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Good afternoon, ladies and gentlemen, and welcome to Veracyte's Third Quarter 2019 Financial Results Conference Call. As a reminder, today's conference call is being recorded.
I'd now like to turn the conference over to Keith Kennedy, Veracyte's Chief Operating Officer and Chief Financial Officer. You may begin.
Thank you, Sidney. Good afternoon, everyone, and thanks for joining us today for a discussion of our third quarter 2019 financial results. With me today are Bonnie Anderson, Veracyte's Chairman and Chief Executive Officer; Giulia Kennedy, our Chief Scientific Officer and Chief Medical Officer; and John Hanna, our Chief Commercial Officer.
Before we begin, I'd like to remind you that various statements that we make during this call will include forward-looking statements as defined under applicable securities laws. Forward-looking statements include those regarding our future plans, prospects and strategy, financial goals and guidance, product attributes and pipeline, drivers of growth, expectations regarding reimbursement, and other statements that are not historical fact.
Management's assumptions, expectations and opinions reflected in these forward-looking statements are subject to risk and uncertainties that may cause actual results and/or performance to differ materially from any future results, performance or achievements discussed in or implied by such forward-looking statements, and the Company can give no assurance they will prove to be correct and will not provide any further guidance or updates on our performance during the quarter, unless we do so in a public forum.
Please refer to the Company's October 22nd, 2019 press release and the risk factors included in the Company's filings with the Securities and Exchange Commission for discussion of important factors that may cause actual events or results to differ materially from those contained in our forward-looking statements.
Prior to this call, we announced our third quarter 2019 results which are available on our website at veracyte.com under Press Releases in the Investor Relations section. We also published a financial presentation, which I will reference during my remarks, and a presentation on the preliminary data for our Nasal Swab Classifier which Bonnie and Giulia will reference later. These presentations are also available on our website under Events and Presentations in the Investor Relations section of our website.
I will now turn the call over to Bonnie Anderson, Veracyte's Chairman and CEO.
Thank you, Keith, and thanks everyone for joining us today for our third quarter 2019 earnings call. We are speaking to you from the CHEST Conference in New Orleans, where we announced exciting new data this morning regarding our Nasal Swab Classifier for early lung cancer detection. We'd like to address and underscore three key points on today's call. First is the continued strength and momentum of the business; second is the significant progress we are making in our pulmonology franchise; and third is the new data for the first ever nasal swab test which we believe will be pivotal to scaling our business and expanding to global markets.
We will start by reviewing our third quarter results. We generated record revenue of $31 million in the third quarter of 2019, an increase of 32%, and genomic test volume of 9,941 tests, an increase of 24% over the third quarter of last year. At the same time, we improved our net cash used in operating activities to $1.6 million, an improvement of 13% over the prior year. We reiterate our full year revenue guidance of $119 million to $122 million, and net cash used in operating activities of $2 million to $4 million and remain on track to reach operating cash flow breakeven before the end of 2019.
I will now share updates on the key metrics with which we are measuring our performance in 2019, the first is revenue growth. We continue to see strong growth across all three of our core classifiers. In pulmonology, we delivered over $1 million in Percepta revenue for the second quarter in a row. Customer response to the Percepta Genomic Sequencing Classifier or GSC, which can now down-classify patients to low-risk as well as up-classify them to high-risk following an inconclusive bronchoscopy continues to be quite positive. We are on track to report an estimated 3,000 results this year, doubling the prior year results.
Our Envisia Classifier is gaining impressive traction as well, with its ability to help physicians distinguish Idiopathic Pulmonary Fibrosis or IPF from other Interstitial Lung Diseases or ILDs without the need for surgery. Over 135 sites have ordered an Envisia test to-date. The third quarter volume nearly doubled that of Q2 and we remain on track to report Envisia test volume between 500 and 1,000 tests for the year.
We also continued the strong momentum of our flagship Afirma business in thyroid cancer, where we reported third quarter test volume of 8,925. This brings our year-to-date Afirma volume to over 26,000 tests, which is a 21% increase over the same period last year. Our solid product growth reflects the continued success of our integrated sales strategy. In fact, the number of accounts that are using more than one of our products grew by 30% in the third quarter to a total of nearly 220 accounts.
Finally, in addition to product revenue, we booked $4.3 million in biopharmaceutical revenue during the third quarter. This stems from our accelerated milestone achievements with the Johnson & Johnson lung cancer initiative as well as our continued collaboration with Loxo Oncology.
Evidence Development is our second metric of success. Here too we experienced significant progress in the third quarter. In September, two new papers added to the growing body of evidence supporting the use of Afirma Xpression Atlas or XA to help guide surgery decisions in patients whose thyroid nodules are deemed suspicious for cancer by our Afirma Genomic Sequencing Classifier. This includes a strong clinical and analytical validation paper published in Frontiers in Endocrinology, as well as a study published in the journal thyroid, reinforcing the task value in identifying the presence as well as the clinical relevant -- relevance, a specific gene alterations found in preoperative thyroid nodules. We are also looking forward to the American Thyroid Association's Annual Meeting next week, where multiple poster presentations will showcase data derived from the Afirma XA, further defining the genomic landscape around thyroid cancer.
