[ad_1]
JD: It doesn’t make much sense to me, [but] I am glad that we have 45 issued patents, 40 patents pending, all in the USA. And our 30 European patents remain unaffected. And to be honest, look, I’m continuing my research.
AR: I always thought that the origin of the patent fight was not about money. My own reading of why it was fought so vigorously was that it was on credit, not trade control.–who did the science–and true.
JD: That’s your speculation. It’s hard to say, isn’t it? I don’t know what the motivations of others are, It will obviously appeal. Frankly, we do not agree with the decision. And frankly, if you’re talking about who invented what in the first place, 30 countries and the Nobel Prize Committee disagree.
AR: What does it say about how the patent system works, about someone accepting the Nobel Prize and then the patent going elsewhere? Should this make sense to people?
JD: It doesn’t make much sense to me. I don’t know if it makes sense to others. I don’t think there are too many questions in the scientific community about what it is.
AR: You were the subject of Walter Isaacson’s book, who also wrote biographies of Steve Jobs and Leonardo da Vinci. What was it like participating in your bio?
JD: To be honest, it’s unassuming and a little scary. Still, I felt lucky that someone as talented as Walter was interested in the story, because he’s a great writer. He did a great job trying to capture the feeling that we’re all a part of this incredible transformation that’s happening with CRISPR.
AR: You recently became the chief science consultant for a Wall Street firm called Sixth Street. What are you planning to do there and why did you take on this role?
JD: I’m excited at Sixth Street that we can identify the right teams, the right opportunities, the right openings where funding can really accelerate science and business opportunities. One area that I think has a lot of potential is using machine learning to analyze data from CRISPR. We know that one of the important opportunities with CRISPR in the future is to understand genomics, which is the function of genes. And obviously not individual genes, but comprehensively all genes and pathways and different cell types. The types of data obtained from these efforts contain a large amount of information, much of which is nuanced. And I think using machine learning algorithms to mine such datasets will be very powerful. You can imagine using such a strategy to understand the genetics of disease (our individual predispositions) and identify new therapeutics.
AR: I always think of you as a scientist’s scientist. I once saw a picture of a student leaning on his shoulder and I was thinking of you. But this one asks you to do something a little different. Contrary to the most compelling scientific questions, why do you think you might be good at choosing technologies for commercial investment?
JD: I love science and my best days are when I’m leaning on a student looking at data in the lab. However, I appreciated that for CRISPR to have an impact in the next decade, it would require the right teams to have real capital.
AR: A survey in the Harvard Business Review found that: Only 2.3% of VC money went to women-led startups. Were you shocked when you learned this?
[ad_2]
Source link