Yield10 Bioscience Inc (YTEN) 2016 Q4 法說會逐字稿

Welcome to the fourth quarter and year end financial results conference call for Yield10 Bioscience. (Operator Instructions) As a reminder, this conference is being recorded.

I would now like to turn the conference over to your host, Yield10 Vice President of Planning and Corporate Communications, Lynne Brum.

Thank you, Tim, and good afternoon, everyone. Welcome to the Yield10 Bioscience year end 2016 conference Call. Joining me on the call today are President and CEO, Dr. Olly Peoples; Vice President of Research and Chief Science Officer, Dr. Kristi Snell; and Chief Accounting Officer, Chuck Haaser.

Earlier this afternoon, we issued our year end and fourth quarter 2016 news release. This release, as well as slides to accompany this presentation, are available in the Investor Relations section of our website, yield10bio.com.

Now let's turn to Slide 2. Please note that as part of our discussion today, management will be making forward-looking statements. These statements are not guarantees of future performance, and therefore you should not place undue reliance on them. Investors are also cautioned that statements that are not strictly historical constitute forward-looking statements. Such forward-looking statements are subject to a number of risks and uncertainties that could cause the actual results to differ materially from those anticipated. These risks include risks and uncertainties detailed in Yield10's filings with the SEC, including the Company's most recent 10-Q, and we plan on filing our first 10-K as Yield10 next week. The Company undertakes no obligation to update any forward-looking statements in order to reflect events or circumstances that may arise after the date of this conference call.

I will now turn the call over to Olly.

Thanks, Lynne. Hello, everyone, and thanks for joining our call tonight. So please turn to Slide 3 and we'll cover a few financial highlights, starting with the balance sheet. We ended 2016 with $7.3 million of cash. We expect that cash on hand, together with revenue expected under current government grants, will support our operations in the fourth quarter of 2017. We estimate cash usage in 2017 to operate Yield10 will be approximately $7.5 million to $8 million, including anticipated payments for restructuring costs due this year. We will continue to identify ways to access capital for the financial markets, generate revenues through grants and collaborations and manage our expense base.

On our P&L, let's review the financial results under reported discontinuing operations where the operating results capture our crop science-related activities as well as administrative and infrastructure support for the Yield10 business. We reported a net loss from continuing operations of $9.2 million for the full year 2016 or $0.33 per share. Our net loss for the fourth quarter was $1.6 million and reflects the requirements for operating as Yield10. We reported [$1.0 million] in R&D expenses, $800,000 in G&A in the fourth quarter. We also reported $300,000 in grant revenue.

At the end of the year, we had 20 full-time employees. We believe that with this profile, we can achieve our 2017 milestones by managing with a lean organizational footprint. For more details on our financial results, please refer to the earnings release.

Now let's turn to Slide 4. Over the last 2 years, we developed a new strategy to take our crop science programs forward and announced the Yield10 Bioscience business last September focused on developing technologies to enable step-changes in crop yield on the order of 10% to 20%. Crop yield is a fundamental driver of value for farmers and a key decision variable for which seed they buy, and this impacts both revenues and market share at the major seed companies.

Yield10 is targeting a critical unmet need in agriculture. With the global population expected to exceed 9.6 billion people by 2050, there is a need to increase global food production by around 70% in this time period. This will need to be achieved in the face of increased pressure on land and water resources in addition to increasingly variable weather patterns. Solving this problem is a major global challenge requiring new crop innovation and technologies at a time when the sector is undergoing its own restructuring.

In fourth quarter 2016, we named the management team for Yield10 and set the stage to rename and rebrand as Yield10 Bioscience with a new ticker symbol, YTEN, which we executed in early January. In 2016 we conducted a field test with our C3003 yield trait gene in Camelina and in early 2017 we reported results. In the best-performing lines, we saw an up to 23% increase in seed yield by weight. The significance of this result is that it shows that our technology approach can produce step-change increases in yield.

Earlier this month, we also reported promising greenhouse results for our second-generation C3003 yield trait gene in Camelina. We also outlined our plans for spring 2017 field tests of our C3003 trait in Camelina and canola. We expect that this will start in the second quarter. We also announced that we have executed an exclusive option with the University of Missouri to evaluate a promising gene editing target for oilseed crops. We also expanded our scientific team with 2 key hires: Dr. Karen Bohmert-Tatarev as Technology Manager and Dr. Frank Skraly as Senior Director of Metabolic Engineering.

In addition, we appointed Richard Hamilton to our Board of Directors. Richard brings more than 20 years of experience in agricultural biotechnology, genomics, strategic partnerships and finance and we look forward to his contributions to Yield10.

