Boris Farber, Dual PhD, ScD, TRIZ Master

Advancing Personalized Medicine Through AI and Dynamic Drug Innovation

Dr. Boris Farber and his team are pioneering next-generation dynamic, self-adaptive, self-assembled medical drug with variable structure, design. Leveraging a unique blend of expertise in mathematical modeling, artificial intelligence (AI), and the Theory of Inventive Problem Solving (TRIZ), grounded in Patterns of System Evolution, Dr. Farber has dedicated his career to developing therapeutics that adapt to individual patient needs. His work delivers highly effective, tailored treatments for some of the world’s most challenging medical conditions.

With a distinguished career spanning over four decades, Dr. Farber has developed a universal approach to creating drugs that protect kidneys from nephrotoxic agents, addressing a critical unmet need in modern healthcare. His innovative research integrates advanced mathematical modeling, bioengineering, and TRIZ methodology to produce dynamic, self-adjusting therapeutics customized for individual patients. His contributions include hundreds of inventions, numerous scientific publications, and international awards, establishing him as a visionary in translating scientific discovery into impactful medical solutions.

Educational Background

Dr. Farber holds dual PhDs in Biomedical Systems and Robotic Systems, a Doctor of Sciences (ScD) in Control in Medical and Biological Systems with a specialization in Mathematical and Computer Modeling, and a Full Professor Diploma. His interdisciplinary expertise is enhanced by professional diplomas in Pharmaceutical Chemistry, Pharmacognosy, Pharmaceutical Biotechnology, Pharmaceuticals and Drug Development, Microbiology, Artificial Intelligence Technologies, Neural Networks, Deep Learning, Machine Learning, Big Data, Data Science, Applied Physics, and Applied Mathematics. This unparalleled educational foundation drives his transformative contributions to healthcare.

Professional Achievements

Over his illustrious career, Dr. Farber and his team have made groundbreaking contributions to pharmaceutical innovation. As the sole TRIZ Master in pharmaceuticals, he has applied TRIZ principles for over 35 years to transform conventional medicines into dynamic, self-regulating therapies. His pioneering work has led to the development of the first dynamic, self-adaptive “quasi-living” drugs, including MoLRx for cancer treatment, Albuvir for viral infections, adaptive insulin, Dipasol for wound healing, and the hemostatic agent Gemma. These therapies, which adjust in real-time to individual patient needs, have demonstrated high preclinical efficacy, setting a new approach in personalized medicine.

Dr. Farber’s universal approach to developing nephroprotective drugs safeguards kidneys from nephrotoxic medications without compromising efficacy, addressing a critical healthcare need. With over 215 patents granted globally—including 10 U.S. patents for dynamic drugs—and more than 500 scientific publications and books, his innovations span dynamic anticancer antisense microRNA, antiviral oligopeptides, stem cell growth stimulants, and antimicrobial formulations for multidrug-resistant strains. His work also extends to applications in cosmetology and food science.

Leadership Roles

As CEO of TRIZ Biopharma Innovations LLC (New Jersey) and TRIZ Biopharma International LLC (New York), Dr. Farber leads interdisciplinary teams that merge AI-powered simulations with TRIZ methodologies to achieve breakthroughs in drug design. As Principal Investigator on multiple projects, he has spearheaded innovations such as antisense oligo-RNAs for targeted cancer therapy and antiviral peptides with remarkable efficacy against different viral strains. His development of universal nephroprotective drugs further addresses critical unmet needs in healthcare.

Vision and Collaboration

Dr. Farber’s vision for the future of medicine is rooted in the synergy between dynamic drug design and artificial intelligence. With experience in AI dating back nearly 40 years, including early work on expert systems for biomedical diagnostics and therapy, he continues to explore new ways to enhance drug development. Today, Dr. Farber values collaboration with professionals in AI and drug design, recognizing that partnerships are key to advancing personalized medicine. His ongoing work is focused on developing adaptive treatments that can better meet individual patient needs, and he welcomes opportunities to work together to further these goals.

Awards and Recognition

Dr. Farber’s contributions have earned him membership in nine prestigious scientific academies. He has received numerous accolades, including the Paul Ralph Ehrlich Medal, Otto Heinrich Warburg Medal, Nikola Tesla Gold Medal, and the European Academy for Natural Sciences Award for his advancements in TRIZ-based drug development. These honors reflect his dedication to advancing healthcare through rigorous science and innovative problem-solving.

Conclusion

In his Nobel Congress address, Pioneering Adaptive Medicine: A Potential Collaboration with AI Dr. Farber emphasized the transformative role of AI in realizing a 300-year dream of truly personalized medicine. His TRIZ-based methodology, combining mathematical precision, adaptive treatments, and extensive AI experience, provides groundbreaking approaches to addressing challenging diseases, redefining pharmaceutical innovation” https://www.youtube.com/watch?v=c9rfPmncy1U&t=76s

For a deeper exploration of his work in personalized medicine, see his presentation Dr. Farber’s unique approach continues to offer hope and healing to patients worldwide, paving the way for a new era in healthcare https://www.youtube.com/watch?v=eO1D6ER3-RY).

Memberships

  • American Society for Pharmacology and Experimental Therapeutics
  • American Society for Microbiology
  • American Chemical Society
  • Association for the Advancement of Artificial Intelligence
  • American Mathematical Society

Works and publications:

https://www.linkedin.com/in/dr-boris-farber-0309b6121/

https://orcid.org/0000-0001-9166-1274

https://www.researchgate.net/profile/