Unidentified Analyst: Great. Thanks for taking the questions.
Operator: Thank you. Our next question is from Matt Sykes with Goldman Sachs. Please post your question.
Matt Sykes: Hey, good afternoon and thanks for taking my questions. Drew, maybe the first one for you. You mentioned that TAM analysis that you guys have done. I would love to get a little bit more additional color on sort of the output of that analysis, if you’re willing to share? And just kind of where you feel like the realistic TAM is and where you think the sort of differentiation with G4 is resonating, and what that does to the, sort of, addressable portion of the TAM sort of this year and into the future?
Drew Spaventa: Yes, absolutely. We are happy to share kind of our models and our numbers separately. I guess at a high-level summary, if you think about the current market of NGS, and again there’s all different TAM analysis of how big it’s going to be in 5 or 10 years and where the growth is. But start with the $6 billion current market, about half of that is academic. And if you look at the breakdown, the majority of the academic are going to be doing targeted panels, RNA-Seq and single cell. So when we think about early adopters and where those things converge, RNA in the academic environment and single-cell RNA are real sweet spots for us, especially with Max Read coming. We think that will be a real driver of adoption since it’s such a differentiated solution for that really popular academic application.
When we look at the clinical side of things, the majority is targeted panels. And that’s something that we’re very interested in addressing and demonstrating. We think the G4 is kind of specs throughput, speed, are really well suited for your academic medical center or your hospital lab, or even a centralized clinical lab, due to the fact that you can run individual samples very quickly at a really good price point. But as we mentioned earlier, we think those are probably further on the adoption curve. The early adopters likely aren’t putting patient-critical samples onto a new technology, and that’s just the reality of how new technologies go. So we can definitely spend more time with you on those TAMs. But the point is sitting here a year from now, if we say we are going to win in the academic single cell market, well, we want to be able to show you proof points of that, have real customers understand the use case of those customers and have metrics.
And if we are telling you we are going to play in academic medical centers and start doing targeted panels, well, where are the early proof points in that and where are we getting traction? And how do we think about what part of that market we can win in. So that’s what we mean, and we’ll share more on it.
Matt Sykes: Got it. And maybe just following up on that comment about Max Read, just kind of leading to my second question, which is just based on the feedback you’ve gotten and if we focus on sort of academic where you’ve had some success, products like Max Read and other products you might have in the pipeline, has it shifted your priorities in terms of where you want to spend some of the R&D to develop products to maybe focus specifically on those applications you mentioned, but on the academic channel and where their kind of interest lie? I mean, has it shifted any of your priorities in terms of spend and focus for product development?