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Burning Rock Biotech Limited (BNR) Q1 2021 Earnings Call Transcript | The Motley Fool

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Burning Rock Biotech Limited (NASDAQ:BNR)
Q1 2021 Earnings Call
May 25, 2021, 8:00 a.m. ET

Contents:

  • Prepared Remarks
  • Questions and Answers
  • Call Participants

Prepared Remarks:

Operator

Good day, and thank you for standing by. Welcome to Burning Rock’s 2021 first-quarter earnings conference call. At this time, all participants are in a listen-only mode. After the speakers’ presentation, there will be a question-and-answer session.

[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 terminologies such as will, expects, anticipates, future intends, plans, believes, estimates, targets, 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.

Yusheng HanChief Executive Officer and Founder

Thank you. Welcome to Burning Rock’s earnings call. I am Yusheng Han, the CEO and founder of Burning Rock. And today we also have our COO, Shannon Chuai; our CTO, Joe Zhang; and our CFO, Leo Li in this call.

The Burning Rock is China’s molecular diagnostic leader for precision oncology. There are two parts to our business. The first one is early detection and using liquid biopsy for pan-cancer. And the second is for therapy selection and MRD.

All right, will you please turn to Page 4? So today we’re going to recap the recent progress for those 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 is the PREDICT trial for the nine-cancer test is going well, mostly. And our COO, Shannon Chuai will talk about these two trials in detail.

In the meantime, the preparation of our commercialization of the six-cancer test is ongoing. And we are continuously building our commercial and operating team and optimizing the SOPs. Nothing significantly important to report for the six-cancer so far. But if you have any questions, you’re welcome to ask at our Q&A session.

And for the therapy selection, we have great news that finally the results of the liquid biopsy part of SEQC2 have published in Nature Biotechnology, which proved to us that Burning Rock’s quality is at 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?

Shannon ChuaiChief Operating Officer

All right. Thanks, Yusheng. So if we go to Page 6, this is to recap the product development roadmap for our early detection programs. So we started with a 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 the 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. And then most recently, I think a lot of you are familiar with our six-cancer test results that we released last year in November on the ESMO Asia.

The six-cancer test includes or covers lung cancer, colorectal cancer, liver, ovarian, pancreatic, and oesophageal. And the data showed that we were able to maintain our 81% sensitivity while improving the specificity to 80 — about 98%. And we also were able to achieve reasonably good accuracy for TOO analysis, tissue of origination analysis, on — from this — as high as about 81% accuracy from the six-cancer test in the results we released last year. And then for the six-cancer test, after the THUNDER study, which was a case-control study to validate the specificity and sensitivity of the product, we also — we’re planning to move on to a prospective interventional study for the asymptomatic population.

So that study is currently under planning and I’m going to show you an overview in later pages. And today, we really 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 had mentioned, for the nine-cancer test, our current status is that the PREDICT study that we started earlier is going very mostly 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 that 22-cancer test, we have just kicked off a large clinical development study a few weeks ago on May 2021 and it’s called PRESCIENT. So 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. 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 product, there are four — 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. 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’re laying out here as the case-control study. In these studies, they are real clinical cases and control 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 — for early detection products. And then after that, eventually, we would 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 intended to you — intend to use population.

And for this one, you can sort of compare that to the Pathfinder trial on — from GRAIL as well in which it is testing Galleri on the asymptomatic population in a prospectively recruited cohort. So for our three-cancer test, we — after we finished the assay development and analytical validation, we did move on to the clinical development. So we will move forward to the six-cancer test. And for the six-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 on the last page as the THUNDER study.

The THUNDER study was able to show in training and a pre-specified validation cohort 81% of sensitivity and 98% of specificity. And then, again, the prospective interventional study on the asymptomatic population for the six-cancer test is currently under planning and we hope that we will be able to disclose more details about that study once it is finalized and released or kicked off in the near future. And then, we — in the meanwhile, in a parallel, we are also moving on to more cancer — to cover more cancer types, of course. So 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.

