Compugen Ltd (CGEN) 2003 Q4 法說會逐字稿

Ladies and Gentlemen. Thank you for standing by. Welcome to the Compugen Ltd. fourth quarter and year-end 2003 financial results conference call. [OPERATOR INSTRUCTIONS] With us online today are Martin Gerstel, Chairman, Dr. Mor Amitai, President and Chief Executive Officer and Nurit Benjamini, Chief Financial Officer.

I'd like to remind everyone that the Safe Harbor language contained in today's press release also pertains to all content of this conference call. If you have not received a copy of today's release and would like to do so, please contact Nurit Benjamini at telephone number 9723-765-8525. Mr. Gerstel, would you like to begin.

Thank you. To those of you in the US, good morning, those in Israel and Europe, good afternoon and to all of you, thank you for joining our call today.

In view of the sharply increased volume in the trading of our shares both on NASDAQ and the Tel Aviv exchange during the past few months, I assume we have some new shareholders on the call today. We wish to extend a special welcome to them as they join the Compugen family. Also, if you have not already done so, we encourage you to read our past annual reports, since they will provide some important information regarding the background and continuing evolution of our company.

Compugen is quite unique, and as such is not the easiest company to understand, or place a value on. Therefore, the most common questions we get from our shareholders and those considering an investment in Compugen take the general form of, well, it sounds great, but can you be more specific, or yes it is obviously great research but how are you ever going to make any money?

In today's call, rather than reviewing with you the events and financial results of last year, which in any event have very little to do with the value of our company, we will try to address these issues. If you have any questions regarding the information provided in our press release today, you are encouraged to raise them during the Q&A session following our presentations.

If you were to spend a day at Compugen, you would almost certainly hear two terms used repeatedly in management discussions. To understand what we are trying to accomplish and to appreciate the potential value of our company, the understanding of these terms is absolutely essential. These two terms are "probability of success" and "discovery engine."

"Probability of success" refers to the probability that any newly discovered potential drug will ultimately become a commercial product. Anyone with familiarity with the pharmaceutical industry knows very well that this is the number one major concern of the industry.

Costs of R&D continue to increase and yet, the number of new drugs at best is flat. The current estimate for getting one new drug to the market is around $800 million. Of course, the actual cost for the specific drug that does reach the market is much less, usually representing only a small fraction of the $800 million. Most of the costs relate to other drugs, which failed at various times in R&D process. Therefore, the extreme importance of probability of success in pharmaceutical R&D.

So, the first point to understand is that the sole focus for Compugen's research is to increase the probability of success of drug and diagnostics, discovery and development. Our pursuit of this objective begins with the evaluation of the key bottlenecks that now exist in the industry. We are not interested in improving a relatively minor aspect of the process, nor in making a modest improvement in a key area by speeding up or finding a way to eliminate some costs. We are interested only in pursuing key areas where we believe our unique capabilities can represent true breakthroughs.

There are two general classes of molecules that are used for therapeutic purposes. Small, synthetic chemicals, which are the primary focus of the traditional pharmaceutical industry, and natural, or almost natural, proteins and peptides that are the primary focus of the biotech industry.

In general, with respect to traditional small chemical research, currently, the key problems are finding and validating the targets that you wish to affect with your drug, and then finding a small molecule that interacts with the target without serious side effects.

On the other hand, the key problem in the biotech world is the discovery process of the new protein itself, since in many cases, the discovered protein will actually be the drug.

First, with respect to the traditional pharma industry and the task of finding a small chemical molecule that interacts with a target, the approach being relied on today by the industry involves massive trial and error experimentation based on combinatorial chemistry and high throughput, and now actually ultra high throughput, screening and other similar techniques.

In comparison, Compugen's program and LEADS discovery takes a completely different approach, an approach aimed at essentially solving this problem rather than relying under literally millions of hit or miss attempts. Although still at a relatively early stage, if successful, this program will clearly revolutionize pharmaceutical research and development.

With respect to both the finding of new targets for traditional pharmaceutical research and the discovery of new proteins for the biotech world, almost all current research by others in the field is again based on high throughput experimentation. Here, in comparison, Compugen relies on an iterative process of predictive modeling followed by hypothesis-driven experimentation, potentially yielding both discoveries and information, which in turn can allow the further improvement of the predictive model. This iterative approach is very powerful as will be more fully described by Mor.

