Burning Rock Biotech Ltd (BNR) 2021 Q1 法說會逐字稿

Good day, and thank you for standing by. Welcome to Burning Rock's 2021 First Quarter Earnings conference call. (Operator Instructions) 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 the 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 risks, 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.

And 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's earnings call. I'm Yusheng Han, the CEO and Founder of Burning Rock. And today, we also have our COO, Shannon Chuai; our CTO, Zhihong Zhang; and our CFO, Leo Li, in this call.

So Burning Rock is a China’s molecular diagnostic leader for precision oncology. There are 2 parts of our business. The first one is early detection using liquid biopsy for pan cancer. And the second is for Therapy Selection and MRD. So we'll turn to Page 4. So today, we're going to recap the recent progress for both Early Detection and Therapy Selection. So for Early Detection, we are very excited to launch the multi-omics 22-cancer test, which is called PRESCIENT. And the second thing, the PREDICT trial for 9-cancer test is going well smoothly. And our COO, Shannon Chuai, will talk about these 2 trials in detail. And in the meantime, the preparation of commercialization of the 6-cancer test is ongoing. And we are continuously building our commercial and operational team and optimizing the SOPs.

Nothing significantly important to report for the 6-cancer so far. But if you have any question, welcome to ask at the Q&A second session. And for the Therapy Selection, we have great news that finally, the result of liquid biopsy part of SEQC2 is published in Nature Biotechnology, which proved that Burning Rock's quality is the top-tier level in the world. And our CTO, Joe, will talk about that in detail. And after that, our CFO, Leo, will talk about the financial numbers. So let's turn to Shannon first about the Early Detection part. Shannon?

All right. Thanks, Yusheng Han. So if we go to Page 6, this is to recap the product development road map for our Early Detection program. So we started with the proof-of-concept on lung cancer. And the study and the methodology has been actually most recently accepted for publication and a manuscript is pending publication right now. And then we moved on to 3-cancer test, which we presented the data last year in January in the AACR Special Conference on Liquid Biopsy. We were able to achieve a 95% specificity and 81% sensitivity.

And then most recently, I think a lot of you are familiar with our 6-cancer test results that we released last year in November on the ESMO Asia. The 6-cancer test includes -- covers lung cancer, colorectal cancer, liver, ovarian, pancreatic and esophageal. And the data showed that we were able to maintain our 81% sensitivity while improve the specificity -- improving the specificity to 80 -- about 98%. And we also were able to achieve a reasonably good accuracy for TOO analysis, tissue-of-origin analysis, from this -- as high as about 81% accuracy from the 6-cancer test in the results we released last year.

And then for the 6-cancer test, after the THUNDER study, which was the case-control study to validate the specificity and sensitivity of the product, we also are planning to move on to a prospective interventional study for asymptomatic population. So that study is currently under planning, and I'm going to share an overview in later pages. And today, we we wanted to focus on the most recent very exciting progresses that we are making on the 9-cancer test and looking forward on to the 22-cancer test.

As Yusheng Han has mentioned, for 9-cancer test, our current status is that the PREDICT study that we started earlier is going very smoothly and the progress is as expected. And also for the 22-cancer test, first of all, the 22-cancer will eventually cover about 88% % of China's cancer incidence altogether. And then for this 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. So in the later pages, I'm going to tell you about -- a little bit about the design and time line for both the PREDICT study and the PRESCIENT study.

So if we go to Page 7, this is sort of an overview of the clinical programs that we are looking at for our Early Detection program. So for each product or each version or each generation of our products, there are 4 -- roughly 4 phases for the product development. The first is the assay development in which we do the panel design, the marker selection and also the assay chemistry finalization. And then we do the analytical validation to validate the performance analytically, including using reference materials or clinical samples to validate the performance specifications.

And then we move on to the case-control study. And for this one, you can sort of think of the CCGA studies from GRAIL. It's similar to what we are laying out here as the case-control study. In these studies, they are real clinical cases and controls or healthy controls. And in these studies, we'll be able to validate the sensitivity, specificity and TOO accuracy, the key statistical performance features for Early Detection products.