And the analytical validation for that product is currently ongoing. And in the pit — in the meanwhile, we were able to start the enrollment on the case-control, the PREDICT study in parallel to sort of shorten — to shorten the development time overall. And the PREDICT study, if you might recall, it actually contains two phases. And in phase II, it does contain a factor of testing or validating the amount of small asymptomatic cohort or healthy controls.

So that’s why over here, we are sort of standing back 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, we’ll be able to give you more details of how the two 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, it 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 — on 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 these studies so that we will be able to recruit samples — clinical samples for future testing or validation for this 22-cancer test in the — in parallel with the product development effort. So if we move on to Page 8, this is — this outlines the study design of the PREDICT study. Again it covers nine 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% — less than10% coming from benign diseases, and the rest, from a healthy control. And one thing we wanted to point out is that 70 — more than 75%, at least 75% of the cancer participants will be on from stage 1, 2, 3.

So most of the cases, we will focus primarily on the early stage patients. We 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 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 pre-specified training and testing sets.

And within the training, we will be able to customize or tune or model and cut off and then to be able to report the results or performances on the validations that set within the phase I cohorts. And then after that, the model, both the assay and the model will be locked and then we move on to phase II sample processing. So in phase II, we will have a totally independent set of data to test or to validate the performance of the locked model or method from phase I, and to be able to have a rather accurate assessment of the model performance for the nine-cancer test. And then one thing we 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 on 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 our objectives and timeline 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 nine cancers — nine types of cancers. And then for the secondary objective, we, of course, wanted to learn about the performance among different types of cancers and also non-different stages of cancers. And also we wanted to know whether other biomarkers, including protein biomarkers that we are processing in parallel with these PREDICT samples, whether will help in a way that we do expect 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 some 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 timeline, 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 readouts for phase II two data.

And by 2024, we would be able to finish the follow-up and have the complete data set for the PREDICT study. On Page 10, we wanted to briefly mentioned 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 as a keynote speech on the National Oncology Conference on Standardized Diagnosis and Treatment Conference in the — 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 designed for PRESCIENT study. So compared to the PREDICT study, PRESCIENT study actually has two dimensions of expansion. The first is, obviously, extending from the nine cancer types 22 cancer types, which are listed on the upper right again.

And also we have a similar design but not divided into the two 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 the exploration from the PRESCIENT study while being focused 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 is to — we will be able to validate the methylation plus protein markers amount of 22 cancer types, and then we will be able to assess different performance among different stages and different types of cancer.

And then very importantly, we will be able to evaluate the potential combinations including methylation protein and other genetic, epigenetic biomarkers from the PRESCIENT study. In terms of the timeline, we expect to complete enrollment for PRESCIENT by 2023. And then with — for the PRESCIENT study, we will divide again into pre-specified training and validation steps. So by the end of 2023, we expect to be able to lock the model for 22 cancer types from the training set.

And then in another year, we will have this study readout for the validation set. So on Page 13, I’m sorry, on Page 13, this is again to introduce you — 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.

Jai Fan, is the leading PI for the PREDICT trial. He is the fellow of the — a 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 China’s largest comprehensive academic hospitals, 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 in — among China’s General Hospital.

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 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 study.

And it actually reflects the sharply growing interest and acknowledgment from the oncologists’ 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 a high quality of cohorts and data will ensure timely recruitment, and of course, the successful operation 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. So we are excited to share with you these PIs and their level in — among the oncologists’ community in China. So with that, I think our path to our CTO, Dr.

Joe Zhang, to tell you more about our recent results released from the SEQC2 study. Joe?

