theCUBE + NYSE Wired: NYSE Rx | Jim Iversen, Sen-Jam Pharmaceutical

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Jim Iversen

CEO

Sen-Jam Pharmaceutical

play_circle_outline Sen-Jam Pharmaceuticals: Iversens Blend Pharmacy and Supply-Chain Expertise to Combat Inflammation, Promote Longevity

play_circle_outline Drug pipeline: two therapeutics Phase 2/3 and five assets in development

play_circle_outline Duke, NIDA & TASK Clinical Collaborate on COVID, Alcohol Inflammation, Opioid/Methamphetamine Disorders — Phase 3 Roadmap, Imminent NIDA Results

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Jim Iversen, Sen-Jam Pharmaceutical

Jim Iversen

CEO Sen-Jam Pharmaceutical

search

(INTRO)

Gemma Allen

>> Welcome back to theCUBE Studio here at the New York Stock Exchange. I'm Gemma Allen with NYSE Wired. Today, we are talking all things AI and bio. There is a phenomenal event happening right here at the NYSE. some great builders and innovators in industry in this building talking about the future of technology and science where the rubber meets the road and joining me for a conversation on exactly that is Jim Iversen CEO of Sen-Jam Pharmaceutical. Welcome Jim.

Jim Iversen

>> Thank you nice to be here.

Gemma Allen

>> So maybe just to start let's just set out the stall here on Sen-Jam. 10 years old started with your wife Jackie, your, could I say better half, Jim? Might I say that?

Jim Iversen

>> Brains of the operation.

Gemma Allen

>> Behind every great man, right? But who's a pharmacist? Talk me through the journey 10 years ago to now. Give me the kind of 360 view of this.

Jim Iversen

>> Yeah. So I've had a career in building supply chain companies. I've built a number of supply chain companies, both on the robotics and automation side and the software side. And I sold my last business about 10 years ago. And that's when Jackie came to me with this idea that with the belief that if we resolve inflammaging, we believe that we can people can live longer, healthier, more resilient lives. And with that in mind, focusing around inflammaging, I quickly looked at inflammaging and realized that 60 to 70 % of deaths are inflammatory related. And that was something that really jumped out at me as something where I can dedicate my career, put time and effort into and see what we can do to better that. And by bettering that, it will benefit everyone.

Gemma Allen

>> Wow. And there were a number of drugs on the market that claimed to solve inflammaging to a certain degree, correct? in varied capacities. But you're looking to solve for something more holistic. Talk me through what is fundamentally shifting and new in what you guys are creating.

Jim Iversen

>> Yeah. So what we're doing is we're focused on immunomodulation. And what immunomodulation is, we have the belief that your immune system is incredibly strong and incredibly resilient. But what happens is with acute inflammatory events and chronic inflammatory events, they affect how the immune system works. So by developing immunomodulators, we can bring the immune system back to homeostasis, and that will allow the immune system to do what it was designed to do, which again, we believe will have positive effects on longevity, health care, health span, which we're calling inflammaging, and overall resilience.

Gemma Allen

>> So 10 years ago, 2016, we didn't have ChatGPT, we didn't have LLMs, we didn't say AI 10 times in a minute, which we do today. A lot has changed. I think a lot has changed in science and tech. But you set about this mission pre that, right? You've brought two drugs. You've got two drugs in stage two or stage three of the kind of trial cycle, which we know is a lengthy and onerous cycle. Even still, what is changing from the perspective of AI and how you shift the focus and bring more tech into this business?

