Good day. Thank you for standing by. Welcome to Burning Rock 2021 first quarter earnings conference call. At this time, all participants are in a listen-only mode. After speakers presentation, there will be a question and answer session. To ask a question during the session, you will need to press star one on your telephone. Please be advised that today's conference is being recorded. Before we begin, I'd like to remind you that this conference call contains forward-looking statements within the meaning of Section 21E of the Securities Exchange Act of 1934, as amended, and as defined in U.S. Private Securities Litigation Reform Act of 1995. These forward-looking statements can be identified by terminology such as will, expects, anticipates, future, intends, plans, believes, estimates, target, confident, and similar statements. Statements that are not historical facts, including statements about Burning Rock's beliefs and expectations are forward-looking statements. Such statements are based upon management's current expectations and current market and operating conditions and relate to events that involve known or unknown risk, uncertainties and other factors, all of which are difficult to predict and many of which are beyond Burning Rock's control. Forward-looking statements involve risks, uncertainties, and other factors that could cause actual results to differ materially from those contained in any such statements. Burning Rock does not undertake any obligation to update any forward-looking statement as a result of new information, future events, or otherwise, except as required under applicable law. Now I'd like to hand the conference over to the management team of Burning Rock. Thank you. Please go ahead. Thank you. Welcome to Burning Rock earnings call. I'm Yusheng Han, the CEO and founder of Burning Rock. Today we also have our COO, Shannon Chuai, our CTO, Joe Zhang, and our CFO, Leo Li, in this call. Burning Rock is a Chinese molecular diagnostics for precision oncology. There are two parts of our business. The first one is early detection using liquid biopsy for pan-cancer, and the second is for cell col lection and MRD. If we will turn to page four. Today, we're going to recap the recent progress for both early detection and therapy selection. For early detection, we are very excited to launch the multi-omic 22 cancer test, which is called PRESCIENT. Second thing is the PREDICT trial for nine cancer test is going well, smoothly. Our COO, Shannon Chuai, will talk about these two trials in detail. In the meantime, the preparation of commercialization of the six cancer path is ongoing. We're continuously building our commercial and operating team and optimizing the SOPs. Nothing significantly important to report for the fifth cancer so far. If you have any question, welcome to ask that during the Q&A session. For the therapy selection, we have great news that finally the result of our liquid biopsy card of SEQC2 has published in Nature Biotechnology, which proves that Burning Rock's oncology is at the top-tier level in the world. Our CTO, Joe, will talk about that in detail. After that, our CFO, Leo, will talk about our financial numbers. Let's turn to Shannon first about the early detection part. Shannon. All right. Thanks, Yusheng. If we go to page six, this is to recap the product development roadmaps for our early detection programs. We started with the proof of concept lung cancer, and the study and the methodology has been actually most recently accepted for publication and is pending publication right now. We moved on to a three cancer test, which we presented the data last year in January in the AACR special conference on liquid biopsy. We were able to achieve 95% specificity and 81% sensitivity. Most recently, I think a lot of you are familiar with our six cancer test results that we released last year in November at the ESMO Asia. The six cancer test includes all common lung cancer, colorectal cancer, liver, ovarian, pancreatic, and esophageal. The data showed that we were able to maintain our 81% sensitivity while improving the specificity, including the specificity to about 98%. We also were able to achieve a reasonably good accuracy for TOO analysis, tissue of origin analysis, from this [SIS], about 81% accuracy from the six cancer test in the results we released last year. For the six cancer test, after the THUNDER study, which was the case-control study to validate the specificity and sensitivity of the product, we also were planning to move on to a prospective interventional study for asymptomatic population. That study is currently under planning, and I'm going to show you an overview in later pages. Today, we wanted to focus on the most recent, very exciting progresses that we are making on the nine cancer test and looking forward to the 22 cancer test. As Yusheng has mentioned, for the nine cancer test, our current status is that the PREDICT study that we started earlier is going very smoothly. The progress is as expected. For the 22 cancer test, first of all, the 22 cancer will eventually cover about 88% of China's cancer incidence altogether. For that 22 cancer test, we have just kicked