Joe ZhangChief Technology Officer

Thanks, Shannon. So I’m going to cover a little bit about our therapy selection part. So for Slide 15, which highlights what’s the strengths of Burning Rock in terms of a therapy selection business. So with regards to a superior product, as well as the NMPA approval process for the different IBD kits 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 number the evidence showing is a paper published last month in Nature Biotechnology. This is in Slide 16. This is basically a learning effort led by a consortium — a community effort led by — a consortium led by the FDA, which they call MAQC Consortium, and focusing on the quality control of the sequencing business. So what you can see here, so the paper has been published.

We participate 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 highlights what’s the participating assay, as well as the study design. So there’s a five different company participated, they are all kit vendor, which means all being capable to produce the liquid biopsy panel and while selling as a kit format and lead the customer to use them.

So Burning Rock is the one and only Chinese vendor that participated in this study and each vendor will distribute their kit to different labs. Also, the lab will receive the FDA-distributed reference material and the performed 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 all the results 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 positive — what’s the true ground truth for this data and trying to evaluate sensitivity 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 lung plasma v4 panel, which we currently call OncoCompass Target panel for the liquid biopsy study, and it covered 168 genes being listed in the top hand table here. So for the next slide, in Slide 18, basically highlights several key performance comparisons across different kinds of panels and products. So Burning Rock is the box in the green color, and as you can see in the top part with the fragment depth, which means based on the sequencing result how many unique fragments that we can collect or recovery — recovered from 25 nanogram reference material. As you can see here, the data showing the higher the better, which means with a limited amount of DNA input, how many real fragments you can collect from the mouth.

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, Burning Rock also showing good performance compared to other vendors. Just all the coverages close to are similar to each other. So for the next slide, in Slide 19, which compare four different hybridization capture panel and look at a different sensitivity, like say, how or what’s the calling probability for different kinds of variant allele frequency bin.

And as this each different panel has a different kind of true positives since the panels are different for the — on PI they basically compare based on their ground truth and then look at different value — variant allele frequency bin whether this panel can be able to call it and each column represent one sample, one replicates in one side, in one lab. So Burning Rock’s on the right, most one basically, if it’s been colored, which means this variant has been called; if it’s blank, which means it’s variants being missed, as we call false-negative here. As you can see here, basically, almost all the colors have been filled for Burning Rock, even if it’s applied for 1%, 2.2% of variant allele frequency bin, and the calling percentage is higher than some other panel. So this is just to give 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 a classic, you know, molecular biology vendors.

So for the reproducibility slide, next slide, Slide 20, they just compare across different kinds of the panel, look at how reproducibility it is across the panel, across lab or within lab. So as each lab process the same sample four times, also there are multiple labs performed. As you can see here, the reproducibility also Burning Rock data showing pretty good performance compared to other vendors’ kit. For Slide 21, it just briefly compared a different kind of input of DNA amount and compared to sensitivity.

As we know, 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, represented Burning Rock’s assay for both sensitivities, as well as reproducibility showing the Burning Rock’ panel as a pretty good performance and very stable on that, and also at a variant allele frequency of 0.1%, 2.5% showing high performance. For Slide 22, very briefly, they just compare analytical accuracy based on the sensitivity and precision curve. And the — as you can — this is the based on 25 nanograms of reference material input and — across compare four different panels and the precision representing the, you know, the positive predictive value, PPV, and the sensitivity here it means we call, 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. We can see here that 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, and this is basically relatively like, say, fair comparison across the 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 compared to the world, as you know, a lot of famous kit vendor, and we’ve been doing pretty good on that. So here basically, I just conclude the therapy selection part highlight.

I will hand it over to Leo to talk about financials. Thanks.

Leo LiChief Financial Officer

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 channel, 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 the industry growth rate, indicating that we’ve been able to gain some shares 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. 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 OK month. Because of the negative track from January and February, the sequential growth rates were negative for the first quarter at minus 14% QOQ. 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 multi-year 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.

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

Questions & Answers:

Operator

Thank you. [Operator instructions] Your first question comes from the line of Doug Schenkel from Cowen. Please go ahead.