As we have transitioned to Yield10, I would like to thank Matt Strobeck and Celeste Mastin for their service on our Board. As part of the transition, they stepped down from the Board in the first quarter.

So we are off to a good start in 2017. Now turn to Slide 5. We are focused on achieving our milestones for 2017, which will help us build significant value in the business. Yield10 has a strong pipeline of crop yield trait genes derived from our 2 discovery platforms: the Smart Carbon Grid for Crops and the T3 Platform. These platforms were developed over the last 5 years as part of our efforts to increase carbon fixation in plants. As expected, we will be taking our C3003 yield trait gene forward in studies with Camelina, canola, soybean and rice. We also plan to progress a number of Yield10's additional trait genes in Camelina, canola, soybean, rice and corn. In corn, for example, we plan to leverage third-party services for the resources and infrastructure that are already in place. We will also seek to partner for different crops under traits where it makes sense.

Genome editing in crops has the potential to significantly reduce development costs and regulatory timelines for crop trait development. At least that is the current view based on the recent DuPont USDA APHIS announcements on an edited corn line, and regulatory rule changes currently being developed by USDA APHIS. Yield10 has identified and/or in-licensed a number of interesting gene targets for genome editing in crops. We've also made substantial progress in deploying the CRISPR/Cas9 technology against the first of these targets in Camelina. We expect to increase our level of effort in this area and other crops, particularly canola over the course of this year.

Securing Ag industry collaborations is something we will continue to work on. We will continue the work we have been doing with our academic partners and expect much of the work to be republished in academic journals. Intellectual property and patents are very important to the success of Yield10, so we will continue to build multiple moats or barriers around our key trait technologies. So overall, you can see we are expecting a very productive 2017.

Let's now turn to Slide 6. We have used our 2 technology platforms for discovering novel yield trait genes. In our Smart Carbon Grid for Crops, we are leveraging some of the discoveries made in the last 10 years in industrial and algal biotech space, which identified new enzymes and metabolic activities in nonplant systems that can be leveraged to debottleneck known carbon limitations in crops. Some of the biology challenges around yield in crops are well understood, and we are accessing capabilities that crops simply don't have today and introducing them from algal and microbial species to address those limitations.

Our T3 Platform is a computational process to identify small numbers of very powerful, global transcription factor genes or master switches. Here, we are mining big datasets to identify yield gene targets that may serve as master switches or global regulators that can pretty much override the crop's macro control systems and essentially boost the entire system within the crop. The idea here was that if you wanted to increase biomass, then you had to increase the activity of the entire plant system. We experimentally tested at 3 lead gene targets in switchgrass and achieved average increases of over 40% in photosynthetic carbon fixation, [indiscernible] central metabolism and biomass level. These are our C4001 to C4003 traits.

To create value from our discoveries, we need to get our trait genes into major crops for testing in the field. Firstly, go into Camelina because this can be done relatively quickly to generate additional data and in parallel, we begin the process of deploying our yield genes into canola, soybean, corn and rice.

As Yield10 Bioscience, we see it as our job to discover potentially breakthrough yield gene technologies for step-change increases in seed yields to prove they work and optimize them in the field using our Camelina plants field testing system and to progress them in canola, soybean and corn to develop data for the seed sector. So we are positioned in the translation phase, where we are assessing their potential in Camelina as well as commercial crops. For the commercialization phase, we expect to partner with ag industry players so we will focus on what we are good at, which is discovery and innovation.

Let's now turn to Slide 7. There are different genetic engineering technologies that can be used for deploying of yield gene traits. We are frequently asked by investors to [relate] these technologies to the regulatory process.

So let's start by looking at the left-hand side of Slide 7. We have 4 scenarios for making changes to the plant genome. The first scenario is most similar to plant breeding, where performance of the crop is increased, genetic engineering is not used, and no new DNA is introduced. In this example, the plant would not be regulated. Research also shows that this approach is unlikely to solve the crop yield gap, which is essential for global food security.

In example 2, which is most similar to the current GM or regulated crops, we have a plant produced through genetic engineering with a nonplant gene or a gene from a different plant species or foreign DNA. This is considered GM and is regulated by USDA APHIS. For examples 3 and 4, we can envision improving crops through genetic engineering, where a plant gene from the same species is inserted with no foreign DNA, a plant gene is deleted or its function knocked out using genome editing. In these cases, we see the potential for improving crops in a system that is outside of the historical regulated process.