off a large clinical development study a few weeks ago in May 2021, and it's called PRESCIENT. In the later pages, I'm going to tell you a little bit about the design and timeline for both the PREDICT study and the PRESCIENT study. If we go to page seven, this is sort of an overview of the clinical program that we are looking at for our early detection program. For each product or each version or each generation of our products, there are roughly four phases for the product development or clinical development. The first is the assay development, in which we do the panel design, the marker selection, and also the assay chemistry finalization. We do the analytical validation to validate the performance analytically, including using reference materials or clinical samples, to validate the performance specifications. We move on to the case-control study. For this one, you can sort of think of the CCGA study from Grail. It's similar to what we are laying out here as a case-control study. In these studies, they are real clinical cases and controls or healthy controls, and in these studies, we will be able to validate the sensitivity, specificity, and TOO accuracy, the key statistical performance features for the early detection products. After that, eventually, we want to move on to the asymptomatic population, in which we will be able to validate again the sensitivity, specificity, TOO accuracy in these eventually intend to use population. For this one, you can sort of compare that to the PATHFINDER trial from Grail as well, in which it tests in Galleri on the asymptomatic population in a prospectively recruited cohort. For our three cancer tests, after we finished the assay development and analytical validation, we were able to move on to the clinical development so we moved forward to the six cancer test. For the six cancer tests, we have so far completed the assay development and analytical validation, as well as the case-control study, which we mentioned in the last page as the THUNDER study. The THUNDER study was able to show in a training and a pre-specified validation cohort the 81% of sensitivity and 98% of specificity. Again, a prospective interventional study on the asymptomatic population for the six cancer test is currently under planning. We hope that we will be able to disclose more details about that study once it's finalized and released or kicked off in the near future. Again, in the meanwhile, in parallel, we are also moving on to cover more cancer types, of course. For that nine cancer test, we have already finished the assay development, which means that we have finalized the chemistry and also the marker selection, the panel design, etc. The analytical validation for that product is currently ongoing. In the meanwhile, we were able to start the enrollment case-control, the PREDICT study in parallel to shorten the development time overall. The PREDICT study, if you might recall, actually contains two phases. In phase II, it does contain a factor of testing or validation among a small asymptomatic cohort or healthy controls. That's why over here we are sort of expanding that a little bit beyond the case-control study, even though it's not fully powered to test on the healthy or asymptomatic population. In the later pages, I will be able to give more details of how the two phases of this study will work out. For the 22 cancers that we are actually working on developing this next generation of the product in the meanwhile, and it's currently under the early development stage. Because we collected a lot of information, also preliminary results from the previous versions of the product, we were able to finalize the design of that PRESCIENT study, as the case-control study that we are planning for the 22 cancer tests. That's why we have kicked off enrollment of the study, we will be able to recruit clinical samples for future testing for validation for these 22 cancer tests in parallel with the analytic development efforts. If we move on to page eight, this outlines the study design of the PREDICT study. Again, it covers nine cancer types, which are listed out on the upper right here. Overall, this study contains more than 14,000 participants, about 55% of them coming from cancer, about 10%, I think 10% coming from benign diseases, and the rest from healthy controls. One thing we wanted to point out is that more than 75%, at least 75% of the cancer participants will be from stage one to three. Most of the cases we will focus primarily on the early-stage patients who wanted to know or be able to assess our sensitivity among the early-stage patients, because that's what really matters. In terms of the study design, as I mentioned, there will be two phases. The phase I will be an open-label design, which means that for phase I, we will divide the phase I samples into the pre-specified training and testing sets. Within the training, we will be able to customize or tune our models and cutoffs, then to be able to record the results or performances on the validation set within the phase I cohort. After that, the model, basically at the end, the model will be locked, and we move on to phase II central processing. In