> AI-Powered Precision Medicine:
The Silver Bullet for Equitable Healthcare? By Shahnaz Radjy, Enrico Santus & Nicola Marino
Transformation is never easy. Whole theories exist around facilitating change, focusing on how to get individuals or populations to modify their patterns of behaviour.
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ow imagine trying to change not just people, but something like the healthcare system. That is the promise and challenge around artificial intelligence — from what is portrayed in popular culture as a tech and innovationcentric society in Back to the Future’s 2015 to any of the risks of technology misuse represented in the Netflix show Black Mirror — and precision medicine. How do we take innovations from the research lab to the patient, and can Covid-19 somehow provide an example that lights the way?
"AI empowers clinicians to tailor preventative or therapeutic interventions that account for the nuanced — and often unique — features of every human being."
Health professionals are treating the pandemic using trial-and-error based on a one-size-fits-all approach. This is a missed opportunity in this age of big data and high-performance. AI-led computing offers more precise, effective, and affordable solutions. Antonella Santuccione Chadha, CEO of the Women’s Brain Project, says: “The potential for drastic change within the healthcare system is within reach thanks to novel technologies and AI-driven solutions available to propel us from the age of shallow medicine to the era of precision healthcare.”
But these data are the perfect playground for AI, enabling the substitution of the hypothetical average patient with a real individual, based on his or her genetic, epigenetic, geographical and socioeconomic signature.”
Precision medicine can revolutionise how we practise medicine. However, we need to bridge the gap between research labs and patient care — and do so in an intentional manner that paves the way for equity in access to healthcare.
Aided by AI, it can predict the risk of a person developing a disease and estimate the likelihood of success for a specific treatment. This leads to enhanced allocation of resources, a better match between treatments and patients, and improved health outcomes.
WHY WE NEED PRECISION MEDICINE AND AI Which patients develop a more severe outcome than others? Which are more likely to respond to a given treatment? What is the best preventative option for any given patient? For centuries, doctors have made this type of prediction based on experience and a hypothetical “average” patient. However, what is normal for you might not be for someone else. Age, gender and a number of other parameters affect the interpretation of results. Wouldn’t you rather use the details of your specific health profile, rather than a potentially oversimplified average? “Multidimensional datasets reflecting all facets of a person simply cannot be grasped by human minds,” explains Maria Teresa Ferretti, cofounder and CSO at the Women’s Brain Project. 78
In that way, AI empowers clinicians to tailor preventative or therapeutic interventions that account for the nuanced — and often unique — features of every human being. This is called precision medicine.
Covid-19 has proven very difficult to tackle with standard medicine. Rates of mortality, severity, and response to treatment are extremely variable, making it hard to make predictions. The incidence and outcomes of Covid vary according to individual factors, including age, gender, race/ ethnicity, health status, drug use and more. A drug that might be beneficial for one patient might be in dangerous for another.
Epidemiology (COPE), a consortium that developed a symptom-tracker app, a real-time data-capture platform. In a few days, it garnered over three million users. Based on available data, AI applications for a broad range of clinical tasks already exist, including risk prediction and prognosis, diagnosis, and treatment. Other tasks are being addressed for long-term solutions. Among them is the identification of existing drugs that could be effective in addressing proteins targeted by the virus, or the discovery of new chemical compounds that can perform the same task. A study published in The Lancet describes how algorithms identifying interactions between drugs and proteins helped detect Baricitinib, as a useful drug against Covid-19, despite being indicated for arthritis. THE HEALTHCARE SYSTEM, PRECISION MEDICINE, AND AI The recent pandemic has highlighted how delicate our healthcare systems are, with even Switzerland and Germany put to the test. This crisis made it evident that including AI is not optional, but critical to speed-up decisions, avoid mistakes, and optimise resources. However, AI implementation for precision medicine in Covid-19 in is still far from complete. Organisations such as the World Economic Forum have initiatives focused on precision medicine and related governance gaps aiming for a worldwide adoption while addressing inequities.
This is direct evidence of the need to move towards precision medicine. For that, we need three things: data, algorithms, and a supportive healthcare system.
The highly fragmented and diverse healthcare systems, the absence of a protocol to document patient data (leading to inter-operability issues), the ethical constraints such as privacy, and the limitations of AI itself (bias and noninterpretability) still represent a serious challenge to extensive AI adoption. The digital literacy of stakeholders — or lack thereof — should not be underestimated either.
AI APPLICATIONS IN COVID Initiatives collecting multidimensional datasets in the context of Covid-19 started early. One example is the Coronavirus Pandemic
The collaborative approach can be unlocked through Covid-19, and powering the myriad consortia created to tackle the pandemic will continue. It will build on learnings from the past
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