The Institute for Network Medicine (iNetMed) unites several research disciplines to develop disruptive solutions, transform life sciences, and technology and enhance the quality of human life. Founded in 2018,
iNetMed houses three centers, which are collaboratively developing new,
human-centered approaches to drug discovery and technological innovation.
Human-Centered Drug Discovery: The world’s drug discovery machinery has a tragic paradox. Academic labs, pharmaceutical companies, and biotechs have better tools than ever before: supercomputers, genomic sequencers, PCR. Despite these incredible technologies, the drug discovery success rate is lower now than it was in the 1970s. There are two reasons for this: First, the era of ‘big data’ has not been translated into effective drugs, as was initially expected. Second, current approaches for target discovery rely far too much on inbred animal models (mice, rats, etc.), and drugs that work wonders in these animals. These pre-clinical studies fail far too often, then too late in clinical trials, making the process wasteful and imprecise. To overcome these challenges, iNetMed’s two Centers, The Center for Precision Computational System Network (PreCSN) and HUMANOID Center of Research Excellence (CoRE) are working collaboratively to provide an end-to-end new paradigm and platform for drug discovery that begins with target identification (at PreCSN) and ends with target validation in human disease models (at HUMANOID).
Technological Innovation: Our endless quest for smarter, faster, better, and more human-like machines, the ‘march of the neural networks’ has reached its limits. Even at ~137 B sized outrageously large artificial neural networks, we are nowhere near emulating human intelligence. Among the solutions proposed to get us there is making it even larger—100 Trillion neurons in the neuronal networks. However, most engineers remain skeptical that size expansion may melt the silicon chips due to insurmountable heat but may still fall short of the human-like decision-making, learning, and adaptation that is required to get us to the
level of desired automation in intelligent machines. To solve these problems, iNetMed has established The Consortium for Cell-Inspired Systems Engineering (ConCISE), whose leadership is engaged within an extensive collaborative framework with other institutes on the UCSD campus, such as the Institute of Engineering and Medicine (IEM).
centers of transdisciplinary science:
The Center for Precision Computational Systems Network (PreCSN),
is radically changing how we sift through big data to find meaningful information. As the computational arm for the
iNetMed’s drug discovery pipeline,
PreCSN develops novel machine learning algorithms to drive precision drug discovery.
of Research Excellence (CoRE),
is the translational arm for
iNetMed’s drug discovery pipeline, bringing a new level of personalization into disease modeling and clinical trials, providing the ability to test the efficacy of therapeutics in Phase “0”.
The Consortium for Cell-Inspired Systems Engineering (ConCISE),
is building a bridge between the life sciences and computer engineering to develop a novel paradigm for enhancing artificial intelligence (AI). As the
iNetMed’s engineering arm,
ConCISE is building virtual human cells to better understand how they degenerate or go rogue, to determine how we can manipulate cellular communication, as well as engineer smarter machines that can sense, decide, act, learn, and adapt – the way cells do.
name was no accident. Each component
synergizes with each other through a vibrant network of transdisciplinary projects.
PreCSN provides better drug targets for HUMANOID, as well as
guides the design and
ConCISE creates new computing tools to
cell’s communication network, which in turn informs
PreCSN may prioritize targets for HUMANOID to test.
computer science and systems engineering,
cell and molecular biology,
biochemistry and structural biology, high-throughput omics,
mathematics, chemistry, physics, and translational medicine will identify novel drug targets
Combining life sciences and computer engineering experts on one team provides unique opportunities to understand biology’s incredible complexity. By looking at biology from multiple points of view, we can expose fundamental principles and exploit that knowledge to solve grand challenges in both biomedical and physical sciences and engineering.