phase II, we will have a totally independent set of data to test or to validate the performance of the locked model or methods from phase I and to be able to have a rather accurate assessment of the model performance for the nine cancer tests. One thing we also wanted to point out is that for PREDICT study participants, we are planning for a 12-month follow-up. It's actually on the healthy controls, which will have the positive testing results so that we will be able to have a positive predictive value assessment among these healthy control cohorts over the follow-up. On the next page, we listed out the objectives and timeline for PREDICT. Of course, the primary objective will be to train and validate the sensitivity, specificity, and TOO analysis of our cfDNA methylation-based model for these nine types of cancers. Then for the secondary objectives, we of course wanted to learn about the performance among different types of cancers and also among different stages of cancer. Also we wanted to know whether other biomarkers, including protein biomarkers that we are processing in parallel in these PREDICT samples, whether they will help in any way, which we do expect they might help in at least some of the cancer types, how do they help, and how do we combine them with the methylation markers? That's something we will explore from the PREDICT data. Last but not least, we will have a chance to evaluate the PPV in this cohort as well after the 12-month follow-up period. In terms of the timeline, we expect the phase I enrollment to complete by 2022, and then we will be able to have a readout of the phase I data by the end of 2022. By the end of 2023, we will have the readout for phase II data. By 2024, we will be able to finish the follow-up and have the complete data set for the PREDICT study. On page 10, we wanted to briefly mention the kind of attention that the PREDICT study has attracted among the Chinese oncology community. This is the picture of the Principal Investigator, Dr. Jian Zhang, when he presented as a keynote speech on the National Oncology Conference, Standardized Diagnosis and Treatment Conference that was held a couple of weeks ago in Beijing. The PREDICT study design, and also the news was announced during that conference by Dr. Jian Zhang, and it has attracted a lot of interest and attention from the community so far. Moving on to the next page 11 lays out the study design for the PRESCIENT study. Compared to the PREDICT study, PRESCIENT study actually has two dimensions of expansion. The first is obviously extending from the nine cancer types to the 22 cancer types, which are listed on the upper right again. It has similar design, but now divided into two phases. However, it has another dimension of expansion, is that beyond methylation and protein markers, we will profile other omics of biomarkers in the PRESCIENT samples as well. We won't be able to disclose too much detail on exactly how we test there, but the exploration from the PRESCIENT study will be focused not just on the cancer type expansion, but also on the omics combination. On page 12, again, the objectives for the PRESCIENT study is we will be able to validate the methylation plus protein markers among the 22 cancer types, and then we will be able to assess the performance among different stages and different types of the cancer. Very importantly, we will be able to evaluate the potential combination, including methylation, protein, and other genetic, epigenetic biomarkers on the PRESCIENT study. In terms of the timeline, we expect to complete enrollment for PRESCIENT by 2023. For the PRESCIENT study, we will divide it again into pre-specified training and validation sets. By the end of 2023, we expect to be able to lock the model for the 22 cancer types from the training set. In another year, we will have the study read out for the validation set. On page 13, this is again to introduce to you the principal investigators for PREDICT and PRESCIENT. We are very proud that we have successfully attracted the top-tier oncologists in China to lead the PREDICT and PRESCIENT trials. On top, Dr. Jian Zhang is the leading PI for the PREDICT trial. He is a fellow of the Chinese Academy of Sciences and also the president of the Shanghai Zhongshan Hospital. For those of you who are not familiar with the Chinese hospitals, Shanghai Zhongshan Hospital is one of China's largest comprehensive academic hospitals, and it performs more than 100,000 operations each year and serves about 169,000 inpatients per year. In 2019, it was ranked top five among China's general hospitals. On the bottom, Dr. Jie He, he is the leading PI of our PRESCIENT study, and he is also a fellow of the Chinese Academy of Sciences and also President of the hospital called Cancer Hospital, Chinese Academy of Medical Sciences. This hospital is arguably the top cancer specialist hospital in China. We are very proud that these top oncologists are leading our PREDICT and PRESCIENT studies. It actually reflects the sharply growing interest and acknowledgment from the oncologist community in China for cancer early detection, especially in the past year or so. It did attract a lot