Meet Professor Yau Thum, a world-leading fertility expert who has joined forces with computer scientists, psychologists and physicists at the University of Cambridge to pioneer a revolutionary AI-driven approach to transform the fertility journey – making it less stressful and more hopeful for families everywhere.
When the first baby was conceived through in vitro fertilisation (IVF) more than 45 years ago, it marked a groundbreaking moment in reproductive medicine. Since then, IVF has come a long way – leading to the birth of more than 12 million babies around the world. But success rates are still low – hovering at around 30 to 45%. More importantly, the investigation and treatment processes are still very similar to those that were used 20-30 years ago.
For many people facing infertility, the path to parenthood via IVF remains a tough journey –emotionally, financially, and physically. Only one in four IVF cycles result in a live birth, and many women try IVF multiple times. Each cycle takes up to six weeks and may involve one or more embryo transfer procedures, requiring numerous internal ultrasounds, dozens of hormone injections, and other physically demanding procedures – potentially costing thousands of pounds.
Researchers like Professor Yau Thum – a fertility specialist at the leading London-based Lister Fertility Clinic – are continually striving to improve the odds for women who are struggling to conceive. He specialises in addressing immunological factors that contribute to the failed implantation of embryos – focusing on the role of so-called ‘natural killer cells’, which play an important role in a successful pregnancy. For more than 20 years, his research and clinical practice have provided hope for women facing fertility challenges.
And now, Professor Thum is applying his clinical expertise in a ground-breaking way –prescribing Artificial Intelligence (AI) as a new tool to help make the fertility journey less stressful for patients. Through ai@cam, he’s working in collaboration with researchers from the University of Cambridge in the Departments of Psychology, Computer Science and Physics, as well as clinicians from Addenbrooke’s Hospital.
The idea was first conceived when the Covid-19 pandemic closed Professor Thum’s clinic temporarily in 2020. As he could no longer see patients in person, he started to think about a digital platform that could help people who were struggling to start a family, wherever they were in the world – dispensing instant advice and guidance to aspiring parents at the click of a button without incurring expensive travel costs and consultation bills.
“Sadly, a lot of patients still suffer in silence because the health service may not be able to help them or they may not have the funding,” he says. “I’d like to give some guidance to these kinds of patients. The ideal outcome would be to make the whole IVF process less stressful through one platform or app that people can download.”
If all goes to plan, Professor Thum’s idea will work like this: Instead of going for a 45-minute in-person clinical consultation, patients would interact with a digital platform in the first instance. This platform would gather all the basic medical history needed and dispense advice to the patient about next steps – using AI to personalise fertility investigations and treatments based on each woman’s individual profile.
“It’s almost like they have me inside the app,” says Professor Thum. “So that would significantly reduce the stress for the couple.”
This wouldn’t just be more efficient for the patient, it would streamline consultation times for clinicians too. Rather than spending 45 minutes with each patient for an initial consultation, Professor Thum could instead spend five minutes looking through and checking the AI-gathered information and suggested diagnosis for each patient. In effect, he’d be able to ‘see’ nine patients in 45 minutes rather than just one patient – freeing his time up to carry out research.
“If people don’t have the luxury to see a doctor,” he says, “they can download the app or digital platform to provide an initial analysis of their health or to get a diagnosis.”
Empowering not replacing clinicians
The obvious question is whether Professor Thum is worried that his invention could potentially make him and his colleagues redundant? His answer is unequivocal.
“We don’t want to replace clinicians, we want to empower clinicians,” he says. “It’s like having a junior colleague that can assist the clinician 24 hours a day, seven days a week. In fact, it’s there to help everyone. The AI system will give a diagnosis suggestion but the clinician can have input as well, so it becomes a hybrid process. And colleagues can learn from it and check things too.”
Not everyone in the fertility sector is as enthusiastic as Professor Thum about embracing AI though. He acknowledges that trust is a big hurdle to be overcome, for doctors and patients alike.
“Trust is very, very important,” he says. “Because if the user doesn’t trust it, your AI system will not take off and it won’t be useful. We still need a lot of energy and research to make sure users trust what we’re doing.”
Professor Thum and colleagues recently carried out a survey of healthcare professionals in Southeast Asia, which found that ethical concerns and a perceived lack of sufficient training represented substantial barriers to the broader adoption of AI in the medical field. Their findings underscore the pressing need for tailored educational programmes and robust policy frameworks that prioritise data privacy and job security. Just as crucially, the research emphasises the importance of equipping healthcare professionals with the skills and knowledge to harness AI effectively – not just as passive recipients, but as active innovators shaping the future of healthcare.
Professor Thum is the first to admit that AI is still very much in its infancy in the fertility context and that there are significant hurdles to be overcome.
“In terms of development, I would say AI in medicine is still not able to walk on its own yet,” he says. “It’s still crawling. It’s still at a very primitive stage.”
Bridging expertise
Initiatives like ai@cam are crucial, Professor Thum believes, for bringing experts together from different sectors – bridging their knowledge to make sure that the potential of AI is being harnessed to solve challenges like infertility.
“You need a multidisciplinary approach to make it happen,” he says. “It’s quite a challenging project because it’s across two specialties and we don’t know each other’s language. We need computer scientists, who don’t know medical language, and we need doctors, who don’t know about computer language. We need to bridge these different fields to develop the foundation of the digital platform.”
Professor Thum’s idea is still in its testing phase – drawing information from multiple sources to train the AI system so that it can be as accurate as possible when it comes to offering advice and diagnoses, as well as making sure that it follows the medical and ethical guidelines for multiple jurisdictions. He and his team have already built the app and the structural framework for the computer programme for this AI fertility wellness digital health platform. The system is beta- tested and is in the validating stage.
“The technology is not perfect yet but it can help a lot in the future,” he says. “I’d like to continue to collaborate with Cambridge to create more opportunities for the younger generations to learn about AI. We need to help the younger generation to establish that knowledge.”
Professor Thum is equally passionate about nurturing younger generations, even before they are born.
“As a fertility doctor, it’s always an incredibly joyous moment when a couple returns with their baby and tells me, ‘You helped change our lives for the better.’ That feeling is really priceless,” he says.
“On the research side, being able to expand knowledge in my field through research is deeply fulfilling. And if I can develop an app to support more patients, that would make me very, very happy.”
Read more about the ground-breaking ai@cam project From Womb to World: Using Innovative AI Methods to Revolutionise Fertility Treatments
