[BostonCard]

MTL will now lead a new company, Xaira Therapeutics, which had a splashy launch with $1 billion dollars of funding "to transform drug discovery and development with AI"

https://endpts.com/marc-tessier-lavigne-...tup-xaira/

Sorry, it is behind a paywall, but this is an interview with MTL about his new job.  There was a question in the interview about his time at Stanford (and whether he intends to incorporate any changes in overseeing the research in his new position):

Dunn: On your time at Stanford, the investigation found no evidence of data manipulation or fraud on your part. But it did criticize your laboratory oversight and management, and you acknowledged there were things you should have done better. What specifically do you plan to do differently at Xaira in terms of supervising science? And why should you be trusted in that type of position?

Tessier-Lavigne: Well, first, I’m obviously here to talk about Xaira. But maybe I can share a few thoughts.

First, I stand by the quality and rigor of my body of research as a whole. I’ve run a research lab for over three decades with 74 papers which I’m a principal author, and a handful of them had issues, as you pointed out. The panel concluded that I didn’t engage in any scientific misconduct, and I could not have reasonably been expected to have known about it.

And in terms of the lessons I take from this, I have run my lab by putting trust in my team. I’ve had exceptional lab members. I trusted that the data they were presenting to me were real and accurate. In general, that trust was entirely merited. But that created a vulnerability that allowed for these issues to arise in a few papers. What I take from that is the importance of also having an appropriate level of skepticism about data that are brought.

Dunn: Are there specific changes you plan to incorporate in overseeing and leading Xaira?

Tessier-Lavigne: Certainly. What this has driven home for me is the importance of having controls in place to ensure that your data that come forward are real and accurate, and not to take that at face value. And it’s certainly a principle that I’ll be applying here.

BC

[BostonCard]

MTL will now lead a new company, Xaira Therapeutics, which had a splashy launch with $1 billion dollars of funding "to transform drug discovery and development with AI"

https://endpts.com/marc-tessier-lavigne-...tup-xaira/

Sorry, it is behind a paywall, but this is an interview with MTL about his new job.  There was a question in the interview about his time at Stanford (and whether he intends to incorporate any changes in overseeing the research in his new position):

Dunn: On your time at Stanford, the investigation found no evidence of data manipulation or fraud on your part. But it did criticize your laboratory oversight and management, and you acknowledged there were things you should have done better. What specifically do you plan to do differently at Xaira in terms of supervising science? And why should you be trusted in that type of position?

Tessier-Lavigne: Well, first, I’m obviously here to talk about Xaira. But maybe I can share a few thoughts.

First, I stand by the quality and rigor of my body of research as a whole. I’ve run a research lab for over three decades with 74 papers which I’m a principal author, and a handful of them had issues, as you pointed out. The panel concluded that I didn’t engage in any scientific misconduct, and I could not have reasonably been expected to have known about it.

And in terms of the lessons I take from this, I have run my lab by putting trust in my team. I’ve had exceptional lab members. I trusted that the data they were presenting to me were real and accurate. In general, that trust was entirely merited. But that created a vulnerability that allowed for these issues to arise in a few papers. What I take from that is the importance of also having an appropriate level of skepticism about data that are brought.

Dunn: Are there specific changes you plan to incorporate in overseeing and leading Xaira?

Tessier-Lavigne: Certainly. What this has driven home for me is the importance of having controls in place to ensure that your data that come forward are real and accurate, and not to take that at face value. And it’s certainly a principle that I’ll be applying here.

BC