We expect to produce yield improvements that will be regulated or GM, but we also see the potential to bring forward traits [first] gene editing or using only genes and DNA from the same plant. That may fall outside of regulation and this has the potential to streamline the path to commercialization. I expect the industry will go looking for field targets that fall outside of regulations to rapidly expand performance that can be offered to farmers in the near term.

Let's now turn to Slide 8. Our crop science program was in stealth mode for about 5 years and produced a number of truly exciting yield trait genes for crops. Some of these, by definition, are only achievable through genetic engineering, but results in GM designation [obviously may] be unregulated. So for example, C3003 is going to be, by definition, GM. So selecting this target for investment, the real issue is, will the value it creates be large enough to offset the cost of getting approval? Some of our targets are amenable to genetic engineering without adding foreign DNA (inaudible) the control sequences for these trait genes and/or introduce additional copies into the plant. Some of these targets could result in a significant increase in seed yield or value. Some of our other targets are suitable for genome editing.

One example of this is the gene editing target we have optioned from University of Missouri: C3007. C3007 is a gene whose activity can be reduced to enable oil seeds like canola to produce more oil, which happens to be the key value driver for canola seed production. C3004, C3007 and C4004 are gene traits that are amenable to genome editing. We are currently editing C3004 and C3007 in both Camelina and canola in our operations in Saskatoon, Canada.

Let's now turn to Slide 9. We have multiple opportunities in the pipeline, limited resources and likely capability to move our yield trait genes forward in all crops simultaneously. So we asked the question, does it bring new science to (inaudible) yield limitation? Is this a really unique piece of technology? Acreage potential is really, really important here. You don't want to invest a lot of money in developing something for small [increase] crops. Will the new trait be effective when transferred into all of the different germplasm or plant varieties? In corn, there are lots of varieties used in different geographies throughout the United States. Same for soybean.

We also consider whether a trait could become a franchised trait, similar to Roundup Ready. The Roundup Ready trait has been translated through a number of major crops -- canola, soybean, corn, alfalfa, sugar beets -- simply because the microbial gene used enabled the plant to do something it could not otherwise have done at the time it was developed.

And leverage third-party resources. One of the things Yield10 is going to do and has been doing is being very effective at leveraging third-party resources and capabilities on a fee-for-service basis. We also look at the economic potential based on the results we achieve in our studies. And I think the final decision criteria, which is, can you achieve the result by gene editing, such as using CRISPR/Cas9 or related technologies, where the regulatory hurdles are potentially much, much lower.

Let's now turn to Slide 10. In terms of value creation, there are different ways of looking at this and obviously it's a lot more complicated than what's on this particular slide. But the bottom line is if you can increase canola seed yields by 20% -- keeping in mind we have demonstrated 23% for Camelina -- if we could translate that into canola, there's a very, very meaningful economic impact in that sector. If we can calculate the value of canola production based on the 2016 harvest of $9.6 billion, 20% increase over time represents $1.92 billion of additional value capture per year.

Soybean is much larger in terms of its acreage. There are 80 million acres planted in the U.S. It's also about $10 per bushel, which was about $40 billion of market value last year. So a 20% yield increase represents $8 billion potential added value. These are C3 photosynthetic crops. For a C3003 yield gene trait, we believe it has a pretty good chance of having a significant impact in these oilseed crops.

Corn is a little different. So we're not yet sure whether C3003 will work there or not, but we do have other traits in development from the C4000 series that apply to corn. A 10% increase in corn seed yield, which is about 18 bushels an acre, would add an additional $5.16 billion in value annually.

It's also obvious we're not going to be capturing this level of economics all by ourselves. But I hope this example illustrates that we can build significant value for our business, testing our traits in our model systems and then translating the most promising traits into agriculturally significant crops. So our goal is to generate proof points in canola, soybean and corn.

Now I will turn the call over to Kristi.

Thanks, Olly. Let's now turn to Slide #11. We have been progressing our work with the C3003 gene aggressively over the last 2 years. C3 photosynthesis is the key photosynthetic pathway in crops like canola, soybean, rice and potato but has a very well-known limitation or inefficiency. The inefficiency is caused by a side reaction of the carbon-capturing mechanism, which results in about half of the carbon capture being lost again, and that has significant yield and hence, economic consequences for C3 crops. For example, models suggest that C3 photosynthesis, which is the primary driver of yield, could improve by 12% to 55% in the absence of this side reaction and that a 5% reduction in this side reaction could result in about an additional $500 million a year of economic value just in soybean and wheat in North America alone. So obviously, addressing this particular scientific problem, solving or reducing its impact could have enormous economic benefits.

