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Artificial Intelligence
The Potential of AI and Nanotech in Precision Medicine
Novel liver cancer drug delivery combines AI, MRI, and magnetic microrobots.
Updated February 23, 2024 Reviewed by Jessica Schrader
Key points
- New technologies are increasing health care and precision medicine capabilities.
- A team of scientists have successfully developed a novel way to deliver precision oncology.
- The capabilities of AI machine learning could soon transform science-fiction concepts into reality.
Innovative technologies are bringing new capabilities to health care and precision medicine that once would be considered in the realm of science fiction. In 1966, the science-fiction film Fantastic Voyage told the story of a team of scientists and their submarine vessel who were shrunken to about the size of a microbe and had 60 minutes to find and treat a blood clot after being injected into the bloodstream before they return to their normal size. It was groundbreaking sci-fi that inspired Isaac Asimov to pen a book inspired by the screenplay, launched the late Raquel Welch’s movie career, and garnered Academy Awards in 1966. Fast forward over half a century later, and the concept of targeted, miniaturized drug-delivery agents to treat potentially fatal medical conditions via injection into the bloodstream is emerging as a scientific reality, only now with microrobots.
A team of Canadian and Shanghai-based scientists have successfully developed a novel way to deliver precision oncology. A new study published in Science Robotics showcases a novel precision oncology approach for treating liver cancer that has been developed using injectable magnet-guided microrobots and artificial intelligence (AI) machine learning.
By 2040, an estimated 1.4 million people worldwide will be diagnosed with liver cancer, which is an over 55% increase during 2020-2040 according to the "Global burden of primary liver cancer in 2020 and predictions to 2040" report published in the Journal of Hepatology. Liver cancer was among the top three most fatal cancers across 46 countries and among the top five most fatal cancers in 90 countries per the same report. An estimated 28,000 Americans die from liver cancer yearly and Liver and Intrahepatic Bile Duct cancer was the sixth leading cause of cancer deaths in America in 2020, the U.S. Centers for Disease Control and Prevention (CDC).
Liver cancer is cancer that originates in the liver, a vital organ responsible for filtering waste and toxins from the blood, producing bile for digestion, removing old red blood cells, producing blood clotting substances, storing nutrients such as glycogen and vitamins, and metabolizing fats, proteins, and carbohydrates according to the Cleveland Clinic. Risk factors for liver cancer include diabetes, obesity, smoking, cirrhosis, alcohol consumption, non-alcoholic fatty liver disease, ingestion of aflatoxin, hepatitis B (HBV), hepatitis C (HCV), and hemochromatosis per the CDC.
The researchers for the current study used a combination of a balloon inflation system, an MRI-compatible microbot injector, and a clinical MRI to maneuver magnetic microrobots through the hepatic arteries into the target lobe of pigs. Approximately 2,000 microrobots were injected per pig.
The biocompatible robots are made of magnetic iron oxide nanoparticles coated with carbon-12 bisphosphonate. Carbon-12 makes up nearly 99% of carbon on Earth, with carbon-13 consisting of the remaining 1%, and carbon-14 occurring in one out of a trillion carbon atoms according to the Earth System Research Laboratories at the National Oceanic & Atmospheric Administration. Stable isotope carbon-12 comprises nearly all of natural carbon, and has six protons, six electrons, and six neutrons. The mass number of 12 is due to the combined number of protons and neutrons.
Blood flow and gravity impact the accuracy of drug-delivery microrobots in arteries. The researchers created an AI algorithm to calculate and predict the ideal body rotation angles to target the liver lobes so that gravity will increase, not decrease, the delivery accuracy.
“Here, we present an algorithm to predict the optimal patient position with respect to gravity during endovascular microrobot navigation,” wrote the team of researchers with affiliations with the Université de Montréal, Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM), Université de Nantes, Shanghai University, University of British Columbia, Polytechnique Montréal, and McGill University.
The scientists report an increase in navigation accuracy, ranging from 1.7 times up to 2.6 times, using the AI algorithm for positioning of the pigs compared to the controls.
With this successful proof-of-concept demonstrated, the researchers then ran simulations with an anatomical map of human livers on 19 human patients with hepatocellular carcinoma (HCC), the most common liver cancer.
“In more than 95 percent of cases, the location of the tumor was compatible with the navigation algorithm to reach the targeted tumor,” stated Université de Montréal Professor Giles Soulez, MD, MSc, FRCPC, in a release by the CHUM Research Centre. Other co-authors include Ning Li, Phillip Fei, Cyril Tous, Mahdi Rezaei Adariani, Marie-Lou Hautot, Inès Ouedraogo, Amina Hadjadj, Ivan P. Dimov, Quan Zhang, Simon Lessard, Zeynab Nosrati, Courtney N. Ng, Katayoun Saatchi, Urs O. Häfeli, Charles Tremblay, Samuel Kadoury, An Tang, and Sylvain Martel.
The study demonstrates proof-of-concept that the predictive capabilities of an AI algorithm can be effective in improving the guidance of microrobots for targeted drug delivery to advance health care and precision oncology. We live in remarkable times where the capabilities of AI machine learning may transform science-fiction concepts into reality in the not-so-distant future.
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