In this podcast, we have with us Yan Leyfman, MD. We will discuss and ask Dr. Leyfman about his views regarding how medicine and medical research will look in the future and the role of Artificial Intelligence and Personalized Medicine in disease treatment and the future of medicine.
Table of Contents
Yan Leyfman, MD, is a medical doctor and a passionate researcher. His areas of command and interest are immunology, and oncology, i.e., the study of cancer. He is a survivor of the Chernobyl Nuclear Disaster in the USSR, and this incident deeply connects with his career and life ambitions.
● Dr. Leyfman’s Career Inspiration and His Services in COVID-19 Pandemic
● What Factors Hinder Progress in Medical Research?
● Role of Artificial Intelligence (AI) in the Future of Medicine
● What Does the Future of Personalized Medicine Look Like?
● What Could Be the Next Breakthrough in Medicine?
● COVID-19 Pandemic for the Future of Medicine
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Dr. Yan Leyfman was born some eighty miles from the place where the Chernobyl disaster happened. Where there was the slightest possibility of surviving, he did. The aftereffects of the nuclear accident did not let anyone live in good health. Dr. Leyfmann tells us that he too had some strange illness that nobody could diagnose in his childhood. Doctors came from all over the world to examine him. He was that “unique case”. With severe itching, diffuse lymphadenopathy, and cysts all over his body, he would lie in pain. This experience of misery was a blessing that converted to his groundbreaking career. He started research at the age of 15 to pay back to the medical community and the patients, of course. Yan has done excellent work in immunology and oncology, with his most recent topic of research being COVID-19. “It almost seemed like deja vu”, says Dr. Leyfman, talking about the pandemic where he saw people helpless again. In pursuit of discovering something that could be done to arise from the hopelessness, he worked in the global COVID-19 task force. Dr. Leyfman was given a unique opportunity to lead the immunology division with a team of MDs and PhDs. Within a few weeks, they proposed the first cohesive mechanism of COVID-19 and the efficacy of a promising treatment against it. The findings are still valid today. Lately, Yan has contributed to the literature regarding the interplay between cancer and COVID-19.
Speaking about the development of novel drugs, Dr. Leyfman says three significant factors usually become a hindrance. There are more, but funding, experience, and regulations play an essential role.
This is more of a problem for smaller companies especially. Investors want to put in their money in projects that have data-based solid outcome predictions. For example, if a company comes up with an innovative idea of some novel drug that isn’t backed up by robust clinical data and research, investors are likely to shy away from that project.
“While someone may have conceived the product at the bench, going from a Ph.D. researcher to a CEO of a large pharmaceutical company can be a huge jump, and that may not fit everyone”, says Dr. Leyfman describing the importance of relevant industrial experience. He says that everyone in a company should know their strengths and weaknesses. Everybody may not be capable of translating his experience in one field into another. And this is one of the reasons there is this incoherence between research and the actual production of novel and innovative drugs.
Another thing that may scare away the investors from putting in the capital is the nature of regulations. Dr. Leyfman gives an example of the current innovative therapies that target the gut microbiome. There are currently no rules and regulations that govern the’ possibility of formal approval for such products. So, there is unpredictability regarding these kinds of new ideas. The regulations may turn in or against their favor in the future; who knows. So, this is one of the factors that can hinder the progress of novel drug development and research.
Yan Leyfman believes that AI is an up-and-coming technology that can speed up drug discovery and maximize the efficiency of development processes. For example;
● It can be a powerful screening tool in drug discovery. It is said that from 10,000 molecules being considered for a drug, only one makes it successfully to the market. Using AI, we can narrow down the best drug candidates. Thus, it can magically potentiate and speed up the process.
● When narrowed down, Artificial Intelligence can compare the efficacy and other attributes of different drug candidates.
● AI can even propose solutions for refining drug treatment, management, or therapy.
● It can simulate disease processes that occur in real, living bodies. That can also help us understand drug interactions and interventions more clearly.
● It can automate some parts of the drug development and testing process. AI can help with research tasks within companies and within the academic sector as well.
At this time, still, clinical studies are the gold standard. “The human body is very complex. There are lots of confounders and variables that the virtual environment, at least in today’s time, may not be able to simulate or anticipate,” explains Dr. Leyfman. This is a barrier that AI poses currently. It can simulate anything in a virtual realm, but that is not necessarily 100% applicable in a complex human body. The final decision is still based on actual experiments carried out in clinical trials. For instance, one drug may be an ideal candidate in an AI simulation, but it may fail due to some factor when given to humans. However, the benefits still are huge, and AI is here to stay.
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Personalized medicine deals with therapies that are tailored to a particular patient’s unique gene profile. The trend towards personalized medicine is on the rise rapidly. The rationale is that every patient has got a unique gene profile, different from others. Thus, one patient may respond to a specific treatment, but another won’t. That is because of genetic makeups that are different. For the same reason, one disease can manifest in various forms in different people. Dr. Leyfman gives the example of CAR T-Cell Therapy. It is a personalized immunotherapeutic technique for cancer patients. T-Cells from the patient are taken. They are genetically engineered to kill the cancer cells specifically and then reinfused into the body.
The biggest challenges in moving towards personalized medicine are cost, affordability, and not having promising data for the investors. We know that the pharmaceutical industry works on the mass-production model. They manufacture drugs and products on a large scale. Obviously, if pharma companies begin to make personalized products for everyone, that is simply not easily possible. As a result, the affordability and cost factor comes in. For example, the cheapest CAR T-Cell Therapy in the US is $375,000 at the moment. So, much work is still needed to be done to tweak the approaches.
Dr. Leyfman says that many breakthroughs in medicine often begin in the field of oncology, and then they are translated into other areas of medicine as a whole. He’s hopeful to see the next breakthroughs happening and contributing to the future of medicine:
● Precision medicine will play a more significant role than ever before. Combined with Artificial Intelligence (AI), it will help boost up diagnostics and therapeutic interventions.
● Immunotherapies will play a more prominent role in cancer treatment than before. They are likely to become second-line and hopefully first-line therapy for some cancers also.
● Various medical subspecialties will growingly use cellular therapies to offer longer-lasting solutions, like stem cell therapy is an example.
● Gene therapies can be seen playing a more significant role in treating genetic conditions like thalassemia, sickle cell anemia, and other diseases.
● Knowledge regarding the gut microbiome is expanding rapidly, and its application and therapeutic use are gaining immense popularity. This is likely to grow more.
We are not yet out of the pandemic, but still, it has taught us many lessons till now. In medicine and therapeutics, we have learned the importance of industry and academia working together. These fruitful coordinations have paved the way for the rapid development of beneficial products. COVID-19 vaccines and monoclonal antibodies are prime examples. In addition, we have learned that sometimes, removing some red tapes can make promising therapies enter into the clinical trials quicker. With drug development and regulatory bodies working together with mutual understanding, we can improve the quality of rules and regulations and make it easier for beneficial treatment to reach the patient much quicker.
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Tagged as: Medicine, AI, Drug Discovery.
Yan Leyfman, MD, is a medical doctor and a passionate researcher. His areas of command and interest are immunology, and oncology, i.e., the study of cancer. He is a survivor of the Chernobyl Nuclear Disaster in the USSR, and this incident deeply connects with his career and life ambitions.
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