of attention in this field. We think high quality of cohort trend data will ensure timely recruitment and of course, successful completion of the study, which will serve as a key in establishing a leadership position and maintaining our leadership position in the development of our cancer early detection products. We are excited to share with you these PIs and their level among the oncologist community in China. With that, I think I'll pass to our CTO, Dr. Joe Zhang, to tell you more about our recent results released from the xQCT study. Joe. Thanks, Shannon. I'm going to cover a little bit about therapy selection part. For the slide 15, which highlights what's the strength of Burning Rock in terms of the therapy selection business. With regards to the superior product and along the NMP approval process for the different IVD kit in the pipeline, but also the commercial penetration. Today I'm going to focus on the first bullet point, which is the superior products, which one of the evidence shown is a paper published last month in Nature Biotechnology. This is in the slide 16. This is basically a community effort, consortium led by FDA and which they call MAQC consortium and focusing on the quality control of the sequencing business. What you can see here, the paper has been published. We participated both the liquid biopsy part as well as the pan-cancer, which is tissue-based. The liquid biopsy study has been published last month. Page 17 basically highlighted what's the participating assay as well as study design. There are five different company participate. They are all kit vendor, which means all being capable to produce the liquid biopsy panel, and as well as sell the kit format and let the customer to use them. Burning Rock is the one and only Chinese vendor who participate this study, and each vendor will distribute their kit to different labs. The lab will receive the FDA distributed reference material and perform the assay based on the vendor's kit guidance, and trying to generate the library and the sequence, and also using the kit vendor's bioinformatics pipeline to perform analysis. All the result will be submitted to FDA. For the Principal Investigator of this study, look at the data and based on the peer project, also led by SEQC effort and trying to know which of the positive, what's the ground truth for this data and trying to evaluate sensitivity and specificity, positive rate as well as evaluate the reproducibility within lab also across labs. Burning Rock using the lung plus [audio distortion] panel, which we currently call OncoCompass Target Panel for the liquid biopsy study, and it cover 168 genes listed in the top table here. For the next slide 18, basically highlights the several key performance comparison across different kind of panel and product. Burning Rock has been boxed in the green color, and as you can see at the top part, basically the fragment depth, which means based on the sequencing, how many unique fragment we can collect at a recovery recovered from 25 nanogram reference material. As you can see here, the data showing the higher the better, which means with limited amount of DNA input, how many real fragment you can collect from them out. The bottom panel compare the coverage uniformity, which means across this panel, what's the average coverage and how uniform this panel will be. As you can see here, Burning Rock also showing good performance compared to other vendors, such that all the coverage is close to or similar to each other. For the next slide, in slide 19, which compare four different hybridization capture panels and look at different sensitivity to say what's the calling probability for different kind of variant allele frequency bin. Since each different panel has different kind of true positives, since the panel are different. For the PI, they basically compare based on the ground truth, and then look at the different kind of variant allele frequency bin and whether this panel can be able to call it, and each column represent one sample, one replicate in one site, in one lab. Burning Rock is on the rightmost one. Basically, if it's been colored, which means this variant have been called, if it's blank, which means this variant's been missed, as we call negative here. As you can see here, basically, almost all the color being filled for Burning Rock, even if it's 0.1% to 0.2% variant allele frequency, the calling percentage is higher than some other panels. This is just to give us a lot of confidence showing our panel as well as our bioinformatics pipeline, showing pretty top performance compared to the other vendors, especially this kind of classic molecular biology vendors. For the reproducibility study and next slide 20, which compare across different kind of panel, look at how reproducibility it is across lab or within lab, since each lab process same sample four times. Also, there's a multiple labs performance. As you can see here, the reproducibility also Burning Rock data showing pretty good performance compared to other vendor's kit. For the slide 21, it just briefly compare different kind of input of DNA amount and compare the sensitivity. As we know, like