So, we have to balance the cost with getting the right information. and even in spite of that we don't, still don't get it right. So over the course of the time frame of all of these R&D processes we lose drugs. Okay? you probably see in the general papers in the press about another company, their drug that they had a lot of promise. For whether it be a vaccine, or what have you, failed. Okay? So it's unfortunate that we don't know until the late stage, phase three type clinical trials, that the drug is going to fail. And unfortunately, at this point, the companies are usually well into several hundred in the order of 5 to 750 million expenditures. So, we try to be smart along the way. One of the newer concepts that has come to light among the industry is to generate more of an integrative sort of process. What has evolved over the past years, all through the 80's and 90's particularly in big pharma. Okay, Pfizer's, Sharrings, Mercks, Hoffman and Roche, you name it. Are these silos if you will. So these are Stand Alone departments. So, you might have research in one silo. You might have clinical development in another silo. You might have commercial guys in another silo. And so there isn't a lot cross talk if you will. And so, that has been damaging to the success of drugs going forward. So companies are constantly looking at ways of reinventing the process, and the current thinking now is to do away with these silo's. And have a more integrative sort of process where we're talking with the business guys, we're talking with the legal guys. the biologist, the chemist are really tight. the folks in the clinic are fully integrated. So that everybody's wishes on, what is needed in other words what is it that the commercial groups need to sell a drug that will be used. That will show some potential to balance off with a biologist and introduce something that's novel, innovative, all of this. So thtat's what this slide is intended to show. Okay? So, a little bit on the compound section process. Okay? so, in the beginning we've got these targets now, the previous speaker was talking about kinases. Kinases are not the only types of targets. there are so many, so many types of small molecule targets, large molecule targets, where it's on the order of thousands. Okay? Just in the kinase space alone if you didn't say it, there's over 400 to choose from. Okay? So you can imagine these biologists and chemists have at their fingertips a lot of choices available to them. So the, the key is meshing the perspective from the biologist who and I put it here under the biology sense, a good target's a biological pathway. That can translate to a therapeutic outcome. Okay? So it's all biology from start to finish. The chemist view point is well biology is there and my idea is to generate a molecule that I know will interact with that target. And because of my chemistry and my knowledge in chemistry will deliver something better than ever before. And, it will work but it's all because of the organic synthesis process that I came up with. So the key is to bring and integrate both of those thought processes. So that the benefits from the biology standpoint are meshed very tightly with the chemical synthesis standpoint. Okay? So early on what the biologists and the chemists will typically do is they'll sit down with a bunch of other representatives from different disciplines. And they'll map out what it is that they desire. So in the industry we talk routinely about. first-in-class or best-in-class.? Okay and what it is that we want, and there is a big distinction. Okay? and, the first-in-class concept, this is basically something that is very novel, something unproven. But we were the first to discover it and to generate some molecules that showed the desired biology that we're seeking and got a drug to market. So we are number one and ahead of everybody else. Okay? That's ideal. That's, like the mother load to achieve that. best in class is a concept where the scientist will say, okay, we know our companies one, two, and three are all working on this specific target. company one is already in phase two, clinical development, so they're midway into the development paradign. Companies two and three well they are right at the the point of an I and D stage of development.? Okay So they probably invested about five years ahead of us. And so, these guys for this type of compound or this type of concept they may be thinking well. We have an understanding of what companies one, two and three have in their portfolio. We know the, the liabilities of what they have, we know the pluses. Let's develop something better. So, we recognize that we're not going to be first to market, very likely. But we'll have the best molecule that hits this target and proves, proves the, to be the best biological response. Okay? Ideally what falls into play is having something structurally unique. Actually this is more of a patent standpoints or an intellectual property standpoint. Okay? so the chemists have to be careful that they're not infringing on other chemists' ideas or concepts in the whole synthetic process. And here, it seems like a simplistic approach, but I can tell you when you're working in a space that's very crowded, where there's a lot of interest. Against the specific target. This makes a challenge very very difficult. solid pharmacology. So again, early on, the guys are going to ask for their dream list of properties. They're going to ask, that they've got this very unique molecule. It's very potent, it's very selective for that target. It works in animal models of a disease indication whether it be a diabetes, a cancer model what have you shows that it works in that model. Okay? excellent drug metabolism in pharmacokinetic properties so. this describes how the body handles the drug. So there are a number of parameters that go into this. Where we want to make certain that [COUGH] we have good predictable, well-behaved drug metabolism in pharmacokinetic properties. I'll show you some examples later on. Okay? put robust efficacy in an autoimmune disease model so in this particular case this would orient towards an inflammation type target. But the point here is that not only do we have very short term demonstrated efficacy in animal models. But we have nice, durable response data. In other words, if we give our new medicine to a rat, for example, we give him a single dose and we see a response and it's a desired response. we don't stop there. What we want is, we want to show in a more robust model that when we repeat dose these animals say every single day for a month. That we show a reproducible effect in a dose-responsive manner in this efficacy model so. You give a dose of 1 milligram per kilogram you get a response of so you give a larger dose you get a much larger response so that's what we expected to see. And then safety, safety now a days comes to the forefront almost above just about everything else here. many of these other activities tie into safety. but this is what the regulatory agencies are very keen on. And so, we are constantly under a microscope to generate data that speaks to the overall safety of a drug. Okay? All this information here, actually much of the information particularly at the back, they are at the bottom half of the information. And all the clinical information, goes into a drug label. So if any of you take prescription drugs, and you get this drug insert, about 75% of what I do goes into that drug label, and it covers a lot of these concepts.
