In this article, we will know that, Medicine 3.0 combines biology and advanced computing to overcome traditional healthcare limits and usher in a new era of precision medicine.
A prominent expert at the nexus of biology and computer science, Professor Nam-Sik Han is advocating for a paradigm change in medical science. Han, who is currently an adjunct professor at Yonsei University and the Director of the AI Research Center at the University of Cambridge’s Milner Therapeutics Institute, is drawing attention to a pivotal moment where biological complexity and conventional artificial intelligence meet. In a recent talk at Yonsei’s Sinchon Campus, he explained how quantum technology is now an essential instrument for the future generation of medicine rather than merely a theoretical idea.
Why AI Struggles with Life Science
Professor Han notes that although artificial intelligence is frequently hailed as a breakthrough force in drug development, it has a fundamental structural constraint. Regardless of its strength, traditional AI ultimately functions on a binary system of 0s and 1s. Biological systems, however, are rarely so simple. According to Han, classical mathematics frequently fails to apply in biology, where variables are almost infinite and networks are extremely complicated; in these complex contexts, 1+1 can result in 1.9 or even exceed 2.
The fluid and unpredictable character of biological interactions is difficult for classical computers to simulate because they cannot readily express ideas that exist between 0 and 1. This is where quantum technology comes into play, providing a means to represent these “non-binary” states and improve the speed and precision of diagnosis and therapy. The South Korean government’s “K-Moonshot” project, which aims to assure national competitiveness by overcoming the inherent limitations of current AI, includes this effort as a central component.
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Tracing the Evolution Medicine 1.0 to 3.0
Professor Han divides the history of human medicine into three separate phases to comprehend the need for this change. The period of antiquated practice known as “Medicine 1.0” was characterized by the primary sources of treatment being the practitioner’s limited personal experience and trial-and-error. As of right now, we are in the “Medicine 2.0” stage, which makes use of evidence-based diagnosis and therapy based on a variety of medical tests. Even if Medicine 2.0 is more sophisticated, it still mostly depends on the subjective interpretation and empirical knowledge of individual physicians.
Han believes that “Medicine 3.0,” or precision medicine, is the way of the future. At this point, clinical judgments will be made based on each patient’s distinct genetic traits, hence lessening the reliance of the healthcare system on empirical medical knowledge through trial and error. However, the amount of data processing needed to achieve this level of precision is currently beyond the capabilities of conventional technology.
The Genetic Data Deluge
Large amounts of human genetic data are the biggest obstacle to Medicine 3.0. Most diseases are influenced by a person’s genetics, which is why similar practices can have such different health outcomes. Heavy smokers can live to 100, whereas nonsmokers can get lung cancer.
Humans have over 3 billion base pairs in their genetic code. Researchers must compare the sequences of hundreds of thousands or millions of people to find clinically useful patterns. Traditional computers cannot do this task due of its exceptionally long processing time.
Qubits and Parallelism
A solution to this “time wall” is provided by quantum computers, which employ “qubits.” Qubits make use of a phenomena called quantum superposition, in contrast to classical bits that are either 0 or 1. This makes it possible for a physical state to exist in several states at once with different probability.
Quantum computers are able to compute numerous variables simultaneously in parallel by utilizing superposition. Because of this aptitude, they are particularly well-suited to resolving the kinds of complex, multivariate issues that characterize human biology. The shift to the data-intensive world of Medicine 3.0 would remain theoretical without this technology.
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Cracking the Code of Long COVID
These quantum algorithms have previously shown promise in a clinical context. A particular method known as “Quantum Walk” was recently used by Professor Han’s team to investigate “long COVID” the lingering symptoms that many infection survivors experience. On February 15, Bioinformatics Advances released their findings showing that the quantum approach exceeded conventional computational methods in speed and accuracy.
The quantum algorithm found illness pathways including neuroinflammation and mitochondrial failure that previous methods missed. Human cells manufacture energy with mitochondria. The scientists found two protein families that govern these organelles, providing doctors new long-term COVID therapeutic targets. This achievement demonstrates that quantum technology is about finding clinically useful outcomes that binary logic would miss, not just about raw power.
Brain Mapping and Infrastructure
Professor Han’s background in complicated biology and computer science puts him in a unique position to bridge the gap between these fields. With the installation of an IBM quantum computer at the university’s Songdo campus in 2024, his long-standing partnership with Yonsei University which started more than ten years ago with research with Severance Hospital has entered a new phase.
Han has his sights set on the human brain, which he believes to be the most intricate biological network in the world. His ultimate research objective is to use quantum computing to implement and analyze the neural network found in the brain. Han hopes to advance medicine beyond its existing binary boundaries by fusing cutting-edge South Korean infrastructure with global knowledge.
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