Doug SchenkelCowen and Company — Analyst

Hi, good day and thank you for taking my questions. Starting on the topic of asymptomatic screening, I appreciate all the detail you provided today. You know, 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? 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 is 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 three questions, as it relates to asymptomatic screening, given the market is different.

Shannon ChuaiChief Operating Officer

OK. Hi, Doug. Thanks for your question. I’ll take your question.

I will 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 these studies, the participants, the control, actually, we define them as the “healthy”, because they need to go through a health checkup or physical examination once — you know 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, you know, 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, powers, or designed to give us answers for the case-control cohorts, which will help us to design the future asymptomatic prospective or even interventional studies. However, for the six-cancer test, the study that we just mentioned, which is under planning, that one will be designed and powered to give us a different answer for the asymptomatic population for the six-cancer test. So that one, we do think or we are designing 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 an MPA so we don’t have 100% answers that is going to be enough. But at least, it’s powered to answer the question about an individual level whether the benefits 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 just sensitivity, specificity on that individual level, for different cancer types, etc. You also have to establish, you know, benefits in terms of health economics, etc. 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 is sort of two things, and we will be able to have the registration by just showing the individual level of benefits. But of course, again, this is a preliminary result, and you know, things might change, and we might have more information as time goes on.

Doug SchenkelCowen and Company — Analyst

Thanks so much for that, Shannon. 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, you know, 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, you know, 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, you know, essentially what’s built into guidance?

Leo LiChief Financial Officer

Yeah. So, for the central lab channels, 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, so it’s pretty much driven by product mix shifts and some seasonality, 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.

Then 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 will be very important for the future growth of NGS penetration as 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, the 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.

Doug SchenkelCowen and Company — Analyst

So, Leo, you know, 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?

Leo LiChief Financial Officer

The first Q drop of the in-hospital channel was expected, as we were expecting Chinese New Year and, typically, there were not a lot of orders 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.

Doug SchenkelCowen and Company — Analyst

OK. And that’s a perfect segue to my last question, which again, is on guidance. You know, obviously, you knew Lunar New Year was in Q1, as it always is. It sounds like what surprised you was the COVID impact in 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?

Leo LiChief Financial Officer

Yeah. As we were building the guidance, we were expecting a second-half heavy versus the first-half lights 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 a lot of surprises in terms of looking at our guidance. Looking forward to 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 updating you guys in the next earnings call.

Doug SchenkelCowen and Company — Analyst

OK. Thanks to all of you. I appreciate all the details.

Leo LiChief Financial Officer

Thanks, Doug.

Operator

Thank you. Our next question comes from Ethan Terry from Bank of America. Please ask your question.

Unknown speaker

Thank you for taking my question. I’m Ethan from Bank of America. And I will ask two questions on behalf of our analyst, David Lee. The first is that, can we have some updated information about our six-cancer test? Are there any changes to the timetable guidance?

Yusheng HanChief Executive Officer and Founder

Do you mean for early detection commercialization?

Unknown speaker

Yes, and approval and the likes, a discussion with NMPA, is there any update?

Yusheng HanChief Executive Officer and Founder

You know, last time we talked about we’re going to be doing the EAP and also the prospective clinical trial. And in terms of the commercialization timeline, now, we are executing our team for commercial 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 team from a consumer industry and also the internet industry.

And we believe that that we have already found the right way to commercialize that. And — but at the same time, you know, that’s a totally new thing in the market. So how to build up an ASP at this time and when it’s time to optimize the whole process. So far, we’re seeing that everything is on the right track, as we set the commercialization will start early next year.

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

Shannon ChuaiChief Operating Officer

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 sure at this point and also, we are, of course, for the whole feud, the early detection products, the registration pathway for that is not clear yet. So I think it’s a dynamic process or discussion with the NMPA.

