I've been looking back at trades trying to figure out what to learn from winners and losers, and it's pretty clear that with science applications, you need access to the data - and this means publishing in journals with peer review.

I follow Cathie Wood's ARKK funds for ideas, and two stocks ARKK and ARKG have owned (and I think still own) are Intellia and Quantum-Si.

Currently NTLA is the 12th largest holding of ARKK and QSI is the 39th largest holding of ARKG.

Here's a fun question for those who track and follow ARKK and ARKG.

What ARKK/ARKG stocks have been your biggest winner and loser?

Why do you think, and is there anything to learn in hindsight?

For me, my biggest winner so far is Intellia with an average cost of $74, up 117% from my entry.

My biggest loser (sold out) is QSI - bought in around 12 and sold at around 8, so a 33% loss (I need to set a tighter stop for sure):

If I had to take anything away from it all - I think with NTLA, the positive scientific results shared in a prominent journal like New England Journal of Medicine kicked it all off - though I had no prescient knowledge that the results would be that good or so widely lauded.

Compare that to QSI - I read the Q2 earnings transcript, and I found this interchange quite telling with CEO John Stark - which went something like - "Hey why don't you have any papers published on your system" and the response being - "yeah good idea, we should do that." I sold and took the loss. Now maybe they have something in the works with NEJM just like Intellia did and can't speak about it, but I'm willing to sit it out for now.

Great. Okay. That was great. And you kind of alluded to some of the PTM analysis stuff there too, but I think you talked about in the prepared remarks, something about generating data, maybe publications with some of these early users. Do you kind of obviously you have been an outstanding IP portfolio, tons of issued patents and pending [indiscernible]? Could there be maybe next year or two some papers submitted for publication or even like white papers for some just tangible kind of data. I'm just wondering because it would – it would maybe help kind of accelerate kind of the types of applications as well as just the awareness?

Absolutely, that's the goal. And again, when we partner with early access groups, we always talk about study designs and potential applications, resource them accordingly. Again early access reason why we're now at five halfway through the year, and we'll be accelerating into the back end of the year with a minimum of 10 placements, as we feel very confident with the instrument is that, we – we're now focused on providing product; we're focused on scaling the commercial organization, but you really hit it on the head that's one of the key areas of focus, which is finalize the optimization of the system, but also show real meaningful published data that represents application, and we'll continue down that path here for the foreseeable future.