George Mahaffey 0:01
Good morning. I'd like to share with you Mindera Health. We are a venture backed small company located down the road in San Diego. We are commercializing our first asset as we speak, bringing precision medicine to a much needed market, which by definition, will improve patient outcomes and significantly lower the healthcare burden of specialty drugs spins. Our platform is applicable across many multiple indications in DERM and beyond. It is the first market we're going to go to is psoriasis. And I will show you why we do so in a moment. But the minimally invasive device a little about the size of a penny, is how we can capture the whole transcriptome of the patient, and then use machine learning to develop classifiers that can predict drug response before the drug is given. It's clinically validated. And we have many ideas beyond dermatology. Why Derm, we'll look at the size of the markets, not only is psoriasis large and growing atopic DERM is the next big market coming. There's 86 drugs in development for atopic DERM.
George Mahaffey 1:17
And when you look at psoriasis a little more closely, this is a very widely disease, 3% of the population, and many of them are moderate to severe. And when you look then at the market opportunity, we now have a price published by Medicare of $3,675. Where we know we will be paid that by the government, which then translates into commercial opportunities. The cost to the payers is enormous. If you look not only at the dollar per member per month cost, the escalation of this, every payer we talked to and we talked to many is aware of the problem. They're trying to solve the problem, we bring the solution to them. Well, how do we do it? First, let's look at the drugs themselves. Many physicians, payers have believed that these drugs work for everyone. These data were published from the largest independent registry last year, which showed that the drugs when prescribed is a little bit better than a coin flip for whether the patient will respond or not. This was a big learning and a big opportunity for us, because we can bring a much needed improvement to get that response rate up. When the drug works for the patient. They work great. The problem is matching the right patient to the right drug. And that is what we can solve. Here are just a couple of examples about the costs of these drugs that the payers are well aware of. And we will be announcing our first deal with the National payer in the coming months. When you look at the cost not only do doctors often use the newer, more expensive drugs when some of the oldies but goodies will work. But when they initiate the drug, and half the time, they don't work the payers on the hook for somewhere around 25 $30,000. And then they switch. They go to the next biologic round and round and round we go. So when you look at the drug label efficacy, which are listed here near the right side, and you compare that to the real world efficacy seen by the registry data and our clinical work, that disparity is important to address. And the penalty is being paid not only with patients who don't get better, and doctors who are guessing, but it's the payer who pays coming and going. This leads then to a paradigm that needs help. When the patient comes in requiring care. They've moved beyond steroids or phototherapy and psoriasis jargon, then the doctor and the patient decide what biologic drug to initiate. But they do that blindly the so called trial and error of medicine. When you then look at where the payers are on the hook, not only do the doctors often use the more expensive newer drugs, because they're new and more expensive, when the older ones would work. And that is net savings that the pit that the payer can realize. Secondly, that trial and error medicine the 25 $30,000 penalty for a swing and a miss makes this Paradine need to be helped.
George Mahaffey 4:32
This is how we help it we use our patch 7000 biomarkers we can capture next generation sequencing we use machine learning to develop algorithms that can predict what drug class is going to be the best for that patient. On this hypothetical report. You can see this patient will respond to a TNF inhibitor and not respond to the other two drugs. That would mean humera is the right drug of choice and we can say now with our classifiers with 94%, accuracy, positive predictive value that we can pick or give the doctor the data from which they can pick the right drug class that's going to work for that individual patient, much better than the coin flip that's going on in the real world. Well, how do we do this, we actually capture RNA from the skin, using a little patch about the size of a penny, I'll show you in a moment. It's painless, it's minimally invasive, it feels like the rough side of Velcro. It sits on the skin for a matter of five minutes, it then comes back to our cap CLIA lab here in San Diego or down the road in San Diego. And then using AI, we can develop very sophisticated classifiers that can prospectively predict what drug is going to work for what patient based on their baseline genetics, a huge advance over the trial and error medicine that's been going on for years. This is how it works. Our product is in a little device here about like I said about the size of a penny, it comes in a pre loaded single use applicator, that the lab or whoever we do, the test is put on the skin, the pet sits on the skin for five minutes, comes back to our lab, we next generation sequence it. And then using the AI and machine learning, we produce the positive predictive value data here. So that in this case, it's a rule in test. That's what the doctors want. They don't want to rule out tests, they want to know what's going to work for them. And now our classifier that the time of publication was 91%, were actually 94%. So as we think about commercialization, where we are, we've announced our first PBM deal about six weeks ago with more coming, when we get payer coverage, and they are our customer, we then backfill that with people in the field to support those areas where we have coverage, we now have four people in the field, we'll be adding more as we expand our coverage. But it's not a case where we have to hire a sales force, send them out there and hope it works. We can do this in a very staged and disciplined approach. And we have our own PLA code, which is obviously for the test and the allowable for Medicare at $3,675. Now as we're cutting deals with commercial payers and PBMs, we have that tailwind to get favorable contracts. And then we can hire people to support where we are in the field. We are on target to close our series B financing within a month to six weeks max, it will be at least a $40 million deal. And we're currently adding into the folks that are doing deep into diligence with us. But we're right on track to get this close in the coming couple of months. So as I mentioned, we have a platform. Psoriasis is the first natural target. We get calls back from payers and payers call us It's first time in my career. It's the case. But as we think beyond that we funded and we'll be starting at atopic DERM program this year as well, which will bring clarity to this market that's under construction. And I can assure you that the payers are scared to death about what's going to happen with eczema dupixent got a first mover advantage but all the big drug companies are working on ad drugs. We can apply what we did with psoriasis to atopic DERM to make sense, and to help the payers get control of those drugs in advance of it being a problem. We've put together a really strong team that has years of DERM and psoriasis experience. This came out of the Scripps lab in San Diego, our co founder and CSO is still with us. And as we've now built a team and doubled the company in the last six weeks. As we're growing into our commercial shoes. This is the trajectory that we're on. Thank you very much