The scientist who co-created CRISPR isn’t ruling out engineered babies someday

JD: It doesn’t really make sense to me, [but] I’m glad we have 45 issued patents, we have 40 pending patents, all in the US. And our 30 European patents are not affected by the ruling. And honestly, look, I’m continuing my research.

AR: I’ve always thought that the root of the patent fight is not about money. My own reading of why it was fought so vigorously was that it was not on commercial control but on credit,Who did science,And truth.

JD: That’s your guess. That’s hard to say, isn’t it? I don’t know what the motivation of others might be, obviously, it would be appealing. Obviously, we do not agree with the decision. And obviously, 30 countries and even the Nobel Prize committee don’t agree, if you’re talking about who discovered what, before.

AR: What does it tell you about how the patent system works, that one person can accept a Nobel Prize but then the patent goes elsewhere? Should those people understand?

JD: That doesn’t really make sense to me. I don’t know if it makes sense to others. I don’t think there is much question in the scientific community about what happened.

AR: You are the subject of a book by Walter Isaacson, a biographer of Steve Jobs and Leonardo da Vinci. How did it feel to participate in your biography?

JD: Polite and a little scary, if I’m honest. Although I have to say that I was lucky that a talented person like Walter was interested in the story, because he is a wonderful writer. He did a great job trying to capture all of our feelings about being part of this wonderful transformation with CRISPR.

AR: You recently became the chief science consultant for a Wall Street firm called Sixth Street. What are you thinking of doing there and why did you take that role?

JD: I’m excited that at Sixth Street we can identify the right teams, the right opportunities, the right opportunities where lending can really boost science and business opportunities. One area where I think there is a lot of potential is using machine learning to analyze data coming out of CRISPR. We know that one of the important opportunities in the future with CRISPR is to understand genomics, which means the function of genes. And honestly not individual genes but a whole set of genes and pathways and a wide variety of cells. The types of data that come from those efforts clearly contain large amounts of information, most of which are subtle. And so mining those types of data sets using machine-learning algorithms, I think, would be very powerful. You can imagine using this type of strategy to understand the genetics of the disease આપણી our individual sensitivities અને and to identify new therapies.

AR: I’ve always regarded you as a scientist’s scientist. I once saw a picture of you leaning on a student’s shoulder, and you are in my mind. But this is telling you to do something different. Why do you think you can be good at choosing techniques for commercial investment as opposed to the most interesting scientific questions?

JD: I love science, and my best days are when I lean over a student looking at data in a lab. But I appreciate the fact that CRISPR will need real capitalization of the right teams to impress over the next decade.

AR: A survey by Harvard Business Review found that only 2.3% of VC money goes to women-led startups. Were you shocked to learn that?

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