the more DNA put in there then the higher sensitivity it is, and each panel showing this kind of trend. For the green line, basically representing Burning Rock's assay. For both sensitivity as well as reproducibility, showing the Burning Rock's panel a pretty good performance and very stable on that. Also, in variant allele frequency of 0.1%- 0.5% showing high performance. For the slide 22, very briefly, they just compare analytical accuracy based on the sensitivity and precision curve. This is based on 25 ng of reference material input and compare four different panels and the precision representing the positive predictive value, PPV, and the sensitivity here means recall, which means how sensitive, how many the true positive rate it is. The closer to the top right corner of this graph means the better performance. You can see here, the overall analytical accuracy, and especially Burning Rock showing the best compared then to other panels. All this information just give us-- From the paper published, and this is basically a relatively fair comparison across different panel and using same reference material, it gave us a lot of confidence showing that our product in the therapy selection zone, showing the top performance, not only in China, but also when compared to the world, a lot of famous kit standards, and we've been doing pretty good on that. Here, basically, I just conclude the therapy selection part highlight, and I'll hand over to Leo talking about financials. Thanks. Thank you, Joe. Our financials are shown on page 25 of our presentation. For this call, we'll focus mostly on our top-line numbers. First, we recap that all our revenues are generated from our therapy selection business, so there's no contribution from our pathogen detection yet, which is still under R&D and clinical development. In the first quarter, we are happy with the year-over-year growth that we've been able to achieve. We grew our revenues by 58% on a year-over-year basis. We grew our gross profits by 72% on a year-over-year basis. By channel, our central lab revenue grew 62%. Our in-hospital revenues grew 70%. In our observation of some anecdotal industry data points, this is above industry growth rate, indicating that we've been able to gain some share in this period. Within the first quarter, talking about the monthly and the sequential trends, January was impacted by COVID resurgence in Beijing, Shanghai, and a few other key cities in China. That did have a negative impact on testing volumes for some of our key customers. February was a quiet month due to Chinese New Year, and March was an okay month. Because of the negative drag from January and February, the sequential growth rate was negative for the first quarter at -14% Q1Q. Now looking at the rest of the year, we have a guidance of RMB 610 million for the 2021 full year, which is unchanged from our previous earnings release. We have not hit the monthly run rate yet to achieve that full-year target, so there is certainly more work that we need to do. In terms of what we're doing in terms of driving additional NGS penetration, we are doing, number one, executing our in-hospital strategy, putting our tests available at more hospitals, which we think is important for building an NGS penetration because this is the most typical formats of testing in China. Second will be the continued execution of our multi-year NMPA registration pipeline process, which will be key in terms of competitive differentiation. We remain focused on these initiatives for driving the long-term success of our therapy selection business. With that, we conclude our prepared remarks. We open up for questions please. Thank you. Ladies and gentlemen, if you wish to ask a question now, please press star one on your telephone and wait for your name to be announced. If you wish to cancel your request, please press the pound or hash key. Your first question comes from the line of Doug Schenkel from Cowen. Please go ahead. Hi, good day. Thank you for taking my questions. Starting on the topic of asymptomatic screening, I appreciate all the detail you provided today. Regarding the six cancer, nine cancer, and 22 cancer asymptomatic screening programs, three things that are pretty important remain unclear to me. One, do you believe studies like THUNDER, PREDICT, and PRESCIENT will be sufficient to allow for product launch from a regulatory standpoint and reimbursement? Second, if not, how big a study will be required to allow for regulatory approval and reimbursement? Third, what is the acceptable target from this perspective when it comes to sensitivity and specificity? I want to go back to these questions because you referenced CCGA and PATHFINDER in your prepared remarks as good precedents or at least comparable studies. Neither of these studies are sufficient in the United States to support FDA approval or CMS reimbursement. Most companies, in fact, that are based in the West have indicated FDA approval and reimbursement would require large, randomized prospective studies, and by large, I mean over 100,000 patients. I understand your programs are not targeted at the U.S. or Western markets. They're targeted at