It is important to note that our activities in this area, which we refer to as predictive biology, have accounted for the vast majority of our R&D activities to date.

So, with respect to improving the probability of success of drug discovery, we can already make a number of statements regarding Compugen's activities and capabilities.

First, without any doubt, we are working on the most important bottlenecks faced by both traditional and biotech industries.

Second, it is clear that our approach is unique, and requires the type of multi-disciplined, experienced research team that we now have, and which we believe does not exist to this extent anywhere else in the world.

Third, our discoveries to date provide incontrovertible evidence that the approach is working and already yielding valuable results.

And fourth, and probably most important, the nature of the iterative process we follow essentially guarantees that our capabilities and predictive models will continue to improve as time passes.

I would now like to briefly address the other key term with respect to Compugen, discovery engines. Here I will only make a few comments since this is the subject of Mor's presentation today, and he can, of course, provide you with much more specific information regarding the subject. However, to appreciate the value of our discovery engines, it is important to point out that although it may appear that the various components of Compugen's R&D activities, it may appear to be stand-alone capabilities.

As I mentioned earlier, almost everything we do is aimed at the single objective of increasing the probability of success of drug and diagnostic discovery and development. And in most cases, these various capabilities are mutually supportive and leverage off one another.

This is important since our discovery engines, as will be described by Mor, are comprehensive platforms that we create, bringing together everything we know and everything that we can find in the literature or in the research of others, that relate to a specific area of interest. These discovery engines are in sense production lines for pharmaceutical discoveries. And as such, we believe are unique in the world of pharmaceutical research.

Now, I will turn the call over to Mor Amitai, Compugen's President and CEO.

Thank you, Martin. As Martin mentioned, the embodiment of almost everything we do in our research efforts is in the form of discovery engines. Those factors underlie the (inaudible) of engines. First, is our unique ability emerging the computational and biological sciences. This allows us to incorporate in a meaningful way almost everything we ever learned in our own research efforts and forms the reported findings of others.

Second, based on these foundations, we have the ability to continually add new information to the engine as it becomes available.

Third, is the incorporation in the engines of our deeper understanding of important biological phenomena such as (inaudible) splicing and antisense.

And finally, the utility process that underlies all of our activities, predictive modeling followed by experimental validation, followed by improvements to the predictive model and so on, guarantees the continuing improvement and value of these engines.

Our infrastructure enables us flexibility and speed in our discovery forces. For example, the fact that some of our algorithm and software developers are part of our discovery teams dramatically decreases the development cycle of new software versions, from months to weeks and sometimes even to days.

In today's call, I would like to further elaborate on one of our most advanced discovery engines. To date, this engine has been used only internally, but as Nurit will describe, we are now evaluating various formats in which we might provide use of our engine to pharma and relative companies.

The discovery engine that I would like to describe is our therapeutic port invariant (ph) engine. This engine identifies novel splice variants of proteins that are known to have a therapeutic utility by combining knowledge arising from our unique transcripto (ph) model with information about therapeutic proteins that are now in the marketplace or in development by others.

The engine also enables the selection of proteins based on properties such as the existence of a single peptide-tissue distribution and various functional domains. This therapeutic port invariant engine, like other Compugen engines, is based on our elite platform, which creates the comprehensive view of predictive genes, emanalate (ph) transcript, splice variants and proteins along with little functional annotations.

LEADS models many complex biological phenomena and provides a comprehensive research infrastructure facilitating the development of drug targets and other biological products. The therapeutic port invariant engine extends the abilities of the LEADS platform by incorporating sophisticated mining algorithms to select the most promising therapeutic protein candidates from the myriad of protein identified by LEADS.

The use of this engine has resulted in the selection of our initial therapeutic pipeline. The proven capability of this engine enables us to state that we plan to add an additional six therapeutic protein candidates to our pipeline this year.

In addition, we are developing other therapeutic and diagnostic discovery engines. Using one of these diagnostic engines, we are looking for a novel market similar to the two novel PSA related proteins; most of you are already familiar with.