Let's now turn to Slide #12. C3003 was a scientific discovery from a university laboratory. It's very unique and Yield10 has been fortunate enough to capture the exclusive worldwide license to C3003 and has worked to build a patent portfolio around this discovery. We tested Camelina engineered with the C3003 trait in the field and reported the results earlier this year.

Camelina is an industrial oilseed crop, which is really useful for trait development because you can progress from the initial genetic engineering to field trials fairly quickly. Keep in mind, "quickly" is a relative term in agriculture. We believe it's also a very reliable system for testing and optimizing our gene traits in field tests, in addition to being a very good model system for studying new yield trait genes for oilseeds. We found a 23% increase in seed yield in field tests in our best lines, which is dramatic given the challenges in the sector. We also found that the plants matured 6 days faster, giving a 6-day faster growing cycle, which, as you get into Northern Canada, is a big deal since the growing season is quite short and the growing season limits how far north you can plant some of these crops, which limits the potential acreage.

There were, however, some other consequences with the C3003 gene which are not necessarily beneficial. While the seed yield increased, since the number of seeds per plant went up, the size of the individual seeds was actually smaller. This is something that we need to address. What we're able to do is use modern analytical tools that allow us to study what's going on in these plants at the genomic level across the entire plant system and identify additional genes that are switched on and may be causing these effects.

In the case of the C3003 gene in Camelina, one of the key genes whose activity was affected was the C3004 gene. The C3004 gene is involved in controlling the flow of carbon from leaf tissue into seed tissue. It looks like what is happening in the engineered C3003 plant is that the plant recognizes it has more carbon available and the control system's downstream responds by turning down the flow of carbon to seed. Obviously, we have been developing next-generation versions of the C3003 trait to optimize performance. We not only want to get the right seed size and weight attributes, but also to maximize the yield potential of C3003.

C3004 is a good target for modification for this purpose using genome editing and may complement C3003 further, increasing the yield delivered by this trait. Our genome editing activity on C3004 is already underway. We plan to test second-generation versions of the C3003 trait in Camelina and we plan to test the first generation C3003 trait in canola this spring and based on this schedule, we would anticipate reporting data towards the end of this year.

Olly, back to you.

Thanks, Kristi. Now let's turn to Slide 13. In terms of the development timelines, each of these crops has a different timeline related to the technology used for making gene modifications. Recognizing this, we actually started working with C3003 in all of these crops almost in parallel, with Camelina furthest ahead, trailed by canola and soybean. We expect to field test the second-generation version of the C3003 gene trait in Camelina this spring but are also working on a third generation. It's a bit like software engineering, where we are essentially upgrading the software. We're removing some of the bugs and improving the performance of the actual product.

In terms of canola, for the first-generation C3003, we will be reporting some greenhouse studies very shortly and we should have field test data sometime at the end of the year. We're also working to get the second-generation and third-generation versions of the C3003 gene into canola. We have progressed both the first- and second-generation version of C3003 in soybean as well as rice. Rice was added because rice is 50% of the grain consumed by humans and also has a C3 photosynthesis system. The potential in rice is pretty large and we've been fortunate that we have the in-house capability to engineer rice, so that is moving forward. We're doing the Camelina, canola and rice work with in-house capabilities. The soybean work has been outsourced to a third party and so we're dependent on the partner to meet these timelines. We expect to see some greenhouse data from soybean for both the first- and second-generation versions of C3003 in soybean either at the end of this year or early next.

Let's now turn to Slide 14. We mentioned earlier that we have identified a number of target genes for genome editing to improve crop performance from our T3 Platform. Let me share with you how a number of these were identified. As an example, Slide 14 shows the data from using genetic engineering to increase the activity or expression of our C4003 gene trait, which is a global regulator: the switchgrass. The increased activity of C4003 in switchgrass had some remarkable impacts: an increase of over 40% in photosynthetic carbon capture, along with similar levels of increase in central carbon metabolism and biomass production. Having these high-yielding plants which fix carbon faster in hand, we were able to use high throughput analytics to identify all the other switchgrass genes whose activity or expression was significantly changed. Not surprisingly, it's a lot. 682 genes to be exact. We've been working with a subset focused on 48 genes encoding downstream regulators or transcription factors, whose activity was significantly changed. 32 were increased or up regulated and 16 were down regulated.

The hypothesis is that the regulatory genes turned down in high-yielding plants are potentially negative controllers of plant growth, more or less a braking system. Currently, genome editing is best used for removing or reducing the activity of genes in plants, so negative controllers should be good targets. To test the impact of modifying one of these potential negative controllers, it was technically expedient to do the opposite experiment first and this was to use genetic engineering to increase the activity of one of these potential negative regulatory genes in our switchgrass system. If we're right, then increasing the activity of this gene should reduce plant growth and result in smaller plants.