China. It just would be helpful to understand, again, what the answers are to my three questions as it relates to asymptomatic screening, given the market is different. Okay. Hi, Doug. Thanks for your question. I'll take your question. First of all, a very straightforward answer for your first question. No, we don't think the PREDICT or PRESCIENT will be enough for testing the asymptomatic population because they are apparently not powered enough to have a precise enough assessment on the sensitivity, especially the sensitivity for the asymptomatic population. Also, the recruitment strategy actually naturally conflicts with [post-factum] asymptomatic validation study, because in this study, the participants, the control arm, actually, we define them as the healthy, quote-unquote, because they need to go through a health checkup or take a blood examination at the recruiter point. Actually, for a purely asymptomatic study, they don't necessarily have to go through that. It's just symptom-free and relying on whatever health checkups habits they're going through in their real life. PREDICT and PRESCIENT are not designed to give us answers for the asymptomatic population performances. They are, on the other hand, powered or designed to give us answers for the case control cohorts, which will help us to design the future asymptomatic post-factum or even interventional studies. For the six cancer test, the study that we just mentioned that's under planning, that one will be designed and powered to give us a definite answer for the asymptomatic population for the six cancer tests. That one we do think, or we are designing it for the purpose, potentially down the road, for registration. Of course, the registration pathway for early detection setup in China is not crystal clear or anywhere near crystal clear at this point. We're having a conversation with an NMPA, so we don't have a 100% answer that it's going to be enough, but at least it's powered to answer the question about, on an individual level, whether the benefit would be enough to pass the product through the registration, at least as a pay out-of-pocket product. However, for reimbursement, I agree with you that it's a completely different story, because for reimbursement, you not only have to establish an individual level benefit, you have to establish a population level benefit. In order to do that, there are a lot more you need to evaluate beyond sensitivity, specificity on that individual level for different cancer types, et cetera. You also have to establish benefits in terms of health economics, et cetera. In China, I think we also talked about this a few times before. In China, the market is an out-of-pocket market. We do believe that in China it's possible to have the registration and reimbursement. They're sort of two things, and we were able to have the registration by just showing the individual level of benefit. Of course, again, this is preliminary thoughts and things might change, and we might have new information as time goes on. Thanks so much for that, Shannon. That was really helpful. I think my other topics are probably more for Leo. Leo, just in terms of the quarter and specific to the central lab, volume dropped relative to Q4. Maybe that wouldn't have been shocking regardless of how January and March went, given Lunar New Year was in the quarter and wasn't in Q4. That being said, volume was also lower than Q3. Additionally, revenue dropped back to levels not seen since the second quarter of last year in this channel, and that was largely a function of both the volume dynamics and maybe just as, if not more importantly, ASPs dropping a bit. On the topic of ASPs, because it sounds like you don't think there's any competitive pressure on volume, it sounds like you think that's just the market. When it comes to ASPs, were there market pricing pressures in the quarter, or was that a function of product mix? Building off of that, how are you thinking about volume and pricing in the central lab channel over the balance of the year? Essentially, what's built into guidance? Yeah. For the central lab channels, we did see ASP fluctuations quarter-over-quarter, and that was more to do with product mix. We have not made any pricing changes for that channel during the first quarter. Pretty much driven by product mix shifts and some seasonalities. That was for the first quarter. For the remainder of the year, for the central lab, we think there are structural challenges that we do need to work through. As we mentioned earlier, if we look at building NGS penetration, we are putting efforts into the in-hospital channel. We think this will be very important for the future growth of NGS penetration. That's the most typical format of testing. The central lab channel is a more fragmented channel with lower entry barriers. Whereas the in-hospital channel is a more institutionalized channel where our product strength will be able to compete better, we believe, versus other non-products and some aggressive commercial factors in the central lab channel. We think, looking for the rest of the year, in-hospital channel will be important in terms of driving growth. For the