With respect to this specific discovery, it is important to note that an enormous amount of PSA-related research has been undertaken around the world during the past 20 years. Therefore, this discovery, along with our key findings regarding (inaudible) splicing and human natural anticsense clearly provides proof of the uniqueness and power of our approach. And with this, I will turn the call over to Nurit.

Thank you, Mor. As Martin mentioned earlier, today I will not be reviewing the financial results for the past year, but instead will attempt to give you some insight in how we intend to continue to develop our business model moving forward. During the Q&A session, following my presentation, I will be glad to answer any questions you may have regarding our financial results.

I would now like to comment on the commercial and financial aspects of our activities and plans as described by Martin and Mor. The first relates to our continuing effort to obtain deeper understandings of important biological phenomena and the related ability to use this knowledge in the analysis of large quantities of experimental data. In the past, the key commercialization pathway for this was our elite collaboration.

Looking to the future, these deeper understandings of biological phenomena will continue to provide important validation within the pharma industry of our underlying capabilities and is expected to remain a key aspect for commercial interactions with the industry. In previous years, an important aspect of our commercialization activities involved the development and sale of hardware and software tools, databases and other products in which we incorporated certain aspects of our understandings and/or discoveries and made them available to other companies.

As previously disclosed, these activities are no longer a focus of our company. We have divested some of these products, and may divest others in the future. An important new area for commercialization is the use of our discovery engines. As Mor mentioned, to date, our existing biological engines have been for our internal use only. However, at the present time, we are evaluating various formats for collaboration based on these and other engines. Our primary financial interest with respect to any collaboration based on our discovery engines is to have downtime participation in the products discovered through their use.

During 2004, we plan to approach potential partners with respect to these types of potential collaboration. Regarding our chemistry engine, which was briefly described by Martin and is at an earlier stage than our biology engines, we are now seeking a partner to continue its development.

Of course, the area that has the greatest financial potential for us relates to the specific discoveries that we continue to make through the internal use of our engines. As previously disclosed, we have initiated an internal pipeline of potential therapeutic proteins and have budgeted substantial increased resources to advancing this pipeline during 2004.

Another important infrastructure activity during this year is our planned expansion of our out-licensing capabilities primarily to pursue the licensing of discoveries that we do not wish to explore ourselves. With that, we conclude our formal presentation and open the call to any questions that you might have, both about the presentations today, and regarding our year-end press release.

Thank you ma'am. [OPERATOR INSTRUCTIONS] Our first question comes from Jeffrey Grossman. Please go ahead, sir.

Good morning. Hello, Martin, Mor, Nurit. Good afternoon. Excuse me. I'm little confused here. There was an interesting article this morning in Ha'aretz concerning the arrival of a senior delegation from Novartis to Israel. The article indicates that it is possible that Novartis will be examining during the visit, the expansion of cooperation with Compugen. I'm wondering if there is anything that you could tell us about this -- if this is in fact the case. Are you meeting with them? Is there anything that you can tell us about the nature of these discussions?

I'm sorry, but we're really not at liberty to respond to your question.

I understand. That was the answer that I frankly expected. That's all right. OK. Second question, how should investors be validating company's progress over the coming year? Should we be looking for additional articles? There was the article concerning antisense some nine months ago, and you said that related to actually discovery that occurred two year ago.

Should we be looking to see partnerships in the near future? Should we be expecting more particulars concerning the molecules that are in the company's pipeline, moreover, perhaps you could tell as little bit about what's happening with Evogene, I'm sure investors would like to know if there are any developments. And finally diagnostic products; has there been any progress in respect to the prostate cancer tests that they are developing and are there any milestone payments to Compugen?

Let me start with the easy ones. The company's policy is not to discuss any products or programs where we have licensed our technology or discoveries to other companies. We really feel it is inappropriate for us to comment. We encourage shareholders who wish to try and get additional information to contact the companies that we have licensed, you know, to commercialize the inventions. That specifically would be with respect to the D.P.C. question that you asked.

With respect to Evogene, I can say that they continue to develop well; there have not been any specific announcements of progress, but I mean, the company is proceeding as planned and I would hope and expect that during the year, they would be in a position to make some kind of comment or announcement, but again that would be up to them. Keep in mind that it is not a wholly owned subsidiary. It's a partially owned subsidiary; so they have to make their own decisions with respect to disclosure of information.

