Collaboration + Technology + Open Science
Our approach to accelerating science and curing disease
The Chan Zuckerberg Initiative’s work in science was founded on a big idea —
To support the science and technology that will make it possible to cure, prevent, or manage all diseases by the end of the century. This is a bold statement — but it’s grounded in the history of biomedical science. To set our aspirations for how far we can advance over the rest of this century, let’s revisit and respect how far we’ve come in the past century.
In 1930, three of the top 10 leading causes of death were infectious diseases: pneumonia and influenza, tuberculosis, and gastrointestinal infections. All are now treatable or preventable with the advent of antibiotics and vaccines. In the 1960s, the Framingham Study established a clear link between high cholesterol, high blood pressure, and heart disease. As a result of that interdisciplinary science, we have new blood pressure medications and statins that have extended heart disease patient lives’ by more than 20 years. In more recent years, AIDS has become a treatable chronic disease with antiviral therapy, and progress in our understanding of the basic cellular mechanisms of cancer has led to a steady 1–2% decrease in cancer deaths per year over the past 25 years. There are many other examples — we have a lot to celebrate.
In each of these cases, advances in basic science led to translational and clinical research and ultimately to changes in medical practice. We think much more can be achieved in the years to come. That’s why we are focusing on investing in a multidisciplinary approach to basic science with a view of what can be accomplished in the next 25, 50, and 80 years. We know that much can be accomplished, but at the same time, we know that we are new players in a strong existing biomedical enterprise. To make a differentiated impact, we must focus our efforts on areas where we can bring unique value and new ideas to science.
We need to learn what the opportunities are. To do that, we engage deeply with the scientific and medical communities, and we frequently hold workshops and meetings with leaders from academic institutions, scientific societies, disease foundations, government agencies, the biotech industry, and other philanthropic foundations. Their guidance, as well as guidance from our Scientific Advisory Board, helps us direct our efforts to make the greatest impact on biomedical research.
A hybrid model
When we look at different philanthropies and foundations, we see two great models that move fields forward. One approach is that of the grant-making foundation. An example of this is the Bill and Melinda Gates Foundation, which supports global health research worldwide. Another kind of philanthropy builds its own research institutions, like the Paul Allen Institute for Brain Science, a research facility in Seattle that studies the brain.
At the Chan Zuckerberg Initiative, we want to fund great research scientists who share our goals and values. At the same time, our origins in Silicon Valley give us special access to state-of-the-art technology, particularly in computational biology and software engineering. We’ve found that working side-by-side with the scientists that we fund, we can build new tools and develop open-source software that can be a tool for scientists to collaborate better and ultimately, to get to their breakthroughs faster. We fund and we build.
In what follows, I want to highlight a few key aspects of our approach, motivated by my experience as both a scientist and, now, leading an organization trying to support and accelerate science.
Collaboration is key
Early in my career, I worked on a gene called NEU/HER2 that caused brain cancer in rats. Subsequently, other researchers found that the same gene is a vicious player in human breast cancers, where abnormally high levels of HER2 in cancers makes them more aggressive. For years, scientists around the world studied HER2, first in animals and then in humans. That work progressed to a drug — an antibody against HER2 — and then to clinical trials, where physicians worked alongside biotechnologists to test it in patients. Eventually, their hard work led to a targeted drug, Herceptin, directed against the HER2 alteration that made breast cancer cells grow, and transforming one of the deadliest cancers in the world into one of the most treatable. As a scientist who helped identify HER2, I was just one link in a massive chain of people working together to take this groundbreaking work from bench to bedside. We succeeded because we were open to trying new ideas and listening to new perspectives — within and across fields.
Experiences like these help shape our approach to solving disease at CZI. Progress accelerates when interdisciplinary teams work together — that’s why we support open, collaborative, and networked models of research. The teams include experimental scientists, computational scientists, physicians, and software engineers. A special feature is ongoing collaborations between scientists in the research community and our computational biology and software teams here at CZI, which keeps us close to the problems we’re helping to solve.
One example of our approach to collaboration is the Biohub. The Biohub is a new kind of research site that brings together three of the great scientific institutions in the world — UCSF, Stanford, and Berkeley. These three groups also happen to be in very close proximity to each other, so there’s an opportunity to bring these groups together to spread ideas back and forth between these institutions and communities.
The Biohub operates independently of CZI — but we fund them and collaborate. The Biohub’s co-presidents are Joe DeRisi and Stephen Quake, two people who exemplify our ideas about collaboration between institutions and between scientists and engineers. Steve is best known for helping to develop the noninvasive blood test that’s used to diagnose Down’s Syndrome without amniocentesis. Joe is known for helping to discover novel viruses, including the Coronavirus that caused SARS. Many of the research projects that are underway at the Biohub are related to the interests and expertise of these two leaders — for example, infectious disease discovery through Joe’s research and single cell technology from Steve’s interests.