Jim Iversen

>> Yeah, that's a great question. And we always said that before AI, we had J .I., which was Jackie Iversen. And what we developed was the ability to automate what we've done manually, which comes from my supply chain background as well. If you can't do it manually, don't automate it. And as you said earlier, the tools didn't exist. And now the tools do exist. So we developed and we brought these two therapeutics through the old way, through the analog way of drug development. And there's a benefit of learning how to do things the old way, because then when you get the tools to do it the new way, you have much higher appreciation for that. So we started in vitro, in cell lines, went to animals, and then ultimately went into humans with our two therapeutics. And currently we have five assets in or at phase two. We're working with the National Institute on Drug Abuse with one of our therapeutics for opioid use disorder. And we've just completed the two phase two clinical trials. And we've just had our first phase two meeting with the FDA. Making the shift into the digital world, we have a scientific advisor, Alexander Wissner-Gross, who has been with us for four years. and Atlas has really helped us with all of our AI planning and development. And what we've done is we've created a, our platform is called Galaxy. And within Galaxy, we have three layers. We have Atlas, which is the discovery layer. We have Sextant, which is the navigation layer and Constellation, which is the routing layer. And right now, we've been doing Atlas manually, given the clinical trials and the data that we've gotten back. And we've been able to determine how well we can use that data to advance our entire platform. It's been unbelievable within our own ecosystem on how we've been able to work with this. With Atlas now we expect later this year to we're looking at biology and pharmacology and you know in the past pharmacology is very very messy biology there's a lot of data but not a lot of knowledge and then just with clinical development and everything that we're bringing all of this to ai now under a computational model atlasand uh and we expect to be able to develop

Jim Iversen

>> some really powerful drugs

Jim Iversen

>> from combinations

Gemma Allen

>> i want to hone in on something you said there a lot of data but not a lot of knowledge and we know why sometimes data doesn't necessarily translate to knowledge right it can be systems orientated it can be technology orientated it can be governance orientated what is the fundamental reason in the pharmaceutical biotech space what has been the great unlock there?

Jim Iversen

>> For me, being new to the industry, there's a lot of siloed data, there's a lot of data, but it's in separate silos. So it's not talking together, which I believe, that's a big inherent problem. And even within pharmacology, we have developed a lot of repurposed drugs. And these repurposed drugs, when you bring them to market, you have to choose one indication for them. But there's other inherent characteristics with the chemicals that are in that. So that's another piece of locked up data. And then on the biology side, there's been a tremendous amount of biological discovery, but it hasn't been combined with the pharmacology, with the other data and with, from drugs and the ability to accelerate clinical trials, the ability to do more proof of concept work. So it's the combination of all of those things are helping us take a lot of data and cleaning it all up and bringing it to knowledge which we can act upon.

Gemma Allen

>> In looking at this topic for today, I was somewhat fascinated by the trial and error ratios for biotech broadly, right? A lot of folks get to kind of preclinical, clinical, even phase one. and then when it comes to the overall efficacy or approval to market there is a lot of companies and opportunities seem to fall off that scale a little bit and I was fascinated that it was like I think less than 10 percent of drugs actually make it through the whole shebang you could say you've taken quite an interesting risk here with this what do you think is so unique about what you're building and about even this moment what made you say, you know what, this is worth the bet?

Jim Iversen

>> Well, one big factor is it benefits everyone. So the work that we're doing and our mission is to increase speed to patient, lower costs and make therapeutics available to everyone on the planet. And so that's a big factor in the work that we're doing.

Gemma Allen

>> Wow, I love it. And talk about the commercial side of this business for a second, because AI has suddenly made everything commercial, right? We talk about money and outcomes and speed to market and all of these terms and even some jargon like we never did before, even in technology itself. The expectations are just so fast. And biotech and pharmaceutical has always been somewhat slower for good reason. You can't expect to develop a cure for cancer in a week. That's just never been a realistic expectation. What are your thoughts around the commercial side of this industry? even when we think about investment theses, the types of folks who are investing, the knowledge base behind that, what are you seeing, especially as someone who's been an entrepreneur in a different space?

Jim Iversen

>> Yeah. So, as we're developing and to give you an example, our platform that we developed, our Atlas, and we've been able to test, and this goes back to the proof of concept question that you asked before, we were able to go back and validate our model because we have a platform. So our platform is made up of similar agents. So anytime we make one improvement, it improves everything. And so we took some of our assets, just to put things in a little bit of perspective, that we haven't been doing work with, that we have patents for, and we've run them through Atlas. And we've shown, based on the results that we've gotten from our clinical trials, that we can have a 200 to 300 % higher probability of success. And so that's something that is very attractive to investors. And then from a commercialization perspective, our original business model was to de -risk on the clinical and regulatory side and then file intellectual property. And then when we get to the end of phase two, that's when the asset has been de -risked. And that's when a company would be interested in in -licensing that asset. So that was our business model when we started out. And now as we're getting more towards commercialization and we're getting more and more tools that we can use with our AI, that our discovery engine of Atlas is now, we're looking at it as a diligence engine for universities and other people who have done early stage drug discovery that could allow us to in-license or acquire those assets to bring them into our development pipeline. And so the commercialization component, we're seeing short term the ability to provide, possibly provide more services because of the tools and technology and algorithms that we have that we can, we could test the probability of success or proof of concept for other assets to increase the likelihood for theirs based on the data sets that we've created as we move and we build our pipeline for more value by developing our portfolio of many more assets.