And then 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 these eventually intended to use -- intend-to-use population. And for this one, you can sort of compare that to the PATHFINDER trial from GRAIL as well in which is testing Galleri on the asymptomatic population in a prospectively recruited cohort.

So for our 3-cancer test, we -- after we've finished the assay development and analytical validation, we did move on to the clinical development. So we moved forward to the 6-cancer test. And for the 6-cancer test, we have so far completed the assay development and analytical validation as well as the case-control study, which was what we mentioned in the last page of the THUNDER study. The THUNDER study, we're able to show in a training and a pre-specified validation cohort, the 81% of sensitivity and 98% of specificity.

And then again, the prospective interventional study on the asymptomatic population for the 6-cancer test is currently under planning, and we hope that we will be able to disclose more details about that study once it's is finalized and released or kicked off in the near future.

And then we -- in the meanwhile, in parallel, we are also moving on to more cancer -- to cover more cancer types, of course. So for that 9-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, et cetera. And the analytical validation for that product is currently ongoing.

And in the meanwhile, we were able to start the enrollment on the case control, the PREDICT study in parallel to sort of to shorten the development time overall. And the PREDICT study, if you might recall, it actually contains 2 phases. And in Phase II, it does contain a factor of testing or validating among a small asymptomatic cohort or healthy controls. So that's why over here, we are sort of standing that a little bit beyond the case-control study, even though it's not fully powered to test on the healthy or asymptomatic population.

So in the later pages, I will be able to give you more details on how the 2 phases of this study will work out. And then for the 22-cancer test, we are actually working on developing the next-generation of the product in the meanwhile. And is currently under the assay development stage. However, because we collected a lot of information or 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 test. So that's why we have kicked off the enrollment of the study. So we will be able to recruit samples -- clinical samples for future testing for -- or validation for this 22-cancer test in the -- in parallel with the product development efforts.

So if we move on to Page 8, this is -- this outlines the study design of the PREDICT study. Again, it covers 9-cancer types, which are listed out on the upper right here. And 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. And 1 thing we wanted to point out is that 70 -- more than 75% -- at least 75% of the cancer participants will be from stage 1 to 3. So 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.

And then in terms of the study design, as I mentioned, there will be 2 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 prespecified training and testing steps. And within the training, we will be able to customize or tune or model and cut offs and then to be able to report the results or performances on the validation set within the Phase I cohort. And then after that, the model, those as the end model will be locked, and then we move on to Phase II sample processing. So in Phase II, we will have a total independent set of data to test or to validate the performance of the lock model or method from Phase I and to be able to have a rather accurate assessment of the model performance for the 9-cancer test.

And then 1 thing we also wanted to point out is that for PREDICT study participants, we are planning for a 12-month follow-up, especially on the healthy controls, which will have a 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.

So on the next page, we listed out the objectives and time line for PREDICT. So of course, the primary objective will be to test the -- to try and validate the sensitivity, specificity and TOO analysis of our cfDNA methylation-based model for these 9 cancer -- 9 types of cancers. And 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 cancers. And 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 way, which we do expect they might help in at least some of the cancer types and how do they help and how do we combine them with the methylation markers, that's something we will explore from the PREDICT data.

And then 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. And then in terms of the time line, we expect the Phase I enrollment to finish -- to complete by 2022. And then we will be able to have a readout of the Phase I data by the end of 2022. And then by the end of 2023, we will have the readout for Phase II data. And by 2024, we'll 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. And this is the picture of the principal investigator, Dr. Jia Fan, when he presented at the keynote speech on the National Oncology Conference on Standardized Diagnosis and Treatment Conference in -- that was held a couple of weeks ago in Beijing. And the PREDICT study design and also the news was announced during that conference by Dr. Jia Fan, and it has attracted a lot of interest and attention from the community so far.

And then moving on to the next page, Page 11 lays out the study design for the PRESCIENT study. So compared to the PREDICT study, PRESCIENT study actually has 2 dimensions of expansion. The first is, obviously extending from the 9-cancer types to the 22-cancer types, which are listed on the upper right again. And also it has similar design but not divided into 2 phases.

