dr frudakis presentation at the open housr dec 2 cont...
Back to our business model a little bit. Once we’ve identified a genetic pattern in the population, which should take us about six months to two years depending on the complexity of the problem. It would then constitute a sort of diagnostic test , we call it diagnomics, diag for diagnostic, nomics for genomics. The conversion of genetic pattern to product is going to be mostly funded through partnership. The clinical validation of the tests that we develop are going to be funded through partnership. The reason we do this is, Why are we going to give away a piece of each product in order to do this. Well a lot of high tech companies fail because the cost of getting the (inaudible) to here , not specifically for genetics but from any preliminary clinical products is very steep indeed. It’s very risky, its in fact more risky to take a product that you know works and get it into a clinic, than it is to develop a product to begin with. So were going to partner, were going to take that risk and give it to somebody else, in exchange were going to give them a piece of the product and as I mentioned before, were going to go back and function as a node to generate a solution for the next trait and the next trait. We’ll let them spend the money to commercialize and they will be the branch. Eventually the product will have to gain acceptance through FDA regulatory approval as a consumer genomics product.
And again that will all be partly funded. Making money from the product through ASP type of a business model where patient genetic profiles are being pushed through server systems that contain our solutions. All of that will be funded through partnership. We don’t want to become an internet company, Were not even a software company. We are an information company. And we wish to remain that so that we can remain the node on the tree.
A little bit about the databases that we make consists of a gene. Genes are organized into discreet modules called exxons. (not sure of spelling) There is a promoter region and a translator region. Most of the companies out there like Incyte Genomics have data on only one region of these genes. Through limitations of the approach they use. It’s called an EST approach. Express sequence tag. They collect these genes and they sequence them from this end and so they have this (pointing to diagram on screen) for most of the pharmacologically important genes in our body, this data does not exist. You can’t get it anywhere. You can’t buy it. You have to pay to make it. Most companies would not do that, because most companies are not involved in our field. But for a company that’s involved in Pharmacogenomics or complex disease genetics this (inaudible) is very important. When were finished building this database for 150 or 200 genes that are important for drug metabolism. It will represent a one of a kind and unique data center that many groups out there, many pharmaceutical companies would like to get their hands on. But won’t be able to. Many of them are unwilling to invest the money to go deep in the population because its easier to wait for other companies to do it and then partner with them. So this is one way that we can bring in short term revenue. Its through partnership of our results. We always take intellectual properties from any project that we do. We are not a service company. We will not perform services on a fee for service basis within the field of genomics. But through partnership because of our strength of having this data where no one else does. And use it to get partnerships and help build our intellectual property portfolio.
One software system that we are using right now to assemble are re-sequencing database is a software system that was written by our mathematician Myung Ho Kim who actually just arrived and is in the back of the audience. That’s also Zach Gaston by the way wearing the sunglasses. Our lead technician. The software basically what it does, it takes the Human Genome Database and it takes our own DNA sequence data that we collected, and it analyzes it by comparing the sequences from multiple individuals to one another. By comparing the sequences to one another we can see what makes them different. And then we can find specific regions in the genes that are different from person to person. This software catalogs those positions in a database. That is called a SNP database. Single nuecletide polymorphisms. The software executes that for us so we don’t have to do it by eye which would take forever and actually scores them as haplotypes and I don’t want to get into to much detail but a haplotype is for example, of our genotype is G/C, A/G. A haplotype would be GA/TC. Its called phase known data. Don’t worry if you don’t understand it. Its actually quite critical to convert genotypes to haplotypes in order to gain the kind of power that were going to enjoy. But once we have the haplotype database this is what constitutes our product that I was talking about here. This is an example output from that software (pointing to screen) this is the comparison of a survey of a certain gene through many different individuals. In this case nine individuals. You can see that the individuals differ with regard to the letter at this position (pointing to screen) in the gene. Most of them have a C, Some of them have a T. All of them have ACAAA in front of this position, all of them have ATAAA behind it. This is an example of a Single Nuecletide Polymorphism. And there are millions of them in the human population. The software produces the molecular address for this SNP and documents it into our database. Then goes back to all the chromosomes that we’ve studied and scores haplotypes for contiguous streams of SNP’s in each chromosome. For example one person may have contributed to a SNP. SNP-1 person 3 may have shown the presence of SNP-4. But what is the sequence of person 1 SNP-1 and 2. And so its more complex information. From this data were going to develop will be what we think are going to be the most intelligent genotyping experiments in the world. Because we will use our software which is in development, to distinguish which genetic positions show the highest power of resolution between haplotype expressions. If you can imagine a haplotype as 101 and a haplotype of 100, in order to learn what is one haplotype or other you must only sequence the third position. Because that is the only thing that distinguishes the two haplotypes. Well in a population you can imagine it is going to be much more complicated than that. And sophisticated software is going to be needed to determine what SNP’s should be sequenced in a population, And how to use that information to put together haplotype data from raw genotype data.
