Artificial intelligence (AI) is revolutionising how we manage most of our activities due to its ability to quickly analyse a huge amount of data, solve complex problems, learn and find solutions. From finance to research, agriculture and marketing, it looks set to gradually make its way into every field. Although the advent of AI raises many questions, it still opens up incredible prospects, especially in the healthcare sector. Medicine, which owes much of its progress to technology and innovation, is a key sector for the use of AI given the volume of data to be analysed. It has already begun its transformation and is expected to further accelerate this process in the coming years, with the emergence of new ways to cure and even prevent disease.
At the dawn of a revolution
Although artificial intelligence has been making headlines in recent years, its existence is nothing new. It emerged to a large extent alongside computing, an area where it supports developments, feeding its systems with programs that can perform certain tasks. The creation of the first computer chess game in the 1950s is the most telling example. What is new, however, is the democratisation of generative AI and its ability to create new content by processing huge volumes of data. Although everyone is familiar with its applications in image, text and music, the possibilities this innovative technology affords us today are incomparable to everything seen so far. By pushing the boundaries of information processing, AI is paving the way for major advances in research and development. This is already evident in online translation tools and can also be seen in the legal field, where time spent consulting case law is beginning to decrease thanks to the use of AI.
"Given the quantity and complexity of medical data, AI could reduce the time it takes to conduct pharmaceutical research to just one to three years (versus eight to ten years currently). The budget per product could also be reduced to $500 million or $1 billion on average, compared with twice this figure today. The trial failure rate of 93% could fall to 50% in the future," explains Hervé Prettre, CIO Office, Head of Research & Thematic Investments at Banque Edmond de Rothschild.
Infinite prospects
This shows just how much the field of medicine looks set for major changes. From cancer to cardiology and dementia, AI could make a contribution in any area. In diagnostics for example, AI can already analyse a radiological image more accurately than the human eye and give a more reliable diagnosis. AI could define treatments more quickly based on symptoms, as well as adapt them according to multiple factors such as genetics, medical history and lifestyle. AI can also allow us to more effectively identify correlations between patients, diseases and drugs by taking into account demographic factors such as sex, comorbidity and the age of patients who have or have not received certain treatments. As such, we are heading towards more personalisation and less empiricism. In addition, AI could enable us to more effectively predict the target-molecule interaction, significantly improving the success rate of new drugs on the market.
Figures already show that cancer deaths have fallen slightly since 2022 thanks to earlier diagnoses and more effective treatments. The introduction of AI in oncology has immense potential, particularly in melanoma screening, targeting immunotherapies and DNA sequencing to decipher a tumour's genome and destroy it more effectively. With experimental AI now able to identify certain cancers with 99% accuracy several years before the tumour is visible on a CT scan, it's easy to see why and how this innovation can revolutionise medicine. This means that administering a treatment could be vastly simplified, for example by simulating a patient's eligibility for certain medications. Meanwhile, effectiveness is also improving. This is evident in mammograms, which are now examined 30 times more quickly and with 99% accuracy.
AI is also useful in terms of knowledge sharing. This technology accelerates the speed at which knowledge is disseminated and accumulated, not just to access information but also to establish correlations between cases, tests, errors, reactions and medications, and thus steer research, diagnosis and treatment in new directions. For example, an AI analysis has identified an insomnia drug that could also have a beneficial effect on neurological disorders related to Parkinson's disease. "AI's ability to draw conclusions, identify pathologies and recognise trends is unparalleled," adds Hervé Prettre, concluding: "This technology will accelerate the health revolution by enhancing the preventive aspect of medicine, thanks to the ability to analyse data and detect disease early on."
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