latest technologies and features an infrastructure-agnostic and cloud-ready design based on microservices, containerization, and automated deployment.

User Interface

Embryo analysis software interface with microscopic view.
Image: EMA

The intuitive user interface allows physicians to access information using convenient dashboards and reports.

Created with several personas in mind, the application’s user interface caters to embryologists, reproductive endocrinologists (REI), and lab managers.

In a single location, specialists can retrieve data pertaining to the status, parameters, and quality of embryos, statistical information with indications and insights, and treatment progress updates. 

Robust backend

We chose Golang as the main backend technology for its ability to build high-loaded applications based on microservices architecture.

Since we forecast the growing demand for fertilization treatments, we decided to go with a SaaS model that allows for high scalability and reliability. 

What does this mean for the future of IVF?

Human hand touching digital interface with binary code. AI
Image: Pixabay

Artificial intelligence will likely transform the fertilization field and significantly increase the chances of success for women across the world.

The technology can reduce risks associated with multiple IVF attempts and provide precise metrics that guide physicians through the process.

Applying AI algorithms to fertilization procedures will alleviate stress, decrease damaging side effects, and prevent patients from spending thousands of dollars on a failed treatment.

The fertilization industry will never be the same, and more and more clinics will rely on this technology to improve their success rates.

Luckily, companies like our client are at the forefront of this change and continue to invent better solutions to help women start families.

Our team at NIX is dedicated to sharing our technical prowess and helping organizations utilize AI to drive the industry forward.

Get in touch with the NIX team to learn more about our experience and create a robust solution for your business. 

Author bio

Natalie Tkachenko is a leading software engineering advisor and head of sales at NIX with seven years of experience. In the last five years, Natalie focused on the healthcare sector and played an integral role in over 40 projects. Her extensive experience helps her expertly identify business needs and growth opportunities, allowing companies to open new doors. 

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Disclosure: This is a sponsored post. However, our opinions, reviews, and other editorial content are not influenced by the sponsorship and remain objective.

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