In pulmonology, we are having tremendous engagement with customers here at CHEST. In addition to the new nasal swab data, five studies for our commercial products are being presented. These include three abstracts showing that the Envisia Classifier enhances physician’s ability to confidently diagnose IPF in combination with high-resolution CT imaging, as well as two abstracts demonstrating the clinical validity and utility of the Percepta Classifier in lung cancer diagnosis when bronchoscopy results are inconclusive. I'm especially proud of the strong scientific and medical reputation our team is building in pulmonology.
Our third metric of success is Pipeline Advancement. In addition to our Nasal Swab Classifier, we are announcing that we formed a research collaboration with National Jewish Health, one of a leading respiratory centers in the country to explore opportunities to further improve diagnosis of IPF and other ILD's. Through the collaboration, we will combine diagnostic imaging data from National Jewish Health with whole-transcriptome RNA sequencing genomic data from our rich bio repository of ILD patient samples.
Our goal is to determine if these expensive and complementary datasets when informed by our Deep Machine Learning expertise can enhance diagnosis across the care continuum for ILD patients. We look forward to keeping you appraise of outcomes from this collaboration and anticipate it being showcased in our future scientific meetings.
Our fourth major success is financial discipline. Here too, our team has continued to excel. Our net cash used in operating activities for the third quarter of 2019 was $1.6 million, a 13% improvement over the third quarter of last year. We remain confident that we will achieve our goal of reaching cash flow breakeven before the end of 2019.
I will now turn the call over to Keith to review our financial results for the third quarter of 2019.
Thank you, Bonnie. As mentioned earlier, our third quarter 2019 financial presentation is available under Events and Presentations in the Investor Relations section of our website.
Turning to Page 3 of our financial presentation. Our performance against six financial key performance indicators or KPIs for the third quarter of 2019 as compared with the prior year's quarter, including select highlights for each metric at the bottom of the page are as follows. Revenue of $31 million increased 32%. Excluding $4.3 million of biopharmaceutical services, revenue of $26.7 million increased 15%. Genomic volume of 9,941 reported tests increased 24%. Gross margins of 71% increased 600 basis points. Excluding biopharma services, gross margins increased 200 basis points from 64% to 66%. Operating expenses excluding cost of revenue increased 21%. Net loss of $0.7 million improved 84%. Net cash used in operating activities of $1.6 million improved 13%. And at September 30th, we had cash and cash equivalents of $196 million.
Turning to Page 4 of the presentation. Our performance against these six KPIs for the year-to-date period ended June 30th, 2019 compared to the same prior year period showed strong comparable performance. The next six pages outline the sequential and year-over-year results underlying each of the six financial KPIs, a few observations. As illustrated by the revenue and genomic volume trends on slides 5 and 6, we continue to see positive momentum across the business. Our lung portfolio represented approximately 1,000 tests or 10% of our genomic volume this quarter.
Turning to Page 12. In our 2019 guidance, as Bonnie stated earlier in her remarks, we are reaffirming our revenue guidance of $119 million to $122 million, and net cash used in operating activities of $2 million to $4 million. In the third quarter, our loss from operations was $1.8 million, which included $3.6 million of depreciation, amortization and stock-based compensation. To add some additional color on our outlook for 2019, principally in the fourth quarter of 2019, in Q4, we anticipate receiving $4 million in payments from Johnson & Johnson related to milestones achieved in the second and third quarter. We expect gross margins, excluding the impact of biopharma services revenue, to be within the 65% to 67% range. In Q4, we expect our average quarterly spend for sales and marketing to stay within $1 million band around the average quarterly spend of $13.5 million, and our average quarterly spend for our combined G&A and R&D spend to stay within $1 million band around the combined average quarterly spend of $10.5 million.
I will now turn the call back over to Bonnie.
Thanks, Keith. Now I will turn to our big news of the day, the preliminary data that we announced earlier today for the first ever non-invasive Nasal Swab Classifier to enable early lung cancer detection and diagnosis. I'll first walk you through the market and where in today's clinical pathway of care, we are positioning this test. Dr. Giulia Kennedy, our Chief Scientific and Medical Officer will then discuss the test development, these exciting new data, and our next steps for bringing the test to market. As Keith mentioned, we have published a presentation which will reference in our remarks. You can find this in the Investor section of the website under Events and Presentations.
The first five slides of the presentation give you background on how Veracyte is transforming care throughout the patient journey. Starting with our mission of improving diagnostic accuracy, we have expanded to advance early detection and inform treatment decisions. We see our Nasal Swab Classifier as a key opportunity to move upstream in the patient care continuum.
Turning to Slide 6. As you likely know, lung cancer is the biggest cancer killer in the US and worldwide. An early detection of lung cancer is key to saving lives. In patients on survival increase significantly when the disease is caught before it has spread.
