NASDAQ:POAI Predictive Oncology Q1 2024 Earnings Report $1.06 -0.03 (-2.75%) Closing price 04:00 PM EasternExtended Trading$1.06 -0.01 (-0.47%) As of 07:37 PM Eastern Extended trading is trading that happens on electronic markets outside of regular trading hours. This is a fair market value extended hours price provided by Polygon.io. Learn more. Earnings HistoryForecast Predictive Oncology EPS ResultsActual EPS-$1.04Consensus EPS N/ABeat/MissN/AOne Year Ago EPSN/APredictive Oncology Revenue ResultsActual Revenue$0.42 millionExpected RevenueN/ABeat/MissN/AYoY Revenue GrowthN/APredictive Oncology Announcement DetailsQuarterQ1 2024Date5/14/2024TimeBefore Market OpensConference Call DateWednesday, May 15, 2024Conference Call Time8:30AM ETUpcoming EarningsPredictive Oncology's Q1 2025 earnings is scheduled for Tuesday, May 13, 2025, with a conference call scheduled on Wednesday, May 14, 2025 at 8:30 AM ET. Check back for transcripts, audio, and key financial metrics as they become available.Conference Call ResourcesConference Call AudioConference Call TranscriptPress Release (8-K)Quarterly Report (10-Q)Earnings HistoryCompany ProfilePowered by Predictive Oncology Q1 2024 Earnings Call TranscriptProvided by QuartrMay 15, 2024 ShareLink copied to clipboard.There are 4 speakers on the call. Operator00:00:00Ladies and gentlemen, good morning and thank you for standing by. Welcome to the Predictive Oncology Q1 2024 Earnings Conference Call. At this time, all participants are in a listen only mode. After the speakers' presentation, there will be an opportunity to ask your questions. Please be advised that today's conference is being recorded. Operator00:00:23And I would now like to hand the conference over to your speaker, Mr. Glenn Garman, Investor Relations. Mr. Garman, please go ahead. Speaker 100:00:33Welcome and thank you everyone for dialing into Predictive Oncology First Quarter 2024 Financial Results Call. First, you'll hear from our Chief Executive Officer and Chairman of the Board, Raymond Vannari. Then our Chief Financial Officer, Josh Blacher, will review our financials. Certain matters discussed on this call contain forward looking statements. These forward looking statements reflect our current expectations and projections about future events and are subject to substantial risks, uncertainties and assumptions about our operations and the investments we make. Speaker 100:01:05All statements other than statements of historical facts included in the call regarding our strategy, future operations, future financial position, future revenue and financial performance, projected costs, prospects, plans and objectives of management are forward looking statements. The words anticipate, believe, estimate, expect, intend, may, plan, would, target and similar expressions are intended to identify forward looking statements, although not all forward looking statements contain these identifying words. Our actual future performance may differ materially from that contemplated by the forward looking statements as a result of a variety of factors, including, among other things, factors discussed under the heading Risk Factors in our filings with the SEC. Except as expressly required by law, the company disclaims any intent or obligation to update these forward looking statements. And now I'd like to turn the call over to Raymond Vounari, Chief Executive Officer. Speaker 100:02:05Raymond? Speaker 200:02:07Thank you, Glenn, and good morning, everyone. Thank you for joining today. I would like to begin this morning with an update on a truly groundbreaking study that we recently completed with UPMC Magee Women's Hospital in Pittsburgh. This was a retrospective multi year study to determine if we could leverage our artificial intelligence capabilities to build multi omic machine learning models that would be better than clinical data alone in predicting both short and long term survival outcomes among ovarian cancer patients. Ovarian cancer represents a significant unmet need in oncology with epithelial ovarian cancer being the deadliest of all gynecologic malignancies. Speaker 200:02:56While these cancers are sensitive to frontline chemotherapy in approximately 75% of the cases, these women will ultimately experience disease relapse in an equal percentage, which is incurable. Outside of primary chemotherapy, there is no universal treatment decision path to determine the agent, sequence and timing of the standard of care for chemotherapy agents. The Magee study was designed to identify key features that drive overall survival endpoints. It included data from 235 ovarian cancer patients from 2010 through 2016. A broad array of inputs, including patient data, whole exome sequencing, whole transcriptome sequencing, drug response profile and digital pathology profiles are used to train the 160 models that we included in the study. Speaker 200:03:59We are very pleased to report that we were able to deliver strong predictive models with high levels of accuracy and our machine learning capabilities demonstrated the ability to identify prognostic subgroups within an ovarian cancer patient population. Further validating the significance of these study results, we announced a few weeks ago that an abstract detailing the study has been accepted for presentation at the very prestigious American Society of Clinical Oncology Annual Meeting, better known as ASCO, which is being held May 31 through June 4 in Chicago. The presentation, which will be delivered by Doctor. Brian Orr, gynecologic oncologist at the Hollings Cancer Center, Assistant Professor at the Medical University of South Carolina and Lead Investigator of the study is scheduled for Monday, June 3 at 9 am Central Time. As we stated last quarter, the potential implications for the MEKIA and other clinical decision makers are significant, as these models can be used as an important decision support tool to better tailor therapies to individual patients and positively affect overall survival. Speaker 200:05:17The implications for predictive oncology extend beyond that, however. We believe there are many opportunities to utilize this information for purposes other than clinical utility