However, it has -- another dimension of extension 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 what exactly are we testing there. But the expansion will be on the exploration from the PRESCIENT study while we focus not just on the cancer type expansion but also on the omics combination.

And then on Page 12, again, the objective for the PRESCIENT study as to -- we will be able to validate the methylation plus protein markers, among the 22-cancer types. And then we will be able to assess different -- the performance among different stages and different types of the cancer. And then very importantly, we will be able to evaluate the potential combination, including methylation protein and other genetic epigenetic biomarkers from the PRESCIENT study.

So in terms of the time line, we expect to complete enrollment for PRESCIENT by 2023. And then we -- for the PRESCIENT study, we will divide it again into prespecified training and validation sets. So by the end of 2023, we expect to be able to lock the model for the 22-cancer types from the training set. And then in another year, we will have the study readout for the validation set.

So 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. So on top, Dr. Jia Fan is the leading PI for the PREDICT trial. He is the fellow of the Chinese Academy of Sciences and also the President of the Shanghai Zhongshan Hospital. So for those of you who are not very familiar with the Chinese hospitals, Shanghai Zhongshan hospital is one of the China's largest comprehensive academic hospital. And it performs more than 100,000 operations each year and serves about 169,000 inpatients per year. And in 2019, it was ranked top 5 among China's general hospitals.

So 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 of the Chinese Academy of Medical Sciences. This hospital is arguably the top cancer specialist hospital in China. So we are very proud that these top oncologists are leading our PREDICT and PRESCIENT studies. And it actually reflects the sharply growing interest and acknowledgment from oncologist community in China for cancer early detection, especially in the past year or so, it has attract -- it did attract a lot of attention in this field.

And also, we think high-quality of cohorts and data will ensure timely recruitment and, of course, successful operation of the study, which will serve as the key in establishing a leadership position and maintaining our leadership position in the development of our cancer early detection products. So we are excited to share with you on these PIs and they are -- their level in -- among the oncologist community in China.

So with that, I think I'll pass to our CTO, Dr. Joe Zhang, to tell you more about our results released from the SEQC2 study. Joe?

Thanks, Shannon. So I'm going to cover a little bit about our Therapy Selection part. So for the Slide 15, which is a highlight what's the strength of Burning Rock in terms of a Therapy Selection and business. So with regards to superior products as well as the NMPA approval process for the different IVD kit in the pipeline, but also the commercial penetration. But today, I'm going to focus on the first bullet point, which is a superior product, which one of the evidence showing is a paper published last month in Nature Biotechnology.

This is in the Slide 16. This is basically a leading effort led by consortium -- community effort led by -- a consortium led by FDA, which they call MAQC consortium and focusing on the quality control of the sequencing business. So what you can see here, the paper has been published. We participated in both the Liquid Biopsy part as well as pan cancer, which is tissue based. So the Liquid Biopsy study has been published last month.

So Page 17 basically highlight what's the participated assay as well as study design. So there's 5 different companies participated. They are all kit vendor, which means all being capable to produce the Liquid Biopsy panel and well as sell as a kit format and to let the customers to use them. So Burning Rock as one -- is the only Chinese vendor, who participated in this study. And each vendor will distribute their kit to different labs. Also, the 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. Then the result will be submitted to FDA.

And for the principal investigator of this study, look at the data and based on the peer project, also led by SEQC2 effort and trying to know which is a positive -- what's the true -- ground truth for this data and trying to evaluate sensitively and specificity , we call it false positive rate as well as evaluate the reproducibility within lab, also the -- across labs.

So Burning Rock using the LungPlasma V4 panel, which we currently call OncoCompass Target panel for the Liquid Biopsy study. And it covered 168 genes being listed in the top table here.

So for the next slide, Slide 18, basically highlights several key performance comparison across different kind of panel and product. So Burning Rock box in the green color. And as you can see at the top part, basically the fragment depth, which means based on the sequencing involved how many unique fragment we can collected or recovery -- recovered from 25 nanogram reference material. As you can see here, the data is showing the higher the better, which means with limited amount of DNA input, how many real fragment you can collect from them all.