As illustrated on Slide 7, lung nodules are often the first sign of lung cancer, but since most nodules are benign, a big challenge for physicians is knowing which patients need invasive biopsies and which patients can be safely followed non-invasively. Currently, about 2 million lung nodules are detected by imaging in the United States each year. These cases are derived from the approximately 10 million patients who are at high risk for lung cancer and are thus eligible for annual CT screening, as well as approximately 1.6 million cases where in lung nodules are detected incidentally via CT scan or X-ray. We expect the number of nodules to increase as screening programs continue to expand. When lung nodules appear suspicious on CT scan, patients are typically referred to a pulmonologist for workup and diagnosis. The pulmonologist then decides how to work up each patient based on the risk the dead nodule is cancerous. Those assessed at being higher risk typically are advanced to more invasive diagnostic evaluation and potential treatment, whereas those considered low risk are monitored noninvasively. Today, there is a lag of standardization and objectivity in determining this risk. As a result, many patients -- many benign patients undergo work-ups they do not need and patients with cancer potentially experience delayed diagnosis and treatment. We propose our Nasal Swab Classifier will help solve this problem.
As you can see on Slide 8, we are positioning our Nasal Swab Classifier to provide pulmonologist with a simple, convenient, and objective tool to inform patients diagnostic and treatment pathway. The sample for this test can be collected right in the pulmonologist office, with no need to refer the patient out for a blood draw. And as Giulia will show you, the preliminary data suggest that our Nasal Swab Classifier can transform this trajectory for many patients at this point, enabling patients with lung cancer to get the treatment they need sooner, while helping patients whose nodules are actually benign avoid unnecessary and costly invasive procedures. By accurately identifying low and high-risk patients, we believe we can greatly reduce the number of patients in the current intermediate risk or uncertain path forward risk pool. This would significantly improve patient management and health outcomes compared to today's current standard of care.
On Slide 9, we note that we estimate that the market opportunity for our test is approximately $1.9 billion in the US. This is based on the estimated 750,000 patients annually who are referred to a general pulmonologist for work-up of a suspicious looking lung nodule found either through lung cancer screening or incidentally. We estimate the market opportunity to be approximately $3.9 billion for both the US and the European Union.
As a reminder, on Slide 10, development of our Nasal Swab Classifier stems from our long-term collaboration with Johnson & Johnson innovation and the lung cancer initiative, which we announced in January 2019. We also plan to explore opportunities to deploy our field of injury technology at other points along the lung cancer care continuum. We believe the overall global lung cancer diagnostic market is approximately $30 billion.
I will now turn the call over to Dr. Giulia Kennedy, our Chief Scientific and Medical Officer, to walk you through the new data.
Thanks, Bonnie. As Bonnie mentioned, our nasal classifier is built on proven field of injury science. This means we can detect genomic damage associated with lung cancer in the airways of current or former smokers. Our Percepta GSC uses this approach to determine from cells collected in the main bronchial airway, whether remote lung nodule is likely cancerous or not.
In a study published in the Journal of the National Cancer Institute in 2017, researchers from Boston University showed that this genomic damage could also be detected in epithelial cells collected from the nose. Our preliminary data confirms and extends these findings, allowing us to develop a prototype set of biomarkers for a new Nasal Swab Classifier.
Our methods are shown in Slide 11. In order to develop and assess the performance of our preliminary classifiers, we're very fortunate to have access to nasal swab samples collected from our large-scale multicenter perspective AEGIS I and AEGIS II clinical study. We acquired the samples through our 2013 acquisition of Allegro Diagnostics. These studies recruited thousands of patients who are undergoing evaluation for potential lung cancer and who have long-term follow-up. In addition to final adjudicated benign or malignant diagnosis, we have extensive clinical and radiology information, for example, such as age, gender, smoking status, use of inhaling treatments and nodule characteristics found on imaging. Importantly, having this rich repository has enabled us to save several years off of the time it would otherwise take to develop a test like ours.
As shown on Slide 12, we begin by randomly dividing the AEGIS cohort into a training set of 411 nasal samples and an independent test set of 261 samples for our early biomarker discovery. You can see the broad range of clinical features and nodule characteristics that were included in both sets. We extracted RNA from the nasal samples and conducted whole-transcriptome sequencing to measure a quarter million features. We then develop machine learning models that were trained to identify two conditions, benign and malignant cases, using the genomic and clinical features. We developed and evaluated hundreds of models using nested cross-validation, several of the best models were selected and then used to scoring independent test set, meaning the samples were not involved in treating the algorithm. Data for the best performing model which provides us with a firm foundation for developing our future Nasal Swab Classifier were presented earlier today at the CHEST meeting.
Slide 13 gives an overview of our prototype classifier. The model, which is a penalized logistic regression classifier was developed by machine learning on clinical features such as those relevant to smoking history as well as other clinical features and combine them with genomic features extracted through our RNA sequencing pipelines. The foundation of this capability has been built over the last decade at Veracyte.