central lab channel, we have been building our sales team and headcounts. We have seen sales and marketing expenses increasing over time, and that's mostly due to headcount increases. We are putting more manpower on the ground, speaking to more physicians to build up this channel. We think that this will take time. Leo, also keeping in mind that in-hospital revenue dropped below levels generated in both the third and fourth quarter of last year, would you attribute the performance in Q1 largely to normal seasonality, and thus you feel pretty confident about a more pronounced ramp in the in-hospital channel versus the central lab over the coming quarters? The first Q drop of the in-hospital channel was expected, as we were expecting Chinese New Year, and typically there was not a lot of ordering during that month. The January COVID resurgence was unexpected, so that did hit us. Without that, we would have been better. Looking at volume trends, we were happy about the in-hospital volumes for the month of March, which grew double digits. We are keeping a watch on the second quarter as we have not closed the second quarter yet. Okay. That's a perfect segue to my last question, which again, is on guidance. Obviously, you knew Lunar New Year was in Q1, as it always is. It sounds like what surprised you was the COVID impact on January and probably more the central lab performance in March versus the in-hospital performance in March. What is it that you saw coming out of the quarter and over the early part of Q2 which made you confident in reaffirming guidance, in spite of the fact that it does seem like there were more headwinds in the first quarter than you might have anticipated? Yeah. As we were building the guidance, we were expecting a second half heavy versus first half light of the year, and it played out that way. We did leave some buffer for COVID fluctuations, and we did get hit by that in January. Not a lot of surprises in terms of looking at our guidance. Looking forwards for the rest of the year, we do need to ramp up our monthly revenue run rates, which we haven't hit the run rate yet to be able to achieve that full year guidance. We need to go back and work hard, and we look forward to update you guys in the next earnings call. Okay. Thanks to all of you. I appreciate all the details. Thanks, Doug. Thank you. Our next question comes from Yi Feng Cheng from Bank of America. Please ask your question. Thank you for taking my question. I'm Yi Feng from Bank of America, and I'll ask two questions on behalf of our analyst community. Firstly, can we have some update information about our six cancer test? Is there any changes for the timetable guidance? I mean, for early detection or commercialization? Yes, the approval and the, like, our discussion with NMPA, is there any updates? Last time we talked about that, whether we're doing the EAP and also the prospective consumer trial. In terms of the commercialization timeline, we are building our team for commercialization and operation. We think that the key point for the early detection is for the consumer trials. We recently are recruiting a team from consumer industry and also the internet industry. We believe that we have already found the right way to commercialize that. At the same time, that's also the new thing in the market. How to do that effectively this time and when trying to optimize the whole process. So far, we're seeing that everything is on the right track. As we said, the commercialization will start early next year. In terms of the clinical trial, will Shannon talk about that? Right. I don't think we ever gave any guidance on registration because we honestly are having an ongoing conversation with NMPA. As I said, there's nothing sure at this point. Also, we are, of course, for the whole field, the early detection product, the registration pathway for that is not clear yet. I think it's a dynamic process or discussion with the NMPA. We don't have a specific timetable that we could give out yet. As Yusheng said, for all the progresses or efforts on getting everything is going as what we planned or expected, including the study that we are planning for among the asymptomatic population. That's still ongoing as expected and also as what we have released last time. Thank you. Very clear. The second question is about the participants in our PREDICT and the PRESCIENT study. Do you think that for the PREDICT study, there are around 14,000 participants, while for the PRESCIENT, there are around 12,000. Can you help us to illustrate more about how this number has been confirmed and why there's a difference, and why the PRESCIENT has fewer number of participants? Thank you. Thanks. It's a very good question. Thank you for noticing that. For PREDICT, because we have quite rich preliminary results for those nine cancer, at least six out of the nine cancers, and there's still a little bit data on the other three cancer types. We were able to design the study, and planning for the sample size, a stage-specific estimate for the sensitivity and PO accuracy. That's why for PREDICT, even with fewer cancer types, we are planning for larger sample size, because the sample