I think I’ll leave the technical sector now because I’m afraid I may be confusing many of you. Just suffice it to say
that we are working on a very difficult problem in a very hot field using truly innovative ideas. Ideas that have garnered a lot of respect so far. I mean we have got Orcid Bioscience to pay us upwards of approaching a half a million dollars just for the right to be first in line. To partner our products from us after we develop them. That is a tremendous honor.
That really (inaudible) the quality of our scientific ideas, many of which your unlikely to understand without a background in genetics. I can actually make a quick analogy for what we do with genetic data. If you look at a plot of weight versus height here I believe it is (pointing to screen). If you plot randomly collected individuals, you see very little pattern in that data. Some people have a high ratio of weight to height, other people have a low ratio. It makes no sense. What’s called a correlation coefficient doesn’t really exist here , If it were a correlation coefficient the spots would all line up linearly, either with a steep slope or with a gradual slope. But there would be a definite relationship between weight and height. You would be able to say that if somebody’s of this height you would know what their weight is by plotting it on the graph. But with this data there is no correlation coefficient. In order to find the pattern in this data you must add another variable to your model. In this case boys and girls. If we color the boys circles blue and the girls circles pink we see that the data really does fit a line. It shows a pattern and that we can with what we know who’s a boy and who’s a girl, we can indeed predict weight from height. This is an analogy for complex genetic analysis where as everybody else looks at things in very simple terms. This is why advanced mathematics and statistical analysis is needed in this field. So that we can do this type of work (pointing to screen) instead of this kind of work. Really come up with useful solutions in the future. Some other problems in the field right now that we address with our business model and our personnel, we use the best technology in the world. The Orchid SNP stream machine is the most cost efficient machine for genotyping. A half a million dollar machine. As I mentioned we are one of twenty companies in the world with access to that type of technology. Many of our competitors use slower technologies. Most of them deal with that. None of our competitors except a small group of maybe two or three are even thinking of developing sophisticated analytical tools that enable this type of result to be gleaned from this type of data. So that really is what our business model is focused on with the analytical space (inaudible) That’s where the bottleneck is.
We are performing our studies in terms of preferred haplotypes. I’ve already mentioned that advantage to you. That’s a serious advantage. We have good access to biological specimens and were building our partnership portfolio in that regard. Our competitors really, none of our competitors do all these things as we do. They may be better than us on other things. Sequenome for instance is certainly better than us at making hardware systems. They are not going to be better than us at producing data nor understanding it. Especially understanding it. Very few companies have the combination of resources that we do to be able to handle all of the problems in the field. For example Celera as I mentioned builds horizontal databases. They don’t have the vertical databases that are needed for this work. We’ll be one of a small group of companies in the world that will have these vertical databases. Some companies have vertical databases but there for specific and narrow regions of the gene. I mentioned the Incyte Genomics of the world (inaudible). Our vertical databases will be extremely valuable to everyone. Some of our competitors are actually software companies, software is a good business model to be talking about selling a product to every consumer in the world but it’s a lousy business model if all of your customers are just scientists. That’s why were not a software company. Some of our competitors, genotype based Pharmico Genomics develops solutions for (inaudible) experimental drugs. And there not true competitors of us for several reasons. Number one, they are working in terms of genotypes, not haplotypes. Number two, their focusing on experimental drugs , not drugs for the current market. That would be your Pfizers of the world, your Eli Lillys. Your Smith-Kline Beechams. They have an incentive to help increase there drug pipeline of new drugs. To get more drugs approved, not to go back and look at old drugs that theve approved and stratify that market. That would cost them money. They want to apply that type of technology to new experimental drugs so that they could tell the FDA sure the drug kills twenty percent of the people. They take it but we can predict with 100% accuracy who those people are going to be so in fact it effectively kills 0% of the people. That in a nutshell is what most pharmaceutical companies are using pharmacogenomics for . What were doing is looking at existing drugs. We may take their money and help them with a project like that if they’ll give us a piece of the product that results, but mostly were focused on the drugs that are (inaudible). Drugs that are hurting people right now as we speak, and drugs for which nobody’s going to come and address that were a pharmaceutical habit. They don’t have senses to stratify the market and to eliminate you as a customer because your livers being hurt . They’d rather you be prescribed the drug and rather than be found out that your liver is being damaged and being taken off the drug then to not have them prescribe the drug to begin with. That is very cruel. But it’s the way the world works. Companies like us are really the champions of the average patient. Were going to help you prevent that damage from the onset. Perhaps our closest competitor is a company called Genainsance Pharmaceutical. The only other company in this space that is using inferential haplotyping. Even they though haven’t invested as heavily in the mathematical side of the equation. To be able to uncover, other than simple associations between haplotypes and phenotypes. So we feel we have something to offer that they don’t. Even though they are a larger company than we are. Even if you were to take all the companies that work in basic genomics , group them together, you still have to consider, when considering competition, that compared to wireless or telephone there is very high barriers to entering this field. You really need P.H.D. level statisticians, mathematicians, geneticists. There are not that many of those people in the world compared to the Java programmers that can put up web pages.That is why in the internet space competition is a much more substantial concern than it is for a pharmacogenomics company. We know the medicine is going to change , the way its practiced in the future . We know that it is going to become more advanced. And we also know that small companies are going to spur a lot of that technological advancement because of some of the limitations I talked about. Big Pharma traditionally can’t hold on to the best talent. The best talent leaves big Pharma and starts companies like DNA Print Genomics. That turn into big Pharma down the road.