Turning to Slide 14. When we initially assess the test, we took a common approach of selecting a single cut-off to distinguish benign from malignant cases. We found the test sensitivity for lung cancer with 97% and its specificity was 46%. This means that, among patients whose nodules were actually benign, the genomic test classified over 40% as low risk for cancer with high accuracy so that these patients could be monitored non-invasively. High sensitivity is crucial for a test used at this point, because if physicians are directing patients to monitoring, they would not want to miss cancers. This was our first version of the test development and with what we included in our initial abstract submission to CHEST. In analyzing the data further, we saw that in addition to seeing high performance in classifying samples as low risk, we saw an opportunity similar to that used in our Percepta GSC development to classify samples as high risk, that finding led us to employ a second high cut-off to improve the test specificity or malignancy.
As you can see on Slide 15, we subsequently demonstrated the test performance using two cut-offs. In addition to the previously shown high sensitivity which allows us to call a substantial portion of the true benign patients as low risk while missing very few cancers, we found that among patients whose nodules were malignant, the test classified over 40% as high risk for cancer and high risk specificity of over 94% meaning these patients could be directed to more invasive diagnostic procedures and treatment with a low rate of false positive results. Thus the test achieved success at both ends of the spectrum calling truly benign patients’ low risk with high sensitivity and calling truly malignant patients’ high risk with high specificity. We also observe that the test performance with consistent regardless of lung nodule size or location, as well as cancer subtype or stage giving us confidence that the test can perform in smaller nodules in a diversity of cancers that might be encountered by physicians.
Now let's look at Slide 16. Because the cancer prevalence rate in our AEGIS cohort was high, 78%, we modeled how the test would perform in a population with the cancer prevalence of 25% which is more aligned with the patients on whom it will be used. In this scenario, with the sensitivity of over 95%, the test negative predictive value would be 98% when it identifies patients as low risk with fewer than 5% of truly malignant patients misclassified as low risk and its positive predictive value would be 76% when it identifies patients as high risk for cancer with less than 6% of true benign patients misclassified as high risk.
We're very pleased with the strength of these early data and looks forward to further refining the classifier and preparing it for commercialization. Specific next steps will include analytical work to ensure robustness of the test system and sample collection methods along with additional studies needed for our publication pipeline.
I'll turn the call back to Bonnie.
Thanks, Giulia. To conclude, we are very excited about the progress with our Nasal Swab Classifier and truly think it can be a game changer in the fight against lung cancer. As we have illustrated on Slide 17, we believe our non-invasive Nasal Swab Classifier can guide patient work-up consistent with guidelines to avoid invasive procedures on benign nodules while making in more timely diagnosis and treatment decision on high-risk patients, and we believe this will be a tremendous tool for physicians in standardizing care with objective measures. Additionally, this test will greatly reduce the pool of intermediate risk patients who will follow the course of standard treatments as they do today. We expect to finalize the test over the coming year and commercialize it in early 2021 in the US.
In closing, we are thrilled with where Veracyte is today and where we are heading in all three of our clinical indications. We expect to provide our 2020 guidance when we report our fourth quarter 2019 financial results, but as we look ahead to next year, we expect to deliver revenue excluding biopharma services and genomic test volume growth of over 20% in 2020. It should be another exciting year.
I will now ask Sidney to open up the call for questions.
Thank you. [Operator Instructions] Our first question comes from the line of Sung Ji Nam, BTIG. Your line is open.
Hi, thanks for taking the questions. So maybe starting out with a clarification, I think you mentioned earlier -- early detection versus diagnosis, but this Nasal Swab Classifier when available, you will -- wouldn't require additional work-up post the results. Is that correct, so you can potentially recommend -- okay.
Yes, that's correct. Although with this test you can avoid the multiple steps that sometimes takes place today and we'll be able to get the high risk for cancer patients in for diagnosis immediately on treatment and avoid a work-up on patients that are truly low risk, because our results are near -- you could almost call them benign with the level of performance we have. So by cutting those two pools in half, we are going to be able to move half the patients to the next step they need and that's a pretty exciting result.
Okay, that makes sense. And I haven't had a chance to look at the publication cited here, but could you kind of go over in more detail the intended to use population. Is that based on specific medical guidelines or medical society guidelines that we should be aware of?
The way this works today is, we know there are about 10 million patients at risk that are currently eligible actually to get a low dose CT screening for lung cancer free of charge, that was part of the ACO requirements that came out a couple of years ago. Unfortunately, though many of those patients that are at risk and are eligible for screening do not get in for screening. And what we hear and what our data show is that often that's because of the concern about the work-up required today to make the diagnosis being highly invasive, costly and risky. So the first thing is, we believe we are now going to help improve this pathway of work-up, so that these 10 million patients that are eligible get in for screening. We think that the imaging -- low dose CT screening is actually a really good tool, it's sensitive. The challenge with it is the false positives and that's what nasal risk can greatly improve on.
In addition to the screening patients, there are about 1.6 million patients today that present with nodules just through incidental finding. These patients may be undergoing a work-up for -- before they go into surgery, they might have a CT scan after following a car accident or an X-ray, and when these incidental nodules are found, then they are determined work-up or not work-up. Out of all of those nodules found, about $2 million today in US, there are a number of those nodules that are determined very, very low risk, so they're not even referred for work-up. But about 750,000 of those nodules will be suspicious enough to be referred for work-up. And so when you think about what could happen next with those 750,000 patients, and this is about a 25% prevalent group, so there is roughly 200,000 cancers detected every year in the US, some of these numbers around a little bit. So if our nasal test were to be performed next, we will be able to take -- over 40% of those 550 benign patients, and at that point in time, classify them as low enough risk do not need work-up. At the same time, we will be able to take about 40% of the 200,000 malignance or about 80,000 cancer cases and put those patients into a high risk for cancer bucket so that they move through the process quickly, get diagnosed right away and on treatment. That's the magnitude of what we are going to be able to do here.
