Research at RSI takes an integrated approach to answering the big, fundamental questions of biology, developing novel tools and technologies to accelerate the pace of discovery, resolving medical unmet needs, and enhancing innate human regenerative capacity to prevent/cure diseases and extend healthy lifespan. RSI has a special focus on using artificial intelligence methods, specifically deep learning and evolutionary algorithms to discover key insights needed for progress.
RSI believes that exploring the interface between the most fundamental research and applied research is most likely to result in scientific and technological breakthroughs. Our innovative synthetic biology artificial intelligence/machine learning oriented approach to regenerative medicine by developing the means to engineer intrinsic regenerative capacity (regeneering) will increase human healthy human lifespan and lead to elimination of serious aging-associated disorders such as Alzheimer’s and cardiovascular disease. Our researchers are interested in effectively using multidisciplinary approaches to understand the basic mechanisms and then design novel effective therapies. All of our research is conducted within the purview with our unique hybrid educational-based research programs.
RSI’s focus on the biology of regeneration and aging presents an interesting and rich context to explore some of the most fundamental outstanding questions in the biological sciences including: What defines living biological systems? Specifically, in hybrid living/non-living systems what constitutes “life”? What is the nature of aging? What features are necessary to ensure unlimited reproduction/replication of biological systems? How do biological “noise” and infidelity in replicative processes contribute to evolution and lifespan? What drives the evolution of complexity? How do biological systems use and encode abstract “information” to drive such processes as pattern formation during development and aging? Regenerative Sciences Institute is developing regenerative biology as a discipline, because of its numerous associated basic questions and the potential for fundamentally changing human health.
RSI’s technology research centers on computational based deep learning and evolutionary algorithm approaches to understanding biological systems, and synthetic biology and materials science, with special interest on developing technologies to engineer cells and genomes, engineer extracellular vesicles, build artificial organelles and cells, and develop micro scale bio-automatons and robots. RSI is especially interested in developing appropriate simulation tools for increasing rational design approaches to accomplish these goals: machine learning and artificial intelligence is playing an ever increasing role in this endeavor.
Our research topics:
For a detailed description of some of the work at our institute, please see the individual research interests of our members.