size was calculated so that on each stage, each cancer type, each stage, we will have a precise enough estimate for the sensitivity. When we are planning for the PRESCIENT study, because it's longer down the road, and also because apparently we don't have as much preliminary data or knowledge about the other 13 cancer types as for these nine. That's why when we designed the PRESCIENT study, it's more on a cancer-specific estimate for the sensitivity instead of cancer and stage-specific estimate. For PRESCIENT, for each cancer type, we actually have a smaller sample size. Even among PREDICT and PRESCIENT, each cancer type actually has different sample size planned in terms of or depending on our estimated sensitivity that we will be able to reach or achieve. Especially for the PRESCIENT study, we actually have fewer samples planned for the nine cancer types that were already covered in PREDICT, and we allocated more samples for the other 13 cancer types. All in all, the design, the sample size calculation was based on different objectives. That's why you see different sample sizes for each cancer type. Okay. Thank you. Very clear. That's all my questions. Thank you. Our next question comes from Sean Wu from Morgan Stanley. Please ask your question. Okay. Thank you for taking my question. I actually am also quite curious about the full number you use for the study. You have exactly 14,026 for PREDICT and 11,879. How did you come out with those kind of numbers? That is for my curiosity. For one study, you are doing nine cancer types and the other 22. I mean, in some sense, why don't you just combine them together? Those two studies supposedly, clearly are designed for different purposes. For nine ones, should we expect that you will get a more conclusive result from the nine ones instead of from the two cancer types? Also, you're competitive, some of them have come out of this. In fact, they were designed the product for one type of cancer detection, like liver cancer or again, prostate cancer. What's the difference, the advantage of multi is versus like single one? For liver cancer, clearly, if people drink a lot and they have hepatitis, this one type of medicine is also very important for them. Finally, I think you have signed up some very good oncologists at the public hospital, oncology hospitals to do your clinical trials. How trials. How have you been so successful with getting so many key PIs like [Beijing] and be a part of your program? Thank you very much. First of all, for the study sample size, as I just previously explained, PREDICT and PRESCIENT are designed based on different objectives. For PREDICT, we are aiming to estimate stage and cancer type-specific sensitivity. For each cancer type, we allocated more sample size. For PRESCIENT, because we didn't have as much previous knowledge to support our stage and cancer type-specific design, that's why we actually will only assess the cancer type or cancer-specific sensitivity. Roughly, that's why for PRESCIENT, we have a little bit fewer sample size planned for the PRESCIENT study. Also for your question, why don't we just combine the two? They are for two different products, because for the PREDICT study, we're using our nine cancer types product, for the PRESCIENT study, we will use our next generation of 22 cancer types product. It's not an add-on relationship between the two products. Actually, the chemistry and also the marker selection and the model will all change, and hopefully will all improve between the two generations. That's why for the new generation, we will have to retest its performance to see whether it holds or even improves on the existing nine cancer types that were already tested in PREDICT. For your last question about the principal investigators, thank you for the comment. We are also very proud, and as I said, it reflects actually the strong interest and attention that early detection has drawn among the oncologist community. I'd say about three years ago, none of them really believed in the new technology, it's getting close to real application or to make real contribution to cancer early detection. Nowadays, a lot of them believe in that, and they think the new technology, especially epigenetic-based biomarkers plus machine learning and next-generation sequencing, finally it's bringing into reality that early detection can be realized in a large scale, especially on a multi-cancer application. That's for one. For two, there are actually very few hospitals in China that have the capability and capacity to be able to host studies like PREDICT or PRESCIENT or lead studies like these. It actually requires a lot of organization power, and also the impact from the principal investigators. That's why actually only the top clinicians or oncologists in China have the capability and impact to be able to operate these really large cohort studies. I think that's also why they have the passion and the ambition as well to fulfill these very innovative studies. Does that answer your question? All right. Thank you. Ladies and gentlemen, we have reached the end of the question and answer session. With that, we conclude our conference for today.