In the meantime, we are going to end up with still in intermediate risk group bucket, because we do fantastic on the book and on, but we have the group in the middle that are still intermediate risk and that bucket will be about half when it's estimated to be today. So a tremendous improvement and an objective improvement where when you look at the guidelines and they recommend patients with a low risk being moved to CT follow-up, our nasal classifier low risk call achieve that less than 5% risk of malignancy. So that's excellent that fits right in with the guideline today and obviously with a positive predictive value estimated at over 75% those patients want to get diagnosed and on treatment for lung cancer. So it will have a great impact for patient care and hopefully get more and more patients in just screening for lung cancer.
That's super helpful. And then lastly from me, if I understand this correctly, I think this is the same patient sample cohort that have bronchoscopies swab data as well. So was wondering, it might be too early, but how -- I guess, how does -- how do the results that you presented compared to Percepta performance. I'm not sure if this is the right way to think about it.
Yes. So it's a different intended use population, right, because we at Percepta, we are capturing the patients that have gone through a bronchoscopy work-up about 380,000 patients today undergo bronchoscopy work-up and up to 50%, 60% of those are inconclusive and that is the group we're measuring with Percepta. So it's completely different subset of the patient population and the prevalence is actually a little bit higher. I think when we presented our Percepta data, the prevalence of cancer in the testing population there is about 30% to 35%, I believe, somewhere in that neighborhood. So it's a little bit higher than what this all group will be. And also, many of the suspected cancer patients, but they're defined by more than 60% risk of cancer as assessed clinically would often go on to the surgical biopsy in place of bronchoscopy work-up.
So we are fortunate that when the AEGIS clinical trial was conducted that they had the foresight to gather nasal swab of all these patients so that we could go back to this library of very well curated samples and begin the work in the nose. Of course we obtained all of that when we acquired a lever. I think in the script, we said 2013, it was actually 2014 that we made that acquisition, and Percepta was very far along and already validated. So they were smart to take that to market first and now we're able to turn our attention to what we can do in the nose and we believe there are even more opportunities beyond the one that we are presenting the data today where this test might add value in the global marketplace for improving lung cancer diagnosis and treatment.
Great, that makes a lot of sense. Thank you so much.
Thank you for joining us.
Thank you. Our next question comes from the line of Thomas Flaten with Lake Street Capital Markets. Your line is now open.
Thank you. Congrats guys on the nasal swab data. It looks great. Just -- I'm looking at Slide 17, and I was hoping, Bonnie, if you could help us understand the future of Percepta in this new paradigm. I'm assuming it obviously fits into that intermediate group, but if you could add some color. That would be great.
Yes, I think we would expect that the intermediate risk group would follow the work-up as they would today, which is typically bronchoscopy is very attractive at this point, because it's less invasive and this population has a little bit lower like a moderate risk of malignancy. And the numbers that we were talking about earlier, it will be about 25% to 30% risk of malignancy after the nasal test is performed. But what you also have to keep in mind is with the nasal test intercepting the classification of the patients in advance of work-up, we expect a funnel of patients coming through and nodules being found to grow. So while that intermediate bucket will still be the likely bucket to go on to bronch, we also believe with the 750,000 patients that are moved through the work-up could double or triple as the 10 million patients at risk for lung cancer get screened. So the dynamic will change. The market for both test should actually grow over what it is today and we believe with the combination of our Nasal Swab Classifier, the Percepta GSC, and eventually Percepta Xpression Atlas that we are going to be able to inform on everything from early detection, to diagnosis, to treatment decisions, at the time of diagnosis with the partnership with the pulmonologists who are making these decisions. And we're really excited about the success and the advance that we have made in our pulmonology franchise.
That's great, thank you. Keith, one for you with respect to guidance. There is an increase above and beyond what you had projected coming out of the second quarter in the biopharma revenue from, I think you had $10 million pegged in the second quarter and now we're might be up as much as $6 million on top of that. Can we infer then from that that there is an implied drop in the guidance that's associated with testing revenue?
We've been updating you quarterly. I think this quarter this $2 million of incremental service revenue over where we were last quarter and now is due to advances that we made in Percepta milestones and the nasal outcomes as we come out with this test. So we are relative to the history. I think we're -- probably $1 million in total below in revenue on the classifiers and $1 million up on service revenue in total. So, I mean, it's…
Okay, great.
There is a little bit of a difference, but it's not -- it's not margin [ph] difference.
Okay, thanks for taking my questions.
Thank you.
Thank you. And our next question comes from the line of Puneet Souda with SVB Leerink. Your line is open.
