Maternal out already reporting a narrow with an expected first quarter loss cost cutting of setting a steep decline in its COVID business. Maternal expecting to receive US approval for its second product, an RSV vaccine, in the coming days, joining us now as the Maternal CEO. Stephan Bansal, Stephan, wonderful to catch up with you, sir. The stock is
just about positive in the pre market. Can you talk to me about how you're balancing cost cutting with investing in innovation given what's in the pipeline.
Sure, well, good morning, Thank you for having me so very pleased with a quote. We basically try to focus on how do we drive sales, how do we drive R and D, how do we prioritize opportunities, which is the way. For example, we announced that we are stopping the partnership with Metagenom in research engine editing.
Same thing if you look.
At the portfolio, we're looking very carefully at all investments. And the good thing about those vaccines, like respiratory vaccines is your only pay the face free study. Whats so if you think about COVID, we still up sells from COVID, but the investment in the idea of COVID has come down a lot. As you said ours, we we are anticipating a launch this spring, but we're not going to do another Phase three four URSV, so you can still
basically have a lot of new studies going on. We're using the capital you used to put in the other products before. And then if you look at oncology, as you know, we're in a fifty to fifty profit share with Merk, so merk is paying half of a phase free study. So that's how we're managing when we're seeing a lot in technology. You might have seen last week
an announcement with open Ai. We actually more than seven hundred fifty GPT is going and that is helping us a lot scale the company across not only science but surd having a lot of productivity in manufacturing in commercial illegal So that's kind of how we're doing it.
So Stephan, let's talk about something that our colleagues here at Bloomberger extremely focused on, and that's your RS three shot, which according to our colleagues, some data is showing that maybe it doesn't last as long as others in the market. What we all want to know here at Bloomberger is whether that raises questions about the promise of your technology in treating other diseases. How would you answer that?
So will first say that if you look at the data the duration of the over vaccines, they are very similar. So I don't think it is scientifically correct to say that one of a vaccine doesn't last as long as your ones of a too that are improved and ours. Look at the data. This will be debated at the CDC meeting at the end of drewne that for reccommodations. So this doesn't worry me. If you look at duration,
the duration of vaccination is induced by T cell. If you look at cancer product, the only reason it works is T cells, not antibodies. Antibodies don't have a row in cancer. It's about T cells going and attacking your cancer. If our vaccine technology didn't have good T cell response, the cancer product will not look as good as it is. So I'm not worried at all about duration.
Pretty much every time we speak, Stefan, I ask you, basically, have we couraged cancer yet? So I'm glad that you went there because that's been sort of one of the big questions in the hope for a lot of the MR and A vaccines. You have this Melanima vaccine in the works, what more do you have to do to get it sort of set up for the approval process to apply for that and are you using artificial intelligence to extradite.
That great question.
So if you look at cancer treatment in melanoma, we've said that we need to achieve free things to be able to talk to regulator about accelerated approval. So the face to day ties data we shared on the show several times, we see duration. If you remember in December we shad a three year survival. It was better than the two year survival. So the difference between people on all treatment and people that are just getting cathedral is
getting wider. So there's a very strong evidence that the drug is working.
So that's number one.
Number two is we need a phase free study to be substantially enrolled, and so we are working very actively. Face free study started two months earlier plan last summer and so when we are substantially enrolled, we will meet that criteria and it could be late this year. And the third one is a plant because of course we need to file in the restrection du all the information about the manufacturing process BFD the day you file is allowed to go, of course, audit your plant. That plant
is being built. I had a chance to go there
two weeks ago. The team is working NonStop, scheduling literally by the days, a bit like we did during COVID during the pandemic, and so I anticipate that potentially sometime next year, you know, the if a regulator was willing to look at the accelerated approval file, we should have this product available to help a lot of people, because one in two people benefit with no thises coming back or our deaths compared to the best drug available today to them on the market.
Stephan, can you just give us a sense of you talk about artificial intelligence. Everyone's talking about artificial intelligence. Could you just talk about how much that could expedite generally some of the drug production that we're seeing. Just how much that could really get us to achieve you know, that cure for cancer, that cure for als, cure for Alzheimer's. You know, it's funny you're talking about sex and city. I sit around and I worry about these things. You know,
what are we to cure these things? So I'm just wondering, you know, this is going to be in our lifetime in the next couple of years because of some of the machine learning.
Yes, so I think there's a few things to tear part in your in your great question. First is I think machine learning in academic labs, in research labs, in industry is helping accelerate the understanding of a human body. If you think about you know, this is Alzheimer and all those complicated disease that we do not have solutions for yet as a society. It's because we do not understand the biology. We do not understand how the disease happened, how the disease evolved, and so we are just trying
things and some work, but very few work. Most of them don't work because we're just trying and guessing. If you look at a biology, once we understand that something works, then the industry can comes with very very good actions to deal with those. So I think AI will accelerate the understanding of biology, which would be fundamental to bring new drug. Then AI is already used to accelerate discovery in terms of what tool do you go after a
disease once you understand it. At modern already we have different chemical matters that are generated by our AI system that are helping us to accelerate the work that humans are doing. So it's an accelerator to the teams. And
then there's a huge chapter on productivity. If you think about clinical development phase one, two and three, it's basically doing experiment in human, getting the data, finding the doors, doing more experiment, and when you have all studied on, you get all the data and you submit by relator.
My point is it's all about data.
They are literally hundreds of business processes that need to happen, and I think many of those, if not most of those, you've got to be able to apply AI to shrink time to go faster. An example we shared in March in a vaccine. Then the team wrote a GPT to help us to do those selections. When you do clinical study your phase one, you try several doses and then based on the data you get in a clinic, you
decide which jos go into your phase three. Well, it used to take around a month to do that by having people and meeting and experts looking at the data while we develop a GPT that basically get all the data from the clinical study and suggests to us a those in literally a minutes or two. That is already a tool that has been developed that I've seen used at the company.
That's just one example. So here you go to shrink them off.
And if you do that on the hundreds of business processes that have to happen in preparing the drug for the clinic, the clinical testing, the analyzing of the data, the communication with the FDA, I think you can save a lot of time. I don't know yet, because only history will show us in the next few years, can you shave thirty percent, forty percent, fifty percent of how many years it takes you to develop a drug?
I think it's going to be very significant.
Stephan, We've got to leave you there. It's fantastic to catch up with you, so amazing to listen to you talk about the efforts taking place at Maderna. Madenna CEO Stefan Bansell