Imagine: you get sick with gastritis and go to a physician, who first treats not you, but a digital replica of your stomach to ascertain how medications will act and to select the optimal treatment approach. Novel remedies are being created with the aid of AI and delivered straight to the affected tissues, so adverse effects might entirely become a thing of the past. New developments that will transform treatment and drug creation methods are covered in this TASS feature.
This article appears as part of the “Vision of the Future” special project—it focuses on technologies that exist presently and will keep rapidly advancing in the next 10–15 years, altering people’s lives. Exclusively for TASS, a team of researchers from the HSE ISSEK Foresight Center selected the main trends: these include neuroimplants, digital organ surrogates, and even self-repairing materials. To achieve this, the iFORA big data analysis system examined over 50 million documents: reports from major corporations, expert opinions, and scientific studies published between 2015 and 2025. TASS discussed the AI data with specialists and highlighted key trends across various domains—from the entertainment industry to healthcare.
Revolution in Healthcare and Pharmaceuticals
Healthcare is gradually changing under the influence of technology: artificial intelligence already “works” as a doctor’s assistant—for instance, helping with paperwork and note-taking during patient consultations. Currently, every third physician in the Moscow region utilizes AI—most often for document analysis, interpreting test results, researching medical literature, and beyond. Artificial intelligence is also transforming diagnostics: it analyzes MRIs and CT scans, X-rays, heart vessel images, and even detects Alzheimer’s disease—according to the Ministry of Health, AI for medical image analysis is employed in 85 regions across the nation.
Methods for medical experimentation are also being modernized: whereas experiments were once conducted either in test tubes—in vitro—or on living organisms (insects, animals, or humans)—in vivo—a new environment appeared in 1989—in silico, “in silicon.” This term refers to experiments conducted in computer simulations. Possessing sufficient insight into a biological or chemical process within the human body, scientists can replicate it using special software and complex mathematical models.
For example, Russian researchers from Sirius University developed a system for treating hypertension. For this purpose, they created “copies” of two systems that influence the regulation of arterial pressure in the body: the cardiovascular and renal systems.
Using the program, one can calculate how various medications will affect a real patient and, based on this, select the best therapeutic approach. Specialists are also developing a multilevel brain system to combat epilepsy.
Digital Twins Guarding Health
Such virtual counterparts are currently being tested but may become the foundation for personalized medicine in the future. To create a person’s digital twin of an organ or system, it is sufficient to upload the medical history, analysis data, and individual patient characteristics into the program. Naturally, knowing absolutely everything about a patient and creating a perfectly precise model is impossible: there are numerous variables within the body that influence disease progression.
Imagine you are a physician: the patient has hypertension. We know the patient’s height and weight, but some information is missing—for example, data on the elasticity of their blood vessels. To select treatment, the physician tests a drug not on one virtual patient but on an entire cohort of digital twins—up to 500 units: all of them will have the same height and weight, but varying vessel elasticity. Ultimately, the doctor will choose the medication that showed the best outcome in simulation and proved effective across all variations.
Furthermore, the doctor will have detailed information: how much the drug lowered the pressure, whether side effects are a concern, and so on. Sometimes, several medications are used for treatment—such complex organism interaction can also be modeled. It is also realistic to forecast future intra-organism changes. “Virtual patients will allow us to see how individual metrics, such as blood pressure, will change with age—in 5, 10, and even 20 years,” explains Fedor Kolpakov, scientific director of the “Computational Biology” area at the Sirius University Center for Genetics and Life Sciences.
Complex mathematical equations underpin these digital twin models—they are used to describe bodily processes. Moreover, diverse models can be interconnected, Kolpakov explains. One group of scientists develops a digital twin of the heart, a second one for the kidneys, a third for the stomach, and these can be combined like Lego pieces to ultimately construct increasingly sophisticated systems.
Where the Difficulty Lies
Years of development are required to create each digital twin of a specific organ or system. Yet, even so, simulating every single process in the human body is virtually infeasible—it is that intricate. Furthermore, available computing power, at least currently, would be insufficient for this. That is why specialists do not work on creating an entire digital patient but rather model specific organ systems for treating particular ailments.
Other Healthcare Trends
As Artur Kadurin, director of the AI Drug Design Center at AIRI Institute, notes, artificial intelligence is already employed in designing drug structures, predicting their physicochemical and biological properties, and selecting the drug target—the structure in the body on which the drug’s action is focused. In the near future, drugs designed with AI assistance will be accessible to the public. “The most successful molecules created this way have already reached the third phase of clinical trials, meaning they will soon reach patients,” the expert states. Additionally, using AI helps reduce the cost of preclinical research phases and “accelerates drug creation by two to three years compared to the traditional approach,” Kadurin points out.
Among promising healthcare trends, experts also highlight drug delivery within the human body—technologies that enable medications to reach affected cells or tissues directly. Since drugs often lack selectivity and act systemically, they cause undesirable effects in addition to their therapeutic action. Such technologies are already employed, for instance, in cancer therapy. According to Philipp Maksimov, head of the Laboratory for Structural and Functional Research of Innovative Antitumor Agents at MIPT, various targeted delivery methods will improve in the near future: from specialized antibodies that act only on specific cells, such as cancer cells, to nanoparticles that can “encapsulate” a drug to slow its clearance from the body. “Different targeted delivery techniques work better for different diseases, so it is likely that various methods will be used concurrently,” the specialist explains. Maksimov notes that drug targeting mechanisms can also be utilized for diagnostics—this area is under active investigation. For example, specialized antibodies already help physicians identify recurring tumors after cancer treatment.
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