Yes. Hi, Bonnie, Keith and Giulia. So question that I have is, if I could ask on the data, if you could help me understand your rationale for two cut classifiers here in the first place. I know you elaborate a bit on that, but which one on the either end has more value in your view, is it the lower risk or the higher risk. And I'm asking that, because the specificity is lower in the low risk and sensitivity is lower in the high-risk group. Maybe just if you could take a minute and help us educate on those front and, sort of, what I'm trying to get is, even after this classifier, what's the group of patients that we are -- that the assays is still missing and still not part of the ones that are going to bronch. Could you -- if you could help me understand that aspect?
I'll start, and then I'll hand it over to Giulia. But I have to say, when we can take nearly -- for over 40% of true malignant patients and classify them as high risk with very high specificity, which means there is very, very few benign patients going to be put into that cloud. There is not much better improvement to that.
On the low end, it's the same thing. Being able to take 40% of the patients that would be in a pool of intermediate risk patients today that the physician would sort of pick and choose and calculate and try to decide the best next steps. When we can put half those benign patients or over 40% of those patients into a low risk bucket with over 96% sensitivity, we are doing that and not missing hardly any cancers. So I think the first thing that's important to clarify is, we're not missing anything here. We are taking this pool of all these patients with nodules and putting nearly half the high-risk into one class that's obvious what you do next, nearly half into low risk which is obvious what you do next and cutting that intermediate risk pool literally in half. Those patients will follow whatever you would do today with the entire bucket.
Giulia, do you want to talk about the rationalization and rationale for this two class approach? I -- we realize this is kind of cutting edge sort of new, but it's pretty exciting.
Yes, I would say, it's a bit of an unconventional approach, but what we've done is play to the strengths of our data at either ends of the spectrum. So it's very hard to get a test that's both highly sensitive and highly specific. And by adding these two cut-offs, we basically play to the strength of the high sensitivity cut-off at the bottom of the range to call patients low risk with very high sensitivity, and then at the top of the range we're involved with the second cut-off, call those with very high specificity B2B truly malignant with very, very low rates of false negatives on the bottom and false positives up at the top. It's just really playing this to the strength of the test.
Okay, that's very helpful. If I could ask on the pricing of the test, Bonnie, the range here is $800 to $2,500. Could you elaborate on the -- what was the pathway to get to that pricing? What are some of the benchmarks used for that? And a follow up there is, you know in past you have created strong clinical evidence and published that in high impact papers like New England Journal of Medicine and others for Afirma and Percepta. So do you think you have an adequate data here, I mean, adequate data at this point to go to publication and dosage -- and hindback publication or do you need more -- further studies here to bring that clinical evidence to market?
Yes. So it wouldn't be the first time. Back when we developed Afirma, we actually had the first publication that came out that got referenced many times after the test was launched within some of the early work that was done. It was all in all. And it was a very high impact publication even though it was an earlier data set then the final released product. So yes, our sign test and obviously all of our clinical investigators that are part of this journey with us, I'm sure will want to get this data out in publication. I'd be very surprised if this would not be in a high profile journal. In terms of pricing of the test and more details on that, we put the range in the market slide, just to be transparent that we believe pricing will need to be different perhaps in the EU then the US part of the market. And we will need to continue to do some work on the modeling around the true value the test will deliver and then we'll pick a price point that makes sense for the value we're delivering in the market that the test will be sold in, but that reference isn't necessarily because we don't have any idea where we'll price the test. It's more to give you the ranges around how we came up with the market data. But you will hear more of that as we move, that part of what we will be doing over this next year is the market development work, the pre-market and commercialization planning, and tightening down all of those T-cells and we'll keep you all very abreast of that progress.
Okay. And if I could just ask on the test performance. How much of that is related to the genomic evaluation relative to other inputs in the algorithm, the age of the patient, the pack years of smoking and nodule characteristics, et cetera. So what is -- how much is that contributing to the assay?
Yes, it's a really good question. I'll ask Giulia to -- that was in the poster actually that was presented. And we'll try to get this poster, access to the poster with a link at some point after we get back from CHEST on our website as well. But Giulia, why don't you talk a little bit about this versus these clinical calculators?
Sure. So we developed the model to include in addition to gene transcript features from 2016. We actually also have what are called interaction terms of those genes and clinical factors. As part of the AEGIS clinical cohorts, we collected a large number of clinical factors and we use these as features in machine learning. And so our algorithm actually is a combination of genomic features and clinical features. When those classifier is compared to a commonly used clinical risk predictor which doesn't have any genomic features, then it's just some clinical factors. For example, the Gould model is what we have in the poster. We find that there is substantial improvement of our classifier over the performance of the Gould Classifier. On the low sensitivity side as well as on the specificity side. So it increases the number of benigns that are called low risk by 70% over what the Gould Classifier would do by itself and 18% of the malignant to high-risk more than what the Gould Classifier will do.
Thank you, Giulia. Anything else, Puneet?
If I can -- last one for Keith, I don't want to miss in this. The gross margin Keith, expectations for any improvement on that, it's sort of flat lined in the last three quarters?