And the bottom panel compared coverage uniformity, which means like across this panel, what's the average coverage and how uniform this panel will be. And as you can see here, the Burning Rock also showing good performance compared to other vendors. All the coverages close to -- are similar to each other.

So for the next slide, in Slide 19, which compares 4 different hybridization capture panel, look at different sensitivity, like say, how -- what's the calling probability for different kind of variant allele frequency in DNA. And since each different panel has a 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 a different variant allele frequency being whether this kind of can be able to call it, and each column represents 1 sample, 1 replicates in 1 site, in 1 lab.

So Burning Rock is on the right most one. Basically, if it's been colored, which means it's variant has been caught. If it's blank, which means it's variants being missed and we call false-negative here.

As you can see here, basically almost all the color been filled for Burning Rock even if there's like 0.1% to 0.2% variant allele frequency being -- and the calling percentage is higher than some other panels. So this is just to give us a lot of confidence showing like our panel as well as our bioinformatics pipeline, showing pretty top performance compared to these -- the other vendors, especially this kind of classic -- molecular biology vendors.

So for the reproducibility, slightly -- on the next slide, Slide 20, we just compared across different kind of panel to look at how you reproducibility it is across panel, across labs or within labs. Since each lab process same sample 4 times. Also, there's a multiple labs perform. As you can see here, the reproducibility also Burning Rock data showing pretty good performance compared to the other vendors kit.

For the Slide 21, it just briefly compared different kind of input of DNA amount and compared to sensitivity, as we know, like the more DNA put in there and within the -- then the higher sensitivity there, so each panel showing this kind of trend. For the green line, basically representing Burning Rock's assay. And for both sensitivity as well as reproducibility, showing the Burning Rock's panel has a pretty good performance and are very stable on that. And also, even at a variant allele frequency of 0.1% to 0.5% showing a high performance.

For the Slide 22, very briefly, they just compare analytical accuracy based on the sensitivity and precision curve. And the -- as you can -- this is based on 25-nanogram of reference material input and across compare four different panels and the precision representing the, the positive predict value, PPV. And the sensitivity here is, as you recall, which means how sensitive you, how many -- the true-positive rate it is.

So the closer to the top right corner of this graph means the better performance. As you can see here, the overall analytical accuracy and especially the Burning Rock showing the best compared to other panels. So all this information just give us both from the paper published. I mean, this is basically a relatively, like say, fair comparison from different panel and using same reference material and give us a lot of confidence showing that our product in the Therapy Selection zone, showing the top performance, not only in China but also compared to the world, as you know, a lot of famous kit vendors, and we've been doing pretty good on that.

So here, basically, I just conclude the Therapy Selection part highlight. I will hand over to Leo talking about financial. Thanks.

Thank you, Joe. Our financials are shown on Page 25 of our presentation. And for this call, we'll focus mostly on our top line numbers.

And first, we recap that all our revenues are generated from our Therapy Selection business. So there is no contribution from Early 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 panel, our central lab revenue grew 72% -- 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 trend, January was impacted by COVID resurgence in Beijing, Shanghai and a few other key cities in China. So 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 minus 14% Q-on-Q. 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.

And 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 test available at more hospitals, which we think is important for building NGS penetration because this is the most typical format of testing in China. And second will be the continued execution of our multiyear NMPA registration pipeline process, which will be key in terms of competitive differentiation. So we remain focused on these initiatives for driving the long-term success of our therapy selection business.

With that, we conclude our prepared remarks, and we open up for questions, please.

(Operator Instructions) Your first question comes from the line of Doug Schenkel from Cowen.

Starting on the topic of asymptomatic screening. I appreciate all the detail you provided today. Regarding the 6-cancer, 9-cancer and 22-cancer asymptomatic screening programs, 3 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. And 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 for 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. So I understand your programs are not targeted at the U.S. or Western markets. They're targeted at China. So it just would be helpful to understand, again, what the answers are to my 3 questions as it relates to asymptomatic screening, given the market is different.

Okay. Hi, Doug. Thanks for your question. I'll take your question. I'll try. So 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.