We’re not limited to one region, though. For example, we’re launching a Neurodegeneration Challenge Network, which aims to bring interdisciplinary networks of scientists, clinicians, and engineers together so they can generate and test new approaches around one big problem — increasing understanding of the fundamental biology of neurodegenerative disorders. We have applicants from around the world — and we’re challenging ourselves to think of ways to get those dispersed groups to work together for greater success. We’re full of ideas on how to support new incentives, rewards, and career paths for collaborative research.
Designing transformative technologies
One thing I hear again and again is that scientists are only as good as their tools. At CZI, we see an opportunity to design new tools so our experimental partners can push forward even more quickly. Our support of the Human Cell Atlas project is one example. The Human Cell Atlas is a global consortium that aims to map and characterize all human cells. It will take years to complete, but once there, the atlas will be a fundamental resource for scientists, allowing them to better understand human health and to diagnose, manage, and cure disease. As part of this effort, we are working together with international genomics leaders from the European Bioinformatics Institute, the Broad Institute, and UC Santa Cruz to formulate, fund, and jointly build a data coordination platform that will enable data sharing across researchers and research institutes.
At the same time, we’re also building tools to help scientists discover knowledge that already exists. In biomedicine, there are over 4,000 papers published per day. I can’t read them all. And neither can anyone else, and so we need tools and technologies to parse all this information in an intelligent way. One such tool we are working on is Meta, which uses artificial intelligence to analyze and organize biomedical papers for readers. With Meta, scientists will be able to follow advances in their fields in real time and spot emerging trends at the intersections of fields. We’re still very much in progress, but when it’s ready, Meta will be made freely available to all researchers, and we will openly share its methods and exemplar datasets through publications and code.
One of the driving principles behind everything we do at CZI is listening to and learning from the communities we serve, because no one understands these problems more than the people who experience them every day. That’s why our computational biologists and software engineers work with scientists on the ground to identify challenges and build open-source tools for analyzing, visualizing, and sharing data, using cutting-edge engineering, data science, machine learning, and cloud computing approaches. Sometimes this means developing new tools. Other times, it means building consensus around formats, standards, or benchmark datasets. An example of an open-source repository containing our current work around standardizing analysis pipelines for image-based transcriptomics can be found here.
Open science, faster progress
We believe that sharing data and results, open-source software, experimental methods, and biological resources as early as possible will accelerate progress in every area. That’s why we support platforms like bioRxiv, which enable researchers to share and receive feedback on preprints before they are submitted to journals. In many cases, we require researchers to deposit manuscripts as preprints before peer review to communicate results to the scientific community more quickly.
We release software developed by our own team and our funded partners under maximally permissive open-source licenses, and develop software collaboratively in the open through sites like GitHub. We do not request rights to IP developed by our partners, and any IP generated by a CZI-supported investigator or as part of a CZI-funded research project must be made freely available for all academic and non-commercial uses — including pre-commercial use by for-profit entities.
We support open sharing of data because it lets scientists build on each others’ work to make new discoveries, faster. This can dramatically accelerate the pace of discovery, and in turn, our understanding of health and disease.
We are just getting started
We are a new organization and we have a lot to learn. We are trying to make an impact by bringing new opportunities to bear on scientific problems, particularly those that come from new technology. We believe that in every field, especially in science, talented and motivated people move the field forward. By getting these talented people together and providing them with new tools that are reliable, robust, scalable, and shareable, we hope to enable new discoveries and accelerate the field.
To learn more about work in science, visit our website or follow us on Twitter. To learn more about our technology team, follow the CZI technology blog. To stay updated on funding opportunities, sign up for our mailing list. And you can always reach us at science@chanzuckerberg.com.
Oh, did I mention we are hiring?
Cori Bargmann, Head of Science
Cori Bargmann, an internationally recognized neurobiologist and geneticist, leads our science work. Dr. Bargmann is also the head of the Lulu and Anthony Wang Laboratory of Neural Circuits and Behavior and the Torsten N. Wiesel Professor at the Rockefeller University in New York. Dr. Bargmann is a member of the National Academy of Sciences and the American Philosophical Society. She received the 2012 Kavli Prize in Neuroscience and the 2013 Breakthrough Prize in Life Sciences, among many scientific honors. She also co-chaired the National Institutes of Health committee that set goals and strategies for President Obama’s Brain Research through Advancing Innovative Neurotechnologies (BRAIN Initiative). Dr. Bargmann is a former Howard Hughes Medical Institute Investigator and holds a Ph.D. in Biology from the Massachusetts Institute of Technology.