Yes, well -- yes that's right, 64% to 66% is where we're holding on the margin. We obviously have the loan products are reimbursed at a lower rate than Afirma obviously so that weighs on the margin. So we're trying to hold it at 64% to 66% range for the first couple of years as we go down the managed care journey on those products.
All right, great. Thank you, guys.
Thank you very much for joining us and for the questions.
Thank you. Our next question comes from Paul Knight with Janney Montgomery. Your line is open.
Bonnie, as we start to think about the commercialization of the product you're saying as starting in 2021, I'm assuming that you're kind of thinking that that's the initial days, perhaps the private pay and dependent upon CMS approval, you would need published papers. So I'm assuming you're thinking what CMS approval sometime in 2021 as well and when do you think commercial pay could develop?
Yes, Paul, we know it will take a little bit of time. History would show that it can take a year depending on how quickly you're able to assemble the required evidence and get it accepted into publication, et cetera. But we've done this a few times. So I think that you can expect over the next year, we'll probably get as much of this lined up as we can and try to be as quick post-commercialization to coverage as we can be. And we'll keep you updated as we have any more clarity on that pathway.
And then Keith, regarding this, you're going to have about 8 million or so of service here in the second half. That seems to be above, I think, where you were at the beginning of the year. So what -- within the core, the diagnostic franchise today is that -- it seems like it's a little lower than we started out with the year. Is it pricing? Is it ramp up on test? What would you give us color on regarding that change in the build out of the model?
Well, we've done about 26% growth on revenue year-to-date on our molecular tests. So that's just Afirma, Percepta and Envisia. So that's up about $15 million for the first nine months of the year. Our cytopathology business, which we've always talked about as being a flat to no margin business, but an important factor in terms of Afirma and the market for the commercial team that's down about close to $2 million year-over-year. So that drag from 26% molecular testing down to the 20%. And then on the quarter, we probably had about 3% reduction in that growth rate, because we had in the prior year revenue recognized for test performed in prior periods. We didn't have the advantage of this period. So that's sort of diluted the growth rate. The by and large of Afirma is growing around 17%, 18% in volume and revenue and we're recurring around $2,800 for accrued samples on the test and that's been consistent quarter-over-quarter. So --
That's very close where we predicted Afirma to be for the year. So that…
Overall in genomic volume, 28% over the year, sort of, for the first nine months relative to the prior nine months and 24% this quarter over the prior year quarter. And so if you think about our long test is now 10% of our portfolio, there is probably 6% to 7% growth embedded in the reduction and what we get for that task. So we're getting $1,300 and we should be getting $2,600 to $2,700 on average in those test. We factor in patient pays and all that. We're leaving 6% to 7% of that growth on the table. And over the next two, three years, we really build that volume up and we get to that commercial journey, that will increase the tailwind you saw on Afirma. So eventually our revenue growth rate will exceed our volume growth rate in the early years of the product. Our volume growth rate is higher than revenue growth rate, which we actually think is a very positive indicator for the long-term growth of the business. Does that make sense?
Yes, very helpful.
Okay, great.
Thanks.
Thank you, Paul.
Thank you. And our next question comes from Brian Weinstein with William Blair. Your line is open.
Hey guys, sorry for the background noise. Giulia, for you, can you just go back and describe a little bit more detail of the current standard of care for classification of nodules model. How that used and just make sure that we understand how your product compares the performance in that model which I believe is what this is all based and I didn't see that in the slides, but is a big part of the poster that we can receive today?
Sure. The clinical models that are used and specifically the Gould model uses factors, simple factors such as age and smoking by exposure, never, current or former nodule size and things like that. Our -- and these variables actually, our clinical variables are themselves quite variable and there is a lack of generalizability to these models. So when they're developed in certain cohorts, they don't always generalize to other cohorts. And so there is a lack of standardization, lack of generalizability. What we've done is we've taken clinical factors, we've interacted them with the gene expression terms and the classifier, and we've made the test more standardized and less objectivity. So regardless of what the pre-test risk that nodule may have going into this testing population, we can take those brushing -- nasal brushings from those patients regardless of what the risk is and assign them with this nasal swab test, a highly accurate low risk and high risk assessment of their risk of cancer.
Yes Brian, to answer that, we have a lot of market data going out and asking physicians what they actually do today. And what we have found is that, while these risk calculators are great tools and there can be used multiple different ones by some of the different physicians. What we notice and what the data show is that regardless of the calculated risk, there is a vast lack of standardization in what is done next. So even though they may use the tool and try to assess the pre-work-up risk, in reality, you have many low-risk patients undergoing aggressive surgical biopsy for diagnosis, you have more higher risk patients and actually are moved to watch more follow-up because of the lack of objectivity and standardization across the universal site. So we think this is a really great tool to help, sort of, seven new standard of care of how risk is actually assessed pre-work-up.
Great, thank you for that clarification. And then last one from me is, just moving further upstream with this technology and the opportunity to move to maybe more of a true screening population. Talk about the opportunity there, how you guys are thinking about that and how that might contribute to the -- to the $30 billion overall market opportunity that you guys have referenced?