With respect to the beginning of your question, you actually gave a very nice summary of the types of things that we should be looking for additional scientific papers, different types of collaborations, progress with respect to our initial pipeline. You know, all of the things that would continue to sort of validate that -- that we are very unique discovery company. You know, that we continue to move forward with the building of these engines.

As Mor stated, I think if people really just sit down and look at what we have already announced publicly, it's very hard not to come to the conclusion that there's something very special going on here, with all of the research worldwide that's going on in you know, in genomics, and proteomics and whatever for so many years for this tiny little company in Israel to be the first one to identify such basic things as the common occurrence of all of alternative splicing, which is interesting, which we have been talking about now obviously since we went public; we made the discovery back in the late 1990's. You are now finding companies being formed solely around the concept of alternative splicing. There are actual companies now. The interesting now we have been doing this as a part of our activity for the last five years now.

And yet now we see funding companies based on this concept. So, it is that one. There's anti-sense, which as when we finally announced it, two years after we made the discovery, it was still news enough in the scientific world to be the cover feature of nature biotechnology in the course of PSA (inaudible) from other specific discoveries we disclosed. I think anyone looking at that would have to come to conclusion, that either we are the luckiest company that has ever set foot on the earth or there is a very, very unusual and powerful discovery capability that's been created here.

OK. Another question. Concerning the chemistry project in Ashkalon, can you provide us with additional information concerning the level of interest that has been expressed by potential partners? Also, perhaps you could indicate whether there's been progress in overcoming the problems that were referred to during the third quarter conference call.

I'll comment first and then Mor may wish to say something additional. With respect to the chemistry project as we've stated, it's at an early stage we have had reviews by many outside experts, and haven't had discussions with a number of pharmaceutical companies. All of them have ended up in a very positive way with respect to the concept and the way we are going about it.

However, at least with respect to the pharma companies in general, the feeling was that in view of the pressures that they are under with respect to their short-term pipelines, that they would like to see more validation before actually committing to, you know a program of this magnitude. And that is what is largely going on now in the company and as additional validation while we are continuing to talk with some potential partners.

But as we stated, although we clearly have the cash in the bank that we could do this on our own, it doesn't, as Nurit has said many times, we manage our company on a cash flow basis and so we're not going to increase the burn rate in order to take this program to the next level. So, that will require a partner coming into the picture.

OK. But Martin, are you satisfied with the progress being made?

I'm never satisfied with anything. I would say that, I was very disappointed last year in that we weren't. I was hoping we would get a partner for the program by the end of the year. But it's clear that as I said that pharmaceutical industry right now in general is kind of focusing on short term -- you know, there are problems with the short-term pipelines and not really looking for long term, more research type or situations. So, but that was a real disappointment, real disappointment for me.

On the other hand, I was very pleased to see the obvious. I think a number of times these groups either outside consultants or the pharma companies kind of came here with the idea or reviewed the project started to review the project with the idea they would clearly show us why it wasn't going to work, and no one has yet. I mean, everyone who has reviewed it, has come to the conclusion they don't see any reason why this isn't going to be successful.

I want to make it clear, no one has said we believe it will be successful. But no one has said that, you know -- no one has pointed out a reason why it theoretically should not be. It really isn't from one standpoint; it's an outrageous program. If successful, it will so revolutionize the pharmaceutical industry probably in a way that no single breakthrough has done in the last 50 years.

OK, But again concerning the technical progress over the say past six months, can you say that you're satisfied?

Well, I think Mor in a better position to comment if he wishes to, with respect to the technical progress on the program.

This is an extremely as Martin stated, ambitious program, and requiring very substantial financial resources. And we have made a decision to invest this is sort of just together with a partner, and our key objective is to perform additional validation, studies in order to give us and the potential partner more information about the risks in this project, and hopefully, if this is the validation studies are successful, and to reduce the risk and be more confident that it's going to work and that it deserves quite substantial financial investment that it requires.

Jeffrey, can I ask you to sort of hold for any additional questions?

I have just one more if it's possible.

Let's wait.

OK.

And see if there are no other questions.

OK fine. No problem.

OK. (Operator Instructions) Our next question comes from Roland Liveous (ph) of Liveous Associates. Please go ahead, sir.

