And we showed in our in our SITC poster late last year, responses as a monotherapy, in RAS and RAS-mutant disease. So they’re the universal-MAPK as well as in combination with immune-oncology agents. But, I think, you can expect the clinical trials to really be focused initially on monotherapy that’s really our initial focus, given the really nice data that we’re seeing as a monotherapy. It’s obviously a much clearer path to start as monotherapy. And I think therapies that can do that, too. So we’re certainly excited to pursue it as a monotherapy. And the rest of the trial design, we’ll talk about in due course. So let me see, Scott, did I miss anything on the 415 design?
Scott Barrett: Well, it’s a work in progress. We’re evolving it. But, obviously, the objective is to integrate multiple aspects of the MAP kinase pathway, and that will include RAS and RAS-driven disease.
Benjamin Zeskind: Thank you, Scott.
Unidentified Analyst: Okay. Thanks.
Benjamin Zeskind: Okay. Thanks, Joyce. Next question, please.
Operator: Thank you. One moment for our next question. Our next question comes from the line of Jeff Hung from Morgan Stanley.
Jeffrey Hung: Thanks for taking my questions. I have two on this week’s AACR data. You indicated that no particular mutation physician or amino acid substitution was exclusively found to convert resistance to drug exposure. So based on what you’ve seen, which mutations do you expect to be particularly challenging or relatively easier to treat? And then I have a follow-up?
Benjamin Zeskind: Sure. Hey, Jeff, thanks for the question. They’re all universal-RAS means universal-RAS, we’ve not seen any difference really among the different mutations at different positions in P-KRAS, NRAS or HRAS in terms of sensitivity or resistance to 104. And, I think that makes sense in that we target MEK, so we’re targeting downstream of RAS. So it’s logical that we sort of be agnostic to the specific mutations, where we do start to see differences in responses, it really has to do with the mutations and other parallel pathways unrelated to MAP kinase. So, for instance, we’ve disclosed that in our Phase 2a in the colorectal cancer arm we plan to look specifically at APC wild-type patients, who are KRAS mutated. And that gives you a sense, for instance that APC mutation on a colorectal cancer model might be a little more challenging. But let me see if Brett wants to add anything to that. And then, we’ll take your second question.
Brett Hall: Yeah, absolutely. Hi, Jeff. I would add €“ we’ve also discussed that really the drivers for resistance to 104 are not really the mutation profile upstream, whether that’s a BRAF or K RAS, HRAS, NRAS. It really has to do with the profile of mutations in a given model. And we’ve outlined this extensively, for example, in NRAS models, where NRAS mutation is something that sets up for utilization or addiction, but addiction is really defined by how many compensatory mutations in parallel pathways exist. And so the more of those events that you see, the lower likely of single-agent response to IMM-1-104, and that’s part of what’s the mapping exercise for the AACR targeting RAS poster really starts to get at.
Jeffrey Hung: Great. Thanks. And then the data were generated in 3D tumor growth assays, would you expect some more broad activity in rodent models in humans? Thanks.
Benjamin Zeskind: Brett, do you want to speak to that?
Brett Hall: Yeah, absolutely. Yeah, so we’ve actually also disclosed that. So, for example, when you look at the depth of sensitivity or response in the 3D-TGA, we’ve generally observed in the models that we’ve already published and disclosed on that the deeper responding models such as MIA PaCa-2, which is a KRAS-G12C pancreatic cancer model, as well as SK-MEL-2, which is a NRAS mutant melanoma model, which are highly sensitive in the 3D-TGA and actually show regressions or mid-cycle regressions in vivo. For those that have an intermediate response profile such as A549, which is a non-small cell lung cancer model that KRAS-G12S, as well as Capan-2, which is a pancreatic cancer G12V model, those have an intermediate response profile, and we see stable disease or flat lining the tumor, if you will, in vivo.