Specific questions, how long to market the typical product of ours would take 6 months to two years, and we intend to stagger them so that we have a steady stream of results coming out. I think you should look for the first results within the next 6 months to 12 months from now. Some of the projects that we are going to be working on are going to be easier than others and I would be inclined to predict the sooner completion rate for those specific projects but I think to be conservative were going to say 6 months to two years. The first project were going to perform, I think will probably take 6 months. It’s a simpler project and aside from the people in our company nobody really knows about it. And I really can’t talk about this easy project yet. You guys will learn about it soon. The other project were working on, such as the Staten’s project is probably a two year project. Another relationship were negotiating right now also will be a two year project. Each one will be different. In the short term our revenues this year are going to be very nice, you know, for a very young company that’s creating a (inaudible) market cap, its nice to be able to say that the revenues are going to be in the mid six figures for the very first year of existence. Long term our revenue growth will come from our diagnomic product portfolio. Short term it will come from partnerships such as it has this year from Orchid mostly and the contracts (taped stopped) Our burn rate is $90,000 a month (inaudible) And it will hold steady for the next year, year and a half. Our current funding arrangement is good for the next two years or the first two years of operation. We will be acquiring additional capital before that time elapses to extend our life through some sort of secondary financing. You will see this financing at a time when the markets clearly are in a better state to receive it. I am almost at the end here.
Question: Are you talking about an I.P.O.?
Answer: No we are already public
Question: So would you be reissuing your stock for this funding?
Answer: It would be either a private or a public placement. Actually whether its one or the other is really strongly contingent on what the market conditions are. Further questions about that can be directed to Craig Hall.
What I am trying to portray here is that we have a solid financial base to develop at least an additional portfolio of diagnomic solutions. All its going to take is one to make this company. Especially if it’s a solution that expands the market. When you consider that were going to be doing this drug after drug after drug and in each one of these drugs can have a different solution. That’s where the fortune 500 comment comes from and I stick by that by the way.
The role of Tampa Bay Financial is as our venture capitalist and public relations firm at present. Eventually we will do our own public relations. Right now we ear mark our dollar for research and development strictly. The role of DNA Print personnel as to day to day management in the company every decision that’s made in this company comes from management at DNA Print Genomics. The deals such as Orchid are negotiated by myself and other key people associated with our management on our payroll. Hiring decisions, budget management. The establishment of the budget, strategic planning day to day concerns. All DNA Print Genomics! That’s how almost all companies work. They take venture capital and are put off on their own. Either sink or swim. If you’re a good company you swim, if you’re a bad company you sink. Venture capitalists stand behind the scenes and watch what happens. They retain financial control over the company, always until the company has demonstrated its ability to live on its own. We think we will get to that point quite rapidly, like I said before all it takes is one product. Relationships with Orchid Biosciences , I’ve already talked about that relationship, quite an honor for a company at our stage of development. Geospiza, you’ve all read the press releases. We have a network of private physicians with Bob White. He’s managing for us, very adeptly I might add, he brings in blood specimens for the Staten project and of course were working on others (inaudible) My scientific advisory board you are well aware of who these people are. What they do basically,
Is for a company like us we cannot take our results and go out into the public and talk about them with other scientists. We would like to be able to do that so that we can get criticisms. That helps us mold a better product. There are a lot of smart people out there . Some of those people may have thoughts or ideas that we may have not thought of before. When you do that and you are a company like this you can sacrifice the integrity of your intellectual property position. Your letting your cat out of the bag so to speak. And that is what a scientific advisory board is for. There some of the most skilled people in this area . Critique’s of our work if you will. Guiders of our research. We pay these people with stock. Bob White is in the audience . He is part of our Statin project. He is actually a member of our board collaborators. We pay these people stock just like we pay our employees with stock . Salaries of our employees are probably below market. We work for stock. Which should make you feel comfortable . It makes me feel comfortable as one of the companies largest shareholders. There is a vested interest in the success and I applaud your courage in investing in a company at this early stage and I think you will be handsomely rewarded if you stick with us. Thank you very much. (Loud clapping)
Disclaimer: It is in my opinion that this text of open house for DNA Print Genomics was public domain. Tape recording device was in full view at all times. All material in this text is taken word for word off recording device. Nothing omitted except for inaudible where marked and nothing added that was not meant to be there. |