Congratulations, Martin, for the progress that your company is evidencing. I just have one short question, are you in your search for partners, are you also looking in the Asian market for partners?

Well, as of now, we have not. Now, let me just say moving forward in the future, you know, we may get into a situation where we will not be in a position to answer questions like that, so I don't want to sort of set, but just to not mislead you, we have, as of now, we have restricted our discussions to sort of top tier pharma companies. I'm sorry -- mainly in the United States.

And Europe?

And Europe. OK

I just one question on this last point. I imagine that your technical people are more aware of this, but to what degree do you think the Indian pharma companies are moving in the same direction as Compugen?

I don't think from what I know, I don't think they are at all. I think they're manly focusing on production aspects. Do you know, Mor?

I haven't heard of any.

Organizations in India or, you know, basically any that are sort of focusing on the approach that we take. If you have the information, you know, we would like to receive it. I should also sort of follow up on your first question, if you remember in Nurit's presentation today, she said that one of our key infrastructure objectives for this year is to really build up our out licensing and our business sort of development capabilities.

So, I mean, when you ask, have we done anything in Japan, a part -- I mean, if you ask why, it's you know, sort of, we have been very, very limited up until this point in time and still with respect to our -- you know, the extent of our capabilities in out-license. I think we're reaching the point now where we have such an inventory of discovery, that it makes sense for us to build up that capability in the company.

Thank you.

Thank you. Our next question comes from Roland Over of Capital Partners. Please go ahead, Sir.

Good afternoon. I just wanted to get a little bit of understanding. You talked in the first part, Martin and Mor, about the increased probability of success. To me, there are two parts to that. This is what I want to gain a better understanding of. Is the implication here that proteins for example, might be killed earlier in the discovery process so that taking down that overall cost of $800 million to a fraction thereof is, because you avoided failure on the one hand or is it because of the discovery process, you can identify better functionality or if you have a particular target, you are going after, you can iterate back and then derive a better class of let's say proteins to target, what you are trying to target, from an iteration point of view?

I'm trying to understand from a modeling point of view how you derive this increased probability of success. How you define that? Can you shed more light on that?

Sure. Actually, you touched the two aspects of increasing the probability of success that we believe that we will benefit from. The more important is the second one. We believe that we have capabilities through the engines that we use and continue to develop to identify proteins and indications, and in which these proteins have substantially higher probability to become drugs at the end of the development process compared to the usual case in some sort of industry and so, this is the key.

You look back from the target basically?

Yeah. This is the key aspect, and this is what we are looking for, and I can elaborate a little bit more with respect to the engine that I mentioned. For example, when we find (inaudible) splicing of an existing drug that is under development on the market or actually even felt during the development, and sometimes what we find is that protein, on one hand, has very similar properties, many properties to the original protein, and on the other hand, it is different in some aspects. And if similar in the desirable properties, but is different with respect to some weakness that is known about the existing drug or the drug that is under development, and this can lead to having a substantially higher probability of success. And this is actually a specific example of what we are -- of some of the things that we are looking for using this engine.

It's a refinement process to some degree.

Yeah. It's an iterative process. And in each iteration, we learn more and improve the engines, but we also believe that some of the discoveries from the beginning have higher probability of success, and this is the key point, and this is what we are after. These guides all of our discovery projects, and however the first point, the point that you made is also an advantage, and because when we start a discovery project, we know exactly what -- what are our assumptions. We believe that this protein has certain list of properties, and this is what we predict. Sometimes these engines -- no, the predictions fail, and because from the beginning where we have a very well defined list of properties that are predicted, and it is also easier to perform certain validation experiments that are much more easily than usually can show us that the assumptions or the predictions were incorrect, and the cost of failure, which is a key component of the total cost of software development, and we believe is also substantially reduced by this process.

Thank you.

Thank you. Our next question comes from John Sullivan of Stevens, please go ahead.

John Sullivan of Stevens. Congratulations on advancing your plan. I had a couple of questions about what I read in the press release, if you don't mind. Could I just ask you regarding the 4 novels splice variance that you highlight in one of your bullet points? Are we to assume that you will undertake free clinical work yourself and animal model work yourself, or will you expect that that happened after a partnership is struck?