Gemma Allen

>> Wow. Well, let's talk a little bit ahead from the perspective of those assets. What does the roadmap look like? what is the next 12 to 18 months for you, yourself and Jackie and the team?

Jim Iversen

>> Yeah, so we have five assets that are currently in our pipeline. And we've in the last 12 months, we've completed two phase two clinical trials. So they're the two assets that we're focused on. One is we worked on with Duke University, an upper respiratory infection, COVID therapeutic. And then the second, which is looking at alcohol's impact on inflammaging. So we have a partner TASK Clinical, who's interested in doing the phase three study for the alcohol impact on inflammaging therapeutic. And so that's the advancement there. And then right behind that, the National Institute on Drug Abuse, we've done a lot of work around opioid use disorder. And we've shown that we can reduce opioid severity and duration by 50%, opioid withdrawal severity and duration by 50%. And then the National Institute on Drug Abuse was very interested in our drug for methamphetamines. So they're testing, and they're doing the third of three sponsored tests right now. And we expect to get those results back hopefully within the coming month or two. And so that's an asset that we're looking to bring forward, bringing it into humans as we look to advance our other therapeutics into phase three.

Gemma Allen

>> Well, Jim, if you can find a drug that solves my hangovers, please ship me a box. Let me be your first customer. But no, fascinating conversation and fascinating theory that just how much inflammaging, how many problems inflammaging causes in society broadly. And if one drug could solve for that, what's not to love about that? So Jim Iversen, thank you so much for joining us on theCUBE.

Jim Iversen

>> Thank you for the invite. Great to be here.

Gemma Allen

>> I'm Gemma Allen here at theCUBE Studio at the New York Stock Exchange. Today we are talking all things AI and biotech, meeting with some of the builders, breakers, and innovators who are really driving change in this industry. Stay tuned.

Jim Iversen, Sen-Jam Pharmaceutical

search

(INTRO)

Gemma Allen

>> Welcome back to theCUBE Studio here at the New York Stock Exchange. I'm Gemma Allen with NYSE Wired. Today, we are talking all things AI and bio. There is a phenomenal event happening right here at the NYSE. some great builders and innovators in industry in this building talking about the future of technology and science where the rubber meets the road and joining me for a conversation on exactly that is Jim Iversen CEO of Sen-Jam Pharmaceutical. Welcome Jim.

Jim Iversen

>> Thank you nice to be here.

Gemma Allen

>> So maybe just to start let's just set out the stall here on Sen-Jam. 10 years old started with your wife Jackie, your, could I say better half, Jim? Might I say that?

Jim Iversen

>> Brains of the operation.

Gemma Allen

>> Behind every great man, right? But who's a pharmacist? Talk me through the journey 10 years ago to now. Give me the kind of 360 view of this.

Jim Iversen

>> Yeah. So I've had a career in building supply chain companies. I've built a number of supply chain companies, both on the robotics and automation side and the software side. And I sold my last business about 10 years ago. And that's when Jackie came to me with this idea that with the belief that if we resolve inflammaging, we believe that we can people can live longer, healthier, more resilient lives. And with that in mind, focusing around inflammaging, I quickly looked at inflammaging and realized that 60 to 70 % of deaths are inflammatory related. And that was something that really jumped out at me as something where I can dedicate my career, put time and effort into and see what we can do to better that. And by bettering that, it will benefit everyone.

Gemma Allen

>> Wow. And there were a number of drugs on the market that claimed to solve inflammaging to a certain degree, correct? in varied capacities. But you're looking to solve for something more holistic. Talk me through what is fundamentally shifting and new in what you guys are creating.