And also, the recruitment strategy actually naturally complex with prospective asymptomatic validation study because in this study, the participants, the control arm actually, we define them as the "healthy" because they need to go through a health checkup or physical examination once at the recruiter point. But 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 checkup habits they're going through in their real life.

So PREDICT and PRESCIENT are not designed, they're 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 be design -- or to design the future asymptomatic prospective or even international studies.

However, for the 6-cancer test, the study that we -- I just mentioned that under planning, that one will be designed and powered to give us a definite answer for the asymptomatic population for the 6-cancer test. So 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 products in China is not crystal clear or anywhere near crystal clear, at this point, we're having a conversation with NMPA. So we don't have 100% answer that is 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 don't have -- you not only have to establish an individual level benefit, you have to establish a population level benefit.

So in order to do that, there are a lot more you need to evaluate beyond the 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. So in China -- I think we also talked about this a few times before. In China, the market is a pay out-of-pocket market. So we do believe that in China, it's possible to have the registration and reimbursement, there are sort of 2 things, and we will be able to have the registration by just showing the individual level of benefit. But of course, again, this is preliminary thoughts and things might change and we might have more information as times goes on.

That was really helpful. I think my other topics are probably more for Leo. So 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. So 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. So when it comes to ASPs, were there market pricing pressures in the quarter? Or was that a function of product mix? And then kind of 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?

Yes. So for the central lab channel, we did see ASP fluctuations quarter-over-quarter. And that was more to do with product mix. So we have not made any pricing changes for that channel during the first quarter. And so pretty much driven by product mix shifts and some seasonalities. So that was for the first quarter. For the remainder of the year, for the central lab, we think there are structural challenges that we'll -- we do need to work through. And if we look at -- as we mentioned earlier, if we look at building NGS penetration, we are putting efforts into the in-hospital channel. We think this is -- will be very important for the future growth of NGS penetration. That's the most typical formats 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. So we think looking for the rest of the year, in-hospital channel will be important in terms of driving growth.

For the in-hospital -- for the central lab channel, we have been building our sales team and headcounts. So we have seen sales and marketing expenses increasing over time, and that's mostly due to headcount increases. So we are putting more manpower on the grounds, speaking to more physicians to build up this channel, but we think that this will take time.

So 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. Then 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 being hospital volumes for the month of March, which grew double digits. And we are keeping a watch on the second quarter as we have not closed the second quarter yet.

Okay. And 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 of 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?

Yes. 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. And we did leave some buffer for COVID fluctuations, and we did get hit by that in January. So lot of surprises in terms of looking at our guidance. Looking forward, 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. So we need to go back and work hard, and we look forward to update you guys in the next earnings call.

Our next question comes from [Ethan Cherry] from Bank of America.

I'm Ethan from Bank of America, and I will ask 2 questions on behalf of our analyst, David Lee. First is that, can you help some update information about our 6-cancer test. Is there any changes for the timetable guidance?

You mean for Early Detection commercialization?

Yes, and the approval and the like of discussion with NMPA, is there any update?

Last time, we talked about that we're going to be doing EAP and also the prospective clinical trial. And in terms of the commercialization time line, we are executing our team for commercialization and operation. So we think that the key point for the early pan-cancer early detection is for the consumer side. So we recently are recruiting a team from consumer industry and also the Internet industry.

And we believe that we have already found the right way to commercialize that. And -- but at the same time, that's a totally new thing thing in the market. So how to do that SOP in this time? And when you're trying to optimize the whole size. So far, we're seeing that everything is on the right track. As we said that the commercialization will start early next year.

And in terms of the clinical trial, Shannon will talk about that.

Right. I don't think we ever gave any guidance on registration because we honestly are ongoing -- having an ongoing conversation with NMPA. So as I said, there's nothing unsure at this point. And also, we are -- of course, for the whole field, the Early Detection products, the registration pathway for that is not clear yet. So I think it's a dynamic process or discussion with NMPA, so we don't have a specific timetable that we could give out yet. But as you can see for the progresses or efforts ongoing, everything is going as what we planned or expected, including the study that we are planning for among the asymptomatic population. that's the ongoing successes, and also what we have released the last time.