The process is that we are undertaking with each one of the discoveries is first in vitro validation of the prediction based on which we have chosen this protein. We are going to terminate the project that the validation doesn't approve and continue to animal studies with the discoveries that -- the in vitro experiments validate the computation in human prediction. And we expect that most, if not all of the animal model studies would be done by Compugen or out-sourcing, but it's Compugen will lead and manage the process and we are looking for partners. In general, we are looking at partners in the most advanced stages after the animal studies.

So, it's your intention to take the risk of the animal studies yourself, whether you farm it -- whether you out-source it or do it yourself, and then at that point, more aggressively seek a partner.

We feel comfortable that the proteins that we choose especially after -- especially after the experimental validation, have higher probability of success and that the risks in Compugen performing the animal studies is reasonable. And in addition, we have -- we are choosing the discoveries over the potential device that we are working on from a relatively large list of potential develops. And we are using certain material when we choose which potential drugs to work on.

Some of this material relates to the probability of success of the drug and to the potential therapeutic utility and medical need, but in addition, we also take into account not just our valuable -- how valuable this drug is in general, or what is this drug's general probability of success, but also we try to estimate the feet of this potential drug and Compugen capabilities, and we in general, we prefer and fortunately, we can choose, so we are able to take it into account. So, in general, we prefer proteins for which the animal studies are relatively simple, and that we are not too big undertaking for Compugen.

I think this discussion points out one of the real differences between Compugen and sort of at least with respect to the biotech industry that our - what we have mastered now, the - sort of the initial discovery process from the standpoint of identifying, you know, the transcript tone and potential products. Keep in mind that theoretically, when we say that we have a predictable model of the transcript tone, that means that within our predictive model, essentially, all of the therapeutic proteins that have been discovered or will ever be discovered by anybody. Now it sort of changes and also with respect to protein targets, the same statement can be made.

So, what that means is that the key challenge for us is a very different challenge than for most of the industry. Our challenge is not to discover things. Our challenge is to select from amongst our discoveries, the discoveries which we believe have a higher probability of success, and therefore, are worth -- you know, are worth pursuing. And that's why we focus so much in the company on this probability of success. It's not a question of what's doing -- us lots of experiments and finding something that looks like we ought to explore it. We predict -- you know, literally, we predict tens of thousands of potential products, and then we utilize all of the things that Mor was talking about in order to prioritize and the key for prioritization is probability of success.

I appreciate all of that. Thank you very much. Let me just go on and ask another question, if you don't mind and thank you for the perspective. You talk about also in the press release that you intend to add another six proteins from your inventory of discoveries to your therapeutic pipeline. Do you know enough to be able to confirm that those are also come from the therapeutic protein variant engine?

Most of them -- most of them will come from the protein variant engine, yes.

So, it's reasonable to expect that most of them are slice variants of a FDA approved and commercialized bio therapeutics.

Not necessarily. We are also interested in variants of drugs that are not yet approved, or under development, and even of variants of drugs that have deferred. We have fair reason to believe that the reason for failure is something that exists in the original drug but doesn't exist in (inaudible), we may choose this protein.

Is that broadly how we should think of your starting point for applying your tools and expertise that you start with --you start with drugs or drug candidates in one of three classes. You either start with FDA approved drugs or you start with drug candidates that are now working their way through the drug development process, the clinical development process, or drug candidates that have failed but are interesting to you, because you think they're a good fit with your expertise and tools?

Yeah. This is a very fair description of the most advanced engines that we have, and we do expect that most of our new candidates will come from this engine. We have and we are developing additional engines that are different, but it is correct what you should expect that we will -- we will enter our pipelines are these types of potential drugs.

To make it clear, the process is it's a two-step process in prioritization. The first step is exactly what you just described, that out of all of the potential discoveries as of now, at our current stage of development, we are looking at those where somebody else essentially has already said, this is something worth looking at, either because there's a drug out there or is in develop development or as it's Mor said one that failed. But we have slice variants. That's the first criteria that a product -- that a potential candidate has to go through. The second is that we have to have reasonable reason to believe that our candidate will be superior to what is already out there. And you know, that can be superior in many different ways; efficacy, stability, many different formats.