Jim Iversen

>> Yeah. So what we're doing is we're focused on immunomodulation. And what immunomodulation is, we have the belief that your immune system is incredibly strong and incredibly resilient. But what happens is with acute inflammatory events and chronic inflammatory events, they affect how the immune system works. So by developing immunomodulators, we can bring the immune system back to homeostasis, and that will allow the immune system to do what it was designed to do, which again, we believe will have positive effects on longevity, health care, health span, which we're calling inflammaging, and overall resilience.

Gemma Allen

>> So 10 years ago, 2016, we didn't have ChatGPT, we didn't have LLMs, we didn't say AI 10 times in a minute, which we do today. A lot has changed. I think a lot has changed in science and tech. But you set about this mission pre that, right? You've brought two drugs. You've got two drugs in stage two or stage three of the kind of trial cycle, which we know is a lengthy and onerous cycle. Even still, what is changing from the perspective of AI and how you shift the focus and bring more tech into this business?

Jim Iversen

>> Yeah, that's a great question. And we always said that before AI, we had J .I., which was Jackie Iversen. And what we developed was the ability to automate what we've done manually, which comes from my supply chain background as well. If you can't do it manually, don't automate it. And as you said earlier, the tools didn't exist. And now the tools do exist. So we developed and we brought these two therapeutics through the old way, through the analog way of drug development. And there's a benefit of learning how to do things the old way, because then when you get the tools to do it the new way, you have much higher appreciation for that. So we started in vitro, in cell lines, went to animals, and then ultimately went into humans with our two therapeutics. And currently we have five assets in or at phase two. We're working with the National Institute on Drug Abuse with one of our therapeutics for opioid use disorder. And we've just completed the two phase two clinical trials. And we've just had our first phase two meeting with the FDA. Making the shift into the digital world, we have a scientific advisor, Alexander Wissner-Gross, who has been with us for four years. and Atlas has really helped us with all of our AI planning and development. And what we've done is we've created a, our platform is called Galaxy. And within Galaxy, we have three layers. We have Atlas, which is the discovery layer. We have Sextant, which is the navigation layer and Constellation, which is the routing layer. And right now, we've been doing Atlas manually, given the clinical trials and the data that we've gotten back. And we've been able to determine how well we can use that data to advance our entire platform. It's been unbelievable within our own ecosystem on how we've been able to work with this. With Atlas now we expect later this year to we're looking at biology and pharmacology and you know in the past pharmacology is very very messy biology there's a lot of data but not a lot of knowledge and then just with clinical development and everything that we're bringing all of this to ai now under a computational model atlasand uh and we expect to be able to develop

Jim Iversen

>> some really powerful drugs

Jim Iversen

>> from combinations

Gemma Allen

>> i want to hone in on something you said there a lot of data but not a lot of knowledge and we know why sometimes data doesn't necessarily translate to knowledge right it can be systems orientated it can be technology orientated it can be governance orientated what is the fundamental reason in the pharmaceutical biotech space what has been the great unlock there?

Jim Iversen

>> For me, being new to the industry, there's a lot of siloed data, there's a lot of data, but it's in separate silos. So it's not talking together, which I believe, that's a big inherent problem. And even within pharmacology, we have developed a lot of repurposed drugs. And these repurposed drugs, when you bring them to market, you have to choose one indication for them. But there's other inherent characteristics with the chemicals that are in that. So that's another piece of locked up data. And then on the biology side, there's been a tremendous amount of biological discovery, but it hasn't been combined with the pharmacology, with the other data and with, from drugs and the ability to accelerate clinical trials, the ability to do more proof of concept work. So it's the combination of all of those things are helping us take a lot of data and cleaning it all up and bringing it to knowledge which we can act upon.

Gemma Allen

>> In looking at this topic for today, I was somewhat fascinated by the trial and error ratios for biotech broadly, right? A lot of folks get to kind of preclinical, clinical, even phase one. and then when it comes to the overall efficacy or approval to market there is a lot of companies and opportunities seem to fall off that scale a little bit and I was fascinated that it was like I think less than 10 percent of drugs actually make it through the whole shebang you could say you've taken quite an interesting risk here with this what do you think is so unique about what you're building and about even this moment what made you say, you know what, this is worth the bet?

