India, China lead the AI fertility treatment race

In late 2021, Chinese scientists crafted AI systems or robotic nannies for embryos growing into fetuses in artificial womb environments. The technology could reportedly monitor embryos, detect movements or changes in the womb, and accordingly make adjustments in their artificial environment.

These AI systems possess trained algorithmic combinations to report embryonic defects or abnormalities.

AI has the potential to investigate and expedite fertility treatments through algorithmic decision-making by effectively linking data science to finding solutions to barriers in fertility, which is ignored in most countries.

Technology has kept up with innovations to combat falling birth rates across the world.

Bloom IVF group, one of the oldest IVF chains in India, uses AI-led matrices to assess embryo quality and deciphers the likelihood of a woman to get pregnant.

Robotic technology and nanobots are increasingly becoming part of fertility treatment in India using AI algorithms to provide real-time analysis of oocyte penetration which allows doctors to select suitable sperm cells for the development of healthy embryos.

AI technology can predict unknown patterns and enable early interventions to identify and limit preterm birth rates, stillbirths, birth defects, and provide viable interventions for primary infertility. It lends diagnostic accuracy to fertility treatment and offers detailed analysis by accounting for various variables fed into AI tools.

These use advanced algorithms that consider factors such as a woman’s age, geographical details, previous pregnancies, medical records, lifestyle issues and stress factors to identify women at high risk.

The success rates of AI techniques in treating infertility vary from 35 to 42 years of age per individual life cycle. Overall, women conceive within the first six cycles.

AI is being used to enhance the accuracy of embryo selection, gamete selection, development of new drugs, customised treatments, and automation of tasks involved to improve fertility in India aided by AI technology companies such as Life Whisperer and Presagen.

The Asia-Pacific region has some of the highest fertility variables. In 2023, with the highest population in the world, India’s fertility rate stood at 2.13 which almost coincides with the replacement rate of 2.1%.

As per a recent WHO report, the estimated prevalence of primary infertility among women in the reproductive age group (15 to 49 years)  is 11.8% in India.

China’s fertility rate is already one of the lowest in the world, at 1.705 births per woman in 2023, a 0.18 percent increase from 2022 when the nation’s fertility rate dropped to a record low of 1.09.

The average cost of an IVF treatment session, which includes egg retrieval and transplant in China, is between $USD4,500 to $USD5,000.

In India, a single IVF cycle’s cost can range from $USD2,000 to $USD6,000 or more, depending on the hospital value addition factors.

Intrauterine insemination (IUI) is one of the most affordable fertility treatments in India. The cost of IUI in India ranges from $USD120 to $USD180.

China and India are leading players in AI technology. China is advanced in applying technology in healthcare while India is among one of the leading countries experiencing the fastest rate of AI skills diffusion in terms of acquiring AI skills by the workforce to enrich their work and improve productivity and innovation.

The AI in healthcare market is projected to grow from USD 14.6 billion in 2023 to USD 102.7 billion by 2028 in India.

China’s fertility rate has been lower than India’s for years because of China’s One-Child Policy. Since 2016, however,  Chinese couples have been allowed to have two children.

But policymakers are increasingly concerned about the impact of China’s growing demographic crisis of an ageing population on economic growth.

The National Healthcare Security Administration in China offered free fertility treatment under its national insurance scheme in a bid to reverse falling birth rates. Most of the national insurance schemes in India do not cover fertility treatments under the category of medically necessary treatments.

The high treatment cost in controlling the fertility crisis calls for concerted policy measures by the Indian government with strategic action plans and targets to improve healthcare access for both India’s rural and urban populations.

The national strategy for AI by the Niti Aayog in India in 2018 and 2021 does not explicitly cover fertility under the focus areas for AI implementation in healthcare.

Artificial intelligence is set to reinvent healthcare with far-reaching technological breakthroughs and ever-increasing medico-technical integration of AI in healthcare, particularly addressing primary and secondary concerns of female and male fertility.

The important question is how will providers and patients benefit from enriched AI tools in revolutionising fertility treatments using algorithmic decision-making.

A set of comprehensive, universally accepted guidelines for AI technology use in fertility treatments addressing patients’ privacy concerns and medico-legal regulations are the principal areas to be addressed by policymakers.

Ethical concerns in determining the sex of the fetus can arise again. In this context, the government would need to make policy changes in other women-centric policies revolving around the fetus.

If AI is a boon in treating fertility issues in the economies with the largest populations and technology adoption such as India and China, then factors determining AI readiness with respect to the prevalence, need, culture, governmental interventions and citizen awareness need to be evaluated and strengthened.

The government and private sector’s willingness to have robust collaborations to facilitate, regulate, measure and evaluate the use of AI in fertility treatments can significantly improve the fertility conundrum.

Dr Vijayetta Sharma is an associate professor of public policy at Manav Rachna International Institute of Research and Studies. 

This article was first published by 360info.