So we don’t have a specific timetable that we could give out yet. But as Yusheng said for all the progress or efforts ongoing, everything is honestly going as we planned or expected, including the study that we are planning for — among the asymptomatic population, that still ongoing as expected, and also as what we have released the last time.

Unknown speaker

Thank you. Very clear. And the second question is about the participants in our PREDICT and PRESCIENT study. Do you think that for the PREDICT study there 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 the PRESCIENT have fewer numbers of participants? Thank you.

Shannon ChuaiChief Operating Officer

Thanks. It’s a very good question. Thank you for noticing that. Actually for PREDICT, because we have quite rich preliminaries out for those nine cancers, at least six out of the nine cancers, and there’s still a little bit of data on the other three cancer types.

So we were able to design the study and plan 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 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 is 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. So that’s why when we designed the PRESCIENT study, it’s a more 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 a 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. But all in all, the design, the sample size calculation were based on different objectives.

That’s why you see different sample sizes for each cancer type.

Unknown speaker

OK, thank you. Very clear. That’s all my questions.

Operator

Thank you. Our next question comes from Sean Wu from Morgan Stanley. Please ask your question.

Sean WuMorgan Stanley — Analyst

OK. Thank you for taking my question. And I actually — I’m also kind of curious about that full number used for the cohort study. You have exactly 14,026 of PREDICT and 11,879.

How did you come out with those kinds of numbers? Let’s just say for my curiosity, for one study you were doing nine-cancer type and the other 22, I mean, in some sense, why don’t you just combine them together? Those two sides clearly are designed for different purposes, I suppose. For the nine ones, do you expect that you will get more conclusive results from the nine ones instead of the two combined? And also your competitors, some of them have come out with a prospective well-designed product and for one type of cancer detection, or liver cancer, or prostate cancer. What’s the difference, the advantage of more types versus a single one? And for liver cancer, clearly, if people drink a lot or ingest [Inaudible] this one type is basically — can be possibly intended for them? And then finally, I think you have found some very good oncologists, which are from the top hospitals — oncology hospitals to do your clinical trials, how have you been so successful with getting so much — so many PIs, from like Beijing and Hubei as part of your program? Thank you very much.

Shannon ChuaiChief Operating Officer

OK. Well, 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. So for each cancer type, we allocated more simplified.

But for PRESCIENT, because we didn’t have as much previous knowledge to support stage and cancer-type-specificity design that’s why we actually will only assess the cancer type or cancer, yeah, cancer-specific on sensitivity. So roughly — that’s why for PRESCIENT, we have a little bit fewer sample size plans for the PRESCIENT study. And also for your question, why don’t we just combine the two, because they are for two different products, because for the PREDICT study, we’re using our nine-cancer test product, and then for the PRESCIENT study, we will use our next generation of the 22-cancer test product. They’re not just — it’s not an add-on relationship between the two products.

Actually, the chemistry and also molecule selection, and the model will all change and, you know, hopefully, will all improve between the two 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 nine cancers that were already tested in PREDICT. And for your last question about the principal investigators, thank you for your comments. We are also very proud and as I said, it reflects, actually, the strong interest and attention that early detection has a strong among the oncologists’ community.

I would say about three years ago, none of them believed in, you know, the new technology is getting close to real at clinical application or to make a real contribution to cancer early detection. But nowadays, a lot of them believe in that and they think the new technology, especially the epigenetics-based biomarkers plus machine learning and next-generation sequencing is finally bringing into a reality that early detection can be realized on a large scale, especially on a multi-cancer application. That’s for one. And 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, and it actually requires a lot of organization powers 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. Does that answer your question?

Operator

All right, thank you. [Operator signoff]

Duration: 59 minutes

Call participants:

Yusheng HanChief Executive Officer and Founder

Shannon ChuaiChief Operating Officer

Joe ZhangChief Technology Officer

Leo LiChief Financial Officer

Doug SchenkelCowen and Company — Analyst

Unknown speaker

Sean WuMorgan Stanley — Analyst

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