Jim Iversen

>> Well, one big factor is it benefits everyone. So the work that we're doing and our mission is to increase speed to patient, lower costs and make therapeutics available to everyone on the planet. And so that's a big factor in the work that we're doing.

Gemma Allen

>> Wow, I love it. And talk about the commercial side of this business for a second, because AI has suddenly made everything commercial, right? We talk about money and outcomes and speed to market and all of these terms and even some jargon like we never did before, even in technology itself. The expectations are just so fast. And biotech and pharmaceutical has always been somewhat slower for good reason. You can't expect to develop a cure for cancer in a week. That's just never been a realistic expectation. What are your thoughts around the commercial side of this industry? even when we think about investment theses, the types of folks who are investing, the knowledge base behind that, what are you seeing, especially as someone who's been an entrepreneur in a different space?

Jim Iversen

>> Yeah. So, as we're developing and to give you an example, our platform that we developed, our Atlas, and we've been able to test, and this goes back to the proof of concept question that you asked before, we were able to go back and validate our model because we have a platform. So our platform is made up of similar agents. So anytime we make one improvement, it improves everything. And so we took some of our assets, just to put things in a little bit of perspective, that we haven't been doing work with, that we have patents for, and we've run them through Atlas. And we've shown, based on the results that we've gotten from our clinical trials, that we can have a 200 to 300 % higher probability of success. And so that's something that is very attractive to investors. And then from a commercialization perspective, our original business model was to de -risk on the clinical and regulatory side and then file intellectual property. And then when we get to the end of phase two, that's when the asset has been de -risked. And that's when a company would be interested in in -licensing that asset. So that was our business model when we started out. And now as we're getting more towards commercialization and we're getting more and more tools that we can use with our AI, that our discovery engine of Atlas is now, we're looking at it as a diligence engine for universities and other people who have done early stage drug discovery that could allow us to in-license or acquire those assets to bring them into our development pipeline. And so the commercialization component, we're seeing short term the ability to provide, possibly provide more services because of the tools and technology and algorithms that we have that we can, we could test the probability of success or proof of concept for other assets to increase the likelihood for theirs based on the data sets that we've created as we move and we build our pipeline for more value by developing our portfolio of many more assets.

Gemma Allen

>> Wow. Well, let's talk a little bit ahead from the perspective of those assets. What does the roadmap look like? what is the next 12 to 18 months for you, yourself and Jackie and the team?

Jim Iversen

>> Yeah, so we have five assets that are currently in our pipeline. And we've in the last 12 months, we've completed two phase two clinical trials. So they're the two assets that we're focused on. One is we worked on with Duke University, an upper respiratory infection, COVID therapeutic. And then the second, which is looking at alcohol's impact on inflammaging. So we have a partner TASK Clinical, who's interested in doing the phase three study for the alcohol impact on inflammaging therapeutic. And so that's the advancement there. And then right behind that, the National Institute on Drug Abuse, we've done a lot of work around opioid use disorder. And we've shown that we can reduce opioid severity and duration by 50%, opioid withdrawal severity and duration by 50%. And then the National Institute on Drug Abuse was very interested in our drug for methamphetamines. So they're testing, and they're doing the third of three sponsored tests right now. And we expect to get those results back hopefully within the coming month or two. And so that's an asset that we're looking to bring forward, bringing it into humans as we look to advance our other therapeutics into phase three.

Gemma Allen

>> Well, Jim, if you can find a drug that solves my hangovers, please ship me a box. Let me be your first customer. But no, fascinating conversation and fascinating theory that just how much inflammaging, how many problems inflammaging causes in society broadly. And if one drug could solve for that, what's not to love about that? So Jim Iversen, thank you so much for joining us on theCUBE.

Jim Iversen

>> Thank you for the invite. Great to be here.

Gemma Allen

>> I'm Gemma Allen here at theCUBE Studio at the New York Stock Exchange. Today we are talking all things AI and biotech, meeting with some of the builders, breakers, and innovators who are really driving change in this industry. Stay tuned.