The picture on the top right of this slide shows that's exactly what happens. Now switchgrass is not a food crop so we've also begun to develop engineered rice using the C4003 yield gene trait. Although it's still early stage, you can see that the engineered rice is behaving similar to what we observed in switchgrass, with a large increase in biomass. Once we have fully developed these rice plants, we will be carrying out the same type of genomic analysis to identify additional rice-specific genome editing targets. So we think our gene editing targets are promising, and we'll conduct further studies in 2017, with the goal of identifying candidate genes for editing for specific crops.

Now we have covered quite a lot of ground tonight, but let's turn to Slide 15 to wrap up our prepared remarks. I believe we're off to a good start in 2017. The Yield10 organization is aligned and sized to achieve our upcoming milestones. Our work with the C3003 yield trait gene produced encouraging results in our 2016 field test in Camelina and paves the way for additional field tests in Camelina and canola. At the same time, we're working to deploy the trait in soybean and rice. Our work in our T3 platform has led to identification of several promising additional gene editing targets, and we will be working to further characterize these targets for impact of seed yields or biomass according to the crop we are studying. Taking this all together, we have a very clear vision for our business, which is to solve the crop yield problem and make a positive contribution to enabling global food security.

So with that, I'd like to turn the call over to Lynne for questions.

Great. Thanks, Olly. We'll now cover 3 questions. The first one goes to Kristi. We've heard you say that the C3003 yield trait gene comes from algae. How did Yield10 come up with this approach?

Algae are ancient photosynthetic organisms that live in water and plants evolved from algae. As the Ag biotech industry has shown, nonplant DNA can provide plants with new functionality. It's part of the collaborations involving Dr. Danny Schnell and our scientists, which was funded by ARPA-e. The team looked at new ways to improve photosynthetic efficiency in plants using algal genes and out of that, C3003 was discovered. We eventually took a global exclusive license to the technology from the University of Massachusetts at Amherst. As our data in Camelina suggests, this novel yield trait gene is allowing increased carbon capture, is impacting photorespiration and is resulting in higher seed yields. We look forward to continuing to work with Danny and to deploying the trade into several crops.

Thanks, Kristi. The second question goes to Olly. In the presentation today, you referred to Roundup Ready and YieldGard as franchised traits and a criteria for evaluating traits to work on at Yield10. Do you think C3003 has the potential to become a franchised trait?

Yes, so Roundup Ready for herbicide tolerance and YieldGard for pest resistance are both based on the successful deployment of bacterial genes that provide crops with new functionality. These traits were broadly applicable to different crops and that's where the franchise concept comes from. We are in early stage with C3003 for sure, but what we are trying to find out is if C3003 affects a common pathway in C3 photosynthetic plants that leads to step-changes in seed yield. We've seen promising results in Camelina, and now we are working to generate results in other oilseed crops and rice. Through our planned field tests, we expect to generate data in canola this year. We think that there's a potential to increase yield across many C3 crops. But in a relatively short time, I think we'll have the data to answer the question about the potential for C3003 to be a franchise trait.

Thank you, Olly. The last questions go to Kristi. Can you tell us more about the C3007 trait as a possible yield trait for oilseed crops?

Yes, we've had an interest in this technology out of the University of Missouri for a while. So earlier this year, we took an exclusive option to license it. It's another good example of an academic group discovering a basic scientific principle that can be used to improve seed yield. In this case, they discovered a previously unknown mechanism which controls fatty acid and oil production in seeds. The way it works is, when it's activated, it turns down the first step in the production pathway. So we think knocking it out through editing will enable the plants to produce more oil in their seeds. As we progress forward, we could potentially then combine the edited C3007 plants with C3003 plants in, for example, canola and make a high-yield, high-oil-content variety. The option is intended to give us some time this year to conduct some experiments with it. So this will be a data-driven decision to license in the technologies.

Great. Thanks, Kristi. We'll now go to Olly for concluding remarks.

I'd like to thank everyone for joining us on the call tonight. Thank you also to our colleagues who have worked so hard to launch Yield10 and are getting us off to a great start in 2017 and thanks as well to all our stockholders. We will work hard to continue earning your support and we look forward to talking with you again on our next call. Good night.

You can now disconnect.

This concludes today's conference. Thank you for your participation. You may disconnect your lines at this time. Have a wonderful evening.