Rare gifts: Fellows Friday with C Jimmy Lin

CJimmyLin_TED_QA

Millions of people, many of them children, suffer from “orphan” diseases — illnesses so rare that no infrastructure exists to investigate or treat them. Now C Jimmy Lin’s Rare Genomics Institute puts hope and empowerment back in patients’ hands by connecting them with researchers, doctors and community support, and a crowdsourced funding platform.

What is the mission of the Rare Genomics Institute?

There are over 7,000 rare diseases, and most of them are not being actively researched. Neither do they have patient organizations helping them. So what happens to most of these patients is that they go from place to place trying to find a diagnosis or seek help. The current medical establishment is not set up to do this because, number one, the medical knowledge is not there because the diseases are so rare; and, number two, there’s no infrastructure to help research these rare diseases.

Is this a cost-related issue?

For many of these diseases, there are challenges from three sides. For academics, there is little funding to study these diseases. From the business perspective, there is too small a market. For awareness, too few are affected to build an advocacy campaign. So most of these patients have had no way of being helped. But one of the really cool advances in biology these days is called personalized medicine. What people are thinking about more and more is creating tailored therapy for different diseases. So even for cancer — even a specific type of cancer — every person is treated individually. This creates a great opportunity to look at rare diseases individually. Rare Genomics helps patients set up individualized research projects to understand their disease, from helping them design science experiments and connecting them to the right researchers, but also raising funds for it, which is also very needed. So RGI offers an online crowd-funding platform. And that’s in a nutshell what we want to do — offer all the resources required to democratize research for rare diseases.

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RGI helped diagnose Robert with dystonia 16. He is the 9th case in the reported literature. Photo: Jeneva Stone

How did you come to straddle the worlds of medical research and philanthropy?

There have always been two strands of my life. One is I’ve been really passionate about science and innovation. The people I admired growing up were people like Thomas Edison, Albert Einstein, people who had been able to transform what we know about science. That intrigue of science has always been a driving factor with me. Secondly, there’s more of a compassionate philanthropic side that I see where I could make an impact — not only for science, but to help people suffer less, to offer more cures and make the world a better place. So biomedical research has been a very natural place where these strands come together.

During my medical and graduate training, I saw a great need within the rare disease community, where there is no medical research — nor medical help — for these patients. So, during my graduate training in cancer, I slowly transitioned and worked, starting with genomics, in the hopes of being able to bring science and innovation and discoveries to a community that really needs it.

Did you become a computational geneticist specifically to study rare diseases?

No, I did that training mostly within cancer. Computational analysis shares two of my other loves: big data and computers (I’ve been programming since I was in elementary school) and biology. Computation analysis was a marriage of those two. That’s a very common theme of a lot of my life — I sort of live between boundaries of fields, seeing how different fields interface, and potentially provide a conversation that would result in new ways of thinking about them.

What does a computational geneticist do, and how does that work dovetail with rare disease research?

Within the last decade or two in the generation of biologic information, it has been easier and easier to create larger and larger datasets. Biologists traditionally have not been the people to deal with large datasets. So there has been an influx of computer scientists, mathematicians and statisticians entering this field. But it’s crucial to understand not only the math and the computer science to crack the data, but the biology behind it. There’s now a great need for people with a background in both biology and big data, to make sense of it. I’m now trying to take that knowledge into rare diseases.

To read the full interview, visit the TED Blog >>>

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