But here, you know, we kind of have an unfair advantage in some way in doing that, because we know what's already there. It's out there. It's reported. So, you can look at that and don't forget, in our predictive transcript tone, we not only have our, but we have theirs, too. So we are in a position to actually look at their transcript protein and look at the alternatives that we have and then come up with a -- look at and say, OK, you know, it --the one they already are developing, do we believe that's the best one. If it is, they probably found it by luck. By luck, they may have found the best one.

We, on the other hand, have done by prediction. We have predicted all of them. Now, we can look and compare. So, those are the two steps. One, first, to make - because we are still at a modest sized company that we don't feel we can be breaking new ground and new families of proteins and whatever. So, we're looking for areas where people have already said they're important and, two, the second screen, which is just as important, perhaps more so is that we have to believe that our transcript, our proteins has some significant improvement over the ones that are already out there.

Just one clarification. Whenever Martin says all, the meaning is -- all of the variant that we could find, in many cases I believe it's all the variant, but clearly, we don't have any guarantees, these are all the nature of variant and in some cases, of course these are not all the variants.

If I gave the impressions that our engines as of today are perfect, I overstated it. They won't be perfect until next week.

Thank you very much and congratulations on the progress.

Thank you.

Thank you. Next question comes from Randy Hough of Lion's Share, please go ahead.

My question has been answered fellows, great progress. Thank you.

Thank you.

Thank you, and do we have a follow-up question from Jeffrey Grossman? OK, you can ask, Sir?

OK. Me again. Every biotech company these days is touting its molecules. Many small companies have molecules in phase one, two or three clinical trials and yet they are not succeeding in finding partners. I'm just wondering why you think perhaps that you will be succeeding in finding interest in another two or three years where these other companies have failed and do you think your cash will hold out until then?

This is a challenge that is well pointed and we hope and obviously we cannot guarantee, but we do hope that we will be able to convince the pharmaceutical and biotechnology partners -- that our potential will really have a higher probability of success. If we are successful in convincing them in what we fully believe in, and then I think that it will be much, much easier than and it looks from the experience of other companies because (inaudible) companies, they are not really looking for advanced sales and development, they are looking for reducing the chances of failure.

One way, and this is by far the best way to provide this to them, is to have very advanced product. If you have an FDA approved product, there is almost no way. If you have a phase three product, it has relatively low. This is by far the best validation. We believe that we can do something that we will be able to convince them that what we have, although in early stages, in terms of the probability of the success of the risk of failure is equivalent to a candidate or drugs that are much more advanced and this is one of our key challenges in the coming year.

Can you tell me approximately when you expect to have -- well, maybe you can't, your first molecule in phase one trials?

We -- the thing that we have stated in the press release, and if I don't find it in the press release, obviously, I will not be able to say, but we stated that our midterm goal is --which means -

Three to five years.

More than two, less than five. Goal is to (inaudible) not just a first candidate in human trials, but also a continuous pipeline of at least two candidates getting into clinical trials every year. And again, this is, as Martin stated, this is one of the differences between us and other companies, and it has advantages and disadvantages, but this is a real difference. We are not looking so much as the most advanced candidate or when the first one will get into a certain state of development, and we're investing almost all of our efforts in building a continuous pipeline of entering the enterprise and advancing further. So, I believe that the two (inaudible) we are looking at is not just the first, is when we will really be able to show that it is working, and we have continuous pipeline of molecules and engines supply.

It's interesting to note that in one way, we are one of the few, maybe the only company at least that I'm aware of. That is really trying to address the key problems faced by the pharmaceutical industry. The key problem faced by the pharmaceutical industry is the predictability of the pipeline, of having products in the pipeline. It's interesting to note that the industry is essentially given up on that from the standpoint of their internal activity and most of them have set up tremendous groups for in-licensing. Because they come to the conclusion there's no way they can count on their own research groups creating pipelines in the future. And of course, the financial community has given up, you know has given up on that concept. It doesn't even think about it.

And I find it quite interesting that you can talk with any financial analyst in the drug business and they will agree that the most critical problems for the industry is how are they going to have a continuing flow of new products in the future. But then what do they do? They go and look at the pipeline and that's how they judge companies. And it's interesting when analysts judge companies, and the drug industry, they don't care whether the drugs were licensed in, or developed internally.