Yes. Well, I think you're pretty provocative to be able to detect genomic damage in a nasal airway swab and develop this level of accuracy in a very large percent of these patient. So it is pretty provocative and pretty exciting data from that standpoint. If we can do that post nodule detection, there certainly is no reason to imagine that something is magical about that patient with the nodule. So we're definitely interested in ways that we can move further upstream. It would certainly be interesting under the new paradigm and thinking in the pharma world to be able to predict pre-cancer with patients that you could halt progression of disease perhaps, and certainly those are some of the discussions we have with our J&J collaborations.
But I do want to come back to a point that we actually think is pretty important and that is that screening broad populations for lung cancer is in fact one of the posters right next to ours today show that screening -- lung-cancer screening with low dose CT can be very effective, but even today it's expensive, because of the work-up costs associated with what you do once you find those nodules. We believe that it's highly unlikely that broad population screening will ever be done in lung cancer, because there are factors that can be used and that have been used to identify the at-risk population. And when you have an at-risk population, you're really not doing population screening, you're using a tool to get those at-risk populations to get -- detect the cancers that are there early. So some of this is Symantec. But we do believe that low dose CT screening is a great tool. The only problem with it today is the high rate of false positives. If we can solve that problem with the nasal swab, then having an inexpensive low radiation dose screening tool in place that is completely non-invasive is not at all a bad place to start for at-risk lung cancer screening. So we'll play to the strengths of where we think the test is best positioned and then we may look for alternative ways that may be in markets where low dose screening isn't as prevalent. We will have market opportunities there.
And then the last thing I want to clarify is that the market opportunity that we have shown here of roughly 4 billion between US and EU, there is a much larger market opportunity for this exact test position where this one is if you may -- add up the China, Japan, Middle Eastern markets, Latin America, et cetera, et cetera, which we haven't done yet. And as we solidify our commercial plans and think about that more global opportunity, we will bring those numbers forward as well. But we've started with US and EU because we think that it will be important to stake our path for international expansion and we believe this pulmonology franchise is the one to do it with.
Okay. Actually I do you want to sneak one more here. Can you just clarify the comments on 2020? I don't know whether I got that down, but you were talking about some over 20% growth. I just want to make sure I understood what that comment was specifically referring and what it was excluding. So, can you just reiterate that please?
Brian, she is talking about topline genomic and revenue growth of 20% excluding biopharma. As you know, we have a lot of biopharmaceutical service revenue. We've been clear this year that we're not -- the J&J revenue will not -- we have about $9 million left on that to earn out the $20 million and we will come forward in the fourth quarter call and talk about biopharmaceutical service revenue and where we think that's going to play out next year. But on product revenue -- what I'll call product revenue was not, it's still service revenue, but our classifier [indiscernible] revenue just on the 20% top-line genomic and revenue on those.
Great, thank you for that.
All right. Thank you.
Thank you. And our next question comes from Steve Unger with Needham. Your line is open.
Hi, thanks. So you guys plan to commercialize in 2021 with the nasal swab test, that's quite a bit earlier than I think anybody expected. Is the expectation then to do an early access program similar to the other long tests prior to Medicare reimbursement and then go nationwide?
Well, as you might expect, I would probably say that as our commercial plans come together and we have clarity on that process and the timing of it will certainly bring that all forward, we're under evaluation right now and that's what will take us through 2020 to make sure we align all the pieces up to have an excellent execution on that launch. So I'm not trying to avoid the answer. I just think it's a little early yet to make any claim on exactly how we will do it. I think we have lots of options. We're already in the pulm [ph] suite with these doctors. 80% of the pulmonologist [ph] -- Envisia are also using Percepta. So this will be one more way to add a test in the pulmonology suite and build the relationships with our customers. So that will certainly be part of the angle. But in terms of Medicare versus commercial and all of that, probably take us a couple more quarters before we have that information laid out. But thanks for the question, it's exciting.
Got it. And then to expand internationally, particularly in the EU, are you planning the full pulmonology portfolio to expand that internationally or…
We have simply planted at the seed right now that we do believe the global markets are big, it's very complicated right to tap some of the global markets, and we've always believed that we would look toward that planning once we had products and portfolio that made more sense to make that effort on. And so we bring it up today as part of this data, because we believe the Nasal Swab Classifier could definitely be a pivotal part of thinking about that global expansion. We will be very thoughtful I think as we always are and we will give everyone plenty of notice on what that plan in timing and thinking will be, but there's certainly a big opportunity outside the US to ignore when you have a test like this that can have such a great impact on care.
Got it. And then, if I could, just one more. As far as the cost of the product, it's RNA credit, it's on the same platform. What is the -- $800 at the low end of your price range? Is that a price that is commercially viable given sort of the average cost per test that you're running at or could be running out in '20, '21 and '22?
Yes, I mean, I think that we obviously will start where we can be in the upper end of that price range. We believe there is a good viable market for that and we will enlighten you with other plans as those roll forward.
But nothing different as far as costs relative to the Percepta, for example, as far as running the test and processes.
Not right now, no.
Got it, great.
Okay, thank you.
Ladies and gentlemen, this concludes our call today. Thank you for joining us. You may now disconnect. Everyone have a wonderful day.