Very clear. And the second question is about the participants in our PREDICT and PRESCIENT study. Do you think that for the PREDICT study, they are around 14,000 participants while for the PRESCIENT, they are around 12,000. And can you help us to illustrate more about how this number has been confirmed? And why there's a difference and why PRESCIENT has fewer number of participants?

Thanks. It's a very good question. Thank you for noticing that. Actually, for PREDICT, because we have quite rich preliminary results for those 9 cancers, at least 6 out of the 9 cancers and so a little bit data on the other 3 cancer types. So we were able to design the study and planning for the sample size on a stage specific estimate for the sensitivity and TOO accuracy. So that's why for PREDICT, even with fewer cancer types, we will -- we are planning for a 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.

However, 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 tests as for these 9. So 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.

So that's why for PRESCIENT, for each cancer type, we actually have a smaller sample size. And also even among, PREDICT and PRESCIENT, each cancer type actually has different sample size plans in terms of -- or depending on our estimated sensitivity that we will be able to reach or achieve.

So especially for the PRESCIENT study, we actually have fewer samples planned for the 9 cancer types that were already covered in the PREDICT and we allocated more samples for the other 13 cancer types. But 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.

Our next question comes from Sean Wu from Morgan Stanley.

And I actually -- I'm also kind of curious about the numbers used for the group study. You have exactly 14,026 for PREDICT and 11,879. How did you come out with those kind of numbers. Let's just say, for my curiosity, so for 1 study, you were doing 9-cancer types, the other 22. I mean, in some sense, why don't you just combine them together? So those 2 studies totally -- clearly are designed for different purposes, of course. For 9 ones -- should we expect that you will get a more conclusive result from the 9 ones compared to 22 cancer types. And also your competitors, some of them have come out with prospectively designed product for 1 type of cancer detection, maybe liver cancer or again prostate cancer. What's the difference -- the advantage of multi versus like single one? For liver cancer, clearly, if people drink a lot and (inaudible), this 1 type maybe is also very advantage for them.

And then finally, I think you have found out some very good oncologists, especially in top hospitals and they have to do your clinical trials. How you've been successful with getting so much -- so many of key PIs, like (inaudible) as part of your program. Thank you very much.

Thank you very much. Okay. Well, first of all, for the study sample size, as I just previous explained PREDICT and PRESCIENT are designed based on different objectives. For PREDICT, we are aiming to estimate stage and cancer type specific sensitivity. So for each cancer type, we allocated more sample size. But for PRESCIENT, because we didn't have as much previous knowledge to support stage and cancer type specific design, that's why we actually will only assess the cancer type or cancer -- yes, cancer specific sensitivity. So roughly, that's why for PRESCIENT -- we have a little bit fewer sample size plan for the PRESCIENT study?

And also, for your question, why don't we just combine the 2 because they are for 2 different products because for the PREDICT study, we're using our 9-cancer test product. And then for PRESCIENT study, we will use our next-generation of 22-cancer test product. They're not just -- it's an add-on relationship between the 2 products. Actually, the chemistry and also the marker selection and the model were all changed and hopefully will all improve between the 2 generations. So that's why for the new generation, we will have to retest its performance to see whether it holds or even improve on the existing 9 cancers that were already tested in PREDICT.

And for your last question about the principal investigators, thank you for a comment. We are also very proud. And as I said, it reflects actually the strong interest and attention that Early Detection has strong among the oncologist community. I would say, about 3 years ago, none of them really believed in the new technology is getting close to real contribution -- or to make real contribution to cancer early detection. But nowadays, a lot of them believe in that, and they they think the new technology, especially the epigenetics 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 the one. And for two, there are actually very few hospitals in China that has the capability and capacity to be able to host studies like PREDICT or PRESCIENT or lead studies like these. And it actually requires a lot of organization power and also the impact from the principal investigators.

So 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.

So ladies and gentlemen, we have reached the end of the question-and-answer session. So with that, we conclude our conference for today. Thank you for participating. You may all disconnect.