Now, obviously, with respect to the commercial success or failure of an individual drug, it doesn't matter at all whether the drug was licensed in or developed. But from the standpoint of valuing and coming up with some conclusion as to that company's capability, of course, there's a big difference in whether they develop themselves or licensed them in, and if you look at just about every big pharma company, what you will find is most of their pipelines are licensed in. And so, you know, the industry has given up on it, the financial community has given up on the concept, because it's so difficult, everybody -- they don't even focus on it anymore.

I mean, to highlight how -- what I'm saying is if you were concerned about a certain country being able to feed itself over the next ten years, it would make no sense whatsoever to go and look at what food is in their warehouses you know, today, and not ask yourself for -- did that food get there because it was shipped from the United States, did it get there because they --developed it themselves. You wouldn't look in the warehouses. Would you look at the capability of growing food?

Now, in our industry, it's been so unpredictable that everyone has given up. And we find it even when analysts try to analyze our company, as even after they, I think they understand the company, they fall into this trap of trying to figure out how valuable is our pipeline.

Let me look at the drugs that you have, and let me decide because they're so used to valuing companies by their pipeline, and that is the way you should evaluate a big pharma company, because they don't have the capability of, you know, assuring you there's going to be a continuing flow of discoveries. We are addressing that head-on. I mean this is what we are doing. We -- I mean, and -- and the issue is one of when we look at our initial pipeline, if all of these drugs fail, what that will say is that we probably selected them too soon.

All right. That because every day as we continue to work on these discovery engines, our knowledge and our insight into the probability of success of our discoveries goes higher and higher and higher. That's people sort of say, we could have picked our initial pipeline two years ago, but having picked it now, or last year rather than two or three years ago, we're probably in the end, we have a higher probability of success with the molecules that we picked and probably will get there faster because we know so much about them now than two year ago. No I'm not aware of anyone else, any other company, big or small in the industry that can make this kind of a statement.

Martin, just one follow-up question. Given that you have another $60 million of cash and given the burn rate of some $15 million a year, that gives you about four years. Shouldn't the company be looking for a strategic shareholder?

Do you have a lot of money, Jeff? Well, first, I think when you said we have four years keep in mind that we basically -- your math was right, but we really have sort of, you know, two years before we -- I think a company like ours should never allow itself to get in a situation where it has less than two years of cash in the bank. So, we basically have one to two years to really put ourselves on the map, and be recognized. You know, I don't think it's a question. It's interesting. I don't think it really is a question of what we can accomplish over the next year or two. I am very confident, we're going to accomplish a great deal. In my judgment, it's more a question of the financial community beginning to recognize what exists here.

And you know it's really fascinating to look at what happened over the last, I don't know, three, six months. We have had a very strong stock market put with our -- we haven't made a single announcement, and yet the volume and the price of our stock has gone up significantly. That obviously means that what's happening is people are buying because of an awareness or recognition that there is something fundamentally special here. It's not that, because, we made an announcement about A, B, or C, we will continue and I think the nature of our research effort is such that it almost guarantees that, you know, that we will continue to make discoveries.

I think as Mor was describing the process, is that every discovery we make increases the odds that we will make additional discoveries. No one else that I'm aware of can make that comment when you are doing, you know, high throughput experimentation et cetera. So, I'm getting told by all my partners here that I should stop talking. They all want to go home and have dinner. So, OK I will stop there.

Thank you very much.

Thanks.

Thank you. There are no further questions at this time. Before I ask Mr. Gerstel to go ahead with his closing statement, [OPERATOR INSTRUCTIONS]

Thank you. This evening my closing statement will be an hour half long. You may wish to get a drink or do something now. Whatever, actually, I just wanted to again say thank you for participating today. Obviously, we had a number of new people on the call, and we really want to welcome you, and if you need additional information, we encourage you to contact us.

I really do think that all of our shareholders to read our reports now -- take if you have them, if you don't, get in touch with us. Take out our old annual reports, and read them. Because, you know, we are now beginning to harvest -- you know, our efforts of many years, and if you read through those annual reports, you will clearly see, you know, the very clear evolution and planned evolution of a company which I think is going to revolutionize the pharmaceutical industry.

So, with that, I thank you, and good morning or good evening depending where you are. Thank you very much.