Yes. Thank you very much, Tom. So what I'd like to share with you is the data from our 2-year open-label Phase II study in adolescent Stargardt subjects. This study was, as I mentioned, a 2-year study, 13- enrolled subjects from Taiwan and Australia. What a lot of people don't understand about Stargardt disease is there are over 1,500 known mutations that are associated with the disease. Not all of them are known to be pathogenic. In fact, many are mild to benign. So one of the analyses we did initially was to determine the genetic composition in our cohort. And we actually gave the genetic data to one of the premier preeminent genetics in Stargardt's disease in the world, Dr. Rando Allikmets at Columbia University. He evaluated our genetic data and determined that 11 of 13 subjects in our cohort had severe biallelic mutations, which we predict pathogenicity. And in those two, where there was a moderate allele [ph] in these 2 subjects, in vitro testing actually showed that these were pathogenic alleles. So our entire cohort really has severe pathogenic mutations that were predicted to progress very rapidly through the disease course. An independent assessment of the genetic severity is provided by something called the CAD score. That sounds for combined annotation dependent depletion score. It tells you the degree of severity of a particular genetic variant or genetic mutation. Scores above 20 are predicted to be among the 1% most deleterious. And every single one of our subjects with the section of 3 and 5 had these CAD scores above 20. So we have two independent confirmations on the severity of the genotypes of these kids. And despite the severity of these genotypes, we had five subjects, which represents 42% of the cohort that never developed atrophic lesions. So I should have mentioned that in this study, these adolescent subjects came in with an early form of disease, where they only have a type of lesion, which is autofluorescent. This is known as a questionably decreased autofluorescent lesion. Over time, these autofluorescent lesions convert to atrophic lesions and that's one of the parameters we're looking at. And we see here in 42% of subjects, that conversion never occurred. Another interesting outcome from the genetic data was we found two pairs of siblings that had the exact same identical mutations. This is important because there are companies -- competing companies of ours that are using as a premise for their therapeutic approach that identical mutations predict an identical disease course. So this gives us an opportunity to evaluate that premise and determine whether or not there's any validity to it. Because this is an open label study, one of the metrics we want to look at to see if we're having an effect to improve patients, that essentially well-being is visual acuity. So we looked at visual acuity in subjects prior to enrollment. And we look specifically for subjects who are losing letters in both eyes, that's called bilateral BCVA loss. And we found a subgroup of six subjects within our larger cohort that was losing a mean of 10 letters per year prior to enrollment. The natural history in our study, basically over 2 years predicts that there would be clinically significant vision loss in these subjects during the duration of the study. So we want to keep an eye on that to see how these subjects fare. Another important thing about these data, these sort of pre-enrollment data is the fact that they're losing vision, all these kids are losing vision and some of them significantly, and they don't have atrophic lesions suggests that non-atrophic lesions, these QDF lesions can actually compromise visual acuity. That's very important because all of these kids have foveal-involved lesions, which means they are compromised, their vision will be compromised over time. But the current thinking in the scientific and clinical community is that you have to have atrophic lesions before there starts being some effect on actual visual function, and that seems not to be the case. And finally, regarding the sibling comparisons, we did find that sibling subjects with identical mutations do, in fact, have different levels of BCVA loss, and this data can be found in the appendix of this presentation. If we look at the overview of visual acuity in all subjects that's shown on the left-hand side, over the 2-year study, we see a mean loss of about 2.5 letters per year. That is significant because that essentially shows stabilization. This vision is not really changing in all subjects. But significantly, if we look at those subjects with prior vision loss, that is those subjects that were losing 10 letters per year before coming into the study that's shown on the right-hand side, now they're only losing about 1.9 letters per year. So we've significantly altered the visual acuity progression in these kids, and we've stabilized it. That's very significant. And really, the only reason you could do that is if you're having some effect on lesion growth. So I want to go to that right now. As I mentioned, 5 of 12 subjects never grew in atrophic lesion, but I want to show you sort of anatomically what that looks like. The images you see here on the upper right-hand side are representations of what basically all these subjects look like. This is subject 10 at baseline. But all these projects have these types of autofluorescent lesions that are encroaching the fovea. They're just of different sizes. And we're measuring over time how this autoforestent lesion converts to an atrophic lesion. And as I said before, there are 7 out of the 12 that actually grew these atrophic lesions. And what we found was something very interesting. In every case, except one, the increase of the atrophic area was matched by a decrease in the autofluorescent area in every single subject. So wherever you see an orange bar, that's an increase of atrophy and where you see a blue bar, that's a decrease of the autofluorescent lesion size. The reason that's significant is because the boundary, the perimeter of the lesion is not actually growing, only the atrophic lesion is growing within the autofluorescence. So it suggests that this lesion could potentially burn itself out over time because there's no place else for the lesion to grow. So sort of what these data are telling us is that there are cells that are predestined to die perhaps we cannot save them with our treatment, but we're certainly preserving the margin of cells on the outside that would lead to further lesion growth. They're not growing anymore. So this is a pretty important finding. There was only one subject where we found a lesion that was outside of initially area of QDAF lesion, so just this one subject. And finally, getting back to the genetic mutations, it was subjects 9 and 10 and subject 12 and 13 that had the identical mutations. But if you look at 9 and 10, yes, they have both, lesion goes [ph] somewhat, somewhat different in subject 10 versus 9. But then if you look at 12 and 13, there's absolutely no lesion growth. Yet all these kids have essentially the same -- they have the identical genotypes and very similar disease duration. So these data, again, suggest on a lesion growth metric, identical mutations do not predict an identical disease course. We have one other very important piece of information to pass along, and that is an assessment of how these lesions are actually graded. So currently, we're using the routine methodology that everyone is using. It's basically a autofluorescent camera that takes a picture of the lesion. And then a reader, a physical reader goes in and draws the boundary around the perimeter of that lesion so that the computer can then tell you the area. So two readers have to grade every single image because there has to be an agreement in terms of the lesion size before it can move on into basically being validated. And if those two readers don't agree with a certain variance, a third reader has to come in and sort of be a tiebreaker. So this particular method is subjective to enter an intra-reader bias. It doesn't look at any one specific area and the red is looking all over, and it's very time consuming. So in order to address the shortcomings in this currently used methodology, our reading center has developed a new AI-based method for assessing the size of these lesions. This is a mathematical classification of lesions that uses basically the gray level density in area of healthy tissue, let's say, out here to the area of disease tissue, which would be sort of represented by the density of the optic nerve disc. So it's doing a scan of the gradation in gray levels, and it's just looking at the macula for different areas of gray that would predict either autofluorescence or atrophic lesions. In this case, we're looking at atrophic lesions. So this is important because it removes the reader and the potential subjective bias out of the equation. When our reading center used that methodology to rescan our images at baseline, they found 12 eyes of 8 subjects that had atrophic lesions within the macula at baseline. And this is something the traditional methodology did not pick up. So we asked our reading center to go back and reread all these images to see what's happening with macular lesion growth in these subjects that it was identified in. This is the data that they developed. On the left hand side shows you the growth of the lesions into the macular area over time. It's pretty linear until about month 16, at which time it completely stops and there's no further lesion encroachment into the macula during the subsequent 18 months. On the left hand side is shown basically the same exact data, except here we're looking at the percent change of lesion into the macula over time, where 100% would mean the entire six millimeter zone of the macula is occupied with lesion. And you can see in our subjects, they never get to more than about single digit involvement into the macula. So this is significant and it renders our visual acuity data sensible, because now we understand why we're getting a stabilization of vision, because we're halting lesion growth into the macula. Again, a very significant observation. Finally, the safety data. This is the two year safety data. I want to start by saying that over this two years of observation, there hasn't been one drug related systemic AE [ph] whatsoever in these kids. And this is a testament to the specificity of this drug, the way it was designed by the scientists at Columbia University. Basically, this drug targets just the residues that are in the binding pocket of retinal binding protein 4. And these residues exist nowhere else in biology in terms of their three dimensional orientation. So this drug was supposed to be very specific. And the AE data systemically tell us that basically it is very clean. What we're seeing in terms of jugulated AE's are anticipated ocular events that we want to see because they're telling us we're having the intended biological effect in the retina. And the other important thing about these AE's is they're completely manageable by accommodating to differences in light, because these AE's are driven by light. The first is a form of xanthopsia or chromatopsia, called xantopsia. This is mediated by a cone photoreceptor in your eye, which confers bright light and color vision. So when patients transition suddenly from a dark light to a bright environment, these cone photoreceptors wake up. They want vitamin A immediately. But under our treatment regimen, we're only supplying it, supplying it sort of slowly. So there'll be a period of time in which these cone photoreceptors don't have maximal amount of vitamin A. They will electrically misfire and produce transient hues of color in the visual field. In this case, yellow, that xanthopsia. But all the kids are reporting it as mild. And of course, no one's left study because of this AE. Finally, the other one is delayed dark adaptation. This is the opposite manifestation. So this is mediated when you transition from a bright environment to a very darkened environment. There'll be a delay in the ability to accommodate to dim light. This particular AE is actually a manifestation of the disease process. So patients with Stargardt's disease already have delayed dark adaptation, so they're used to accommodating it. And that's probably why most of them are reporting this pharmacological immediate DD [ph] as mild or transient. And again, no one's left study because of this. And importantly, as I said, these AE's can be mitigated by moderating transitions from bright to dark and vice versa. And this has been very, very helpful for our kids. I can say that in over one year of dosing, in our Phase 3 study, the dropout rate from these AE's is less than 4%. So that is significant. Night vision impairment is a more severe manifestation of the delayed doc adaptation, which the delay is 20 minutes or more. The increasing error score on the FM 100 is a more severe exacerbation of the chromatopsia. You see that in one subject. And the intermittent headaches we think can occur when subjects strain to use their visual acuity while they are experiencing these AE's. So with that now I'll move over to the overview of the trials that Tom discussed. The DRAGON I and DRAGON II Stargardt trials. We're showing you here the overview of those studies. These studies are essentially identical. There's differences in the geography. As Tom mentioned, we have Japan involved vis-à-vis the Sakigake designation. Essentially, the demographics are similar, except for that both studies are done double blind. There is a difference in the randomization. We're doing a 2:1randomization in the DRAGON study and a 1:1 randomization in the DRAGON II. Again, principally because the DRAGON II study has fewer patients. But other than that, every other assessment, safety, efficacy, et cetera, is the same, as is the key inclusion criteria for these subjects. So because of the similarity in these two studies and how they match the Phase 2 study, and because the Phase 2 study is trending quite well, we believe, or we have optimism that we'll have very promising safety and efficacy data in both DRAGON I and DRAGON II studies. Moving forward to geographic atrophy, to show you the trial design in GA, it as well is very, very similar to the Stargardt disease Phase 3 trials. The only difference in the trial design in GA is the indication, of course, geographic atrophy and the higher number of subjects to reflect the higher prevalence of the disease in the population. Otherwise, these studies are essentially identical. So again, we expect, because the GA studies are lagging behind the Stargardt studies, whatever we see in Stargardt, it could be highly predictive of what we see in GA. And a principle reason for that is that we're using the same dose and there's a very high pathological similarity between Stargardt's disease and geographic atrophy in the particular patients we've enrolled. So with that, I'll turn it back over to Hao-Yuan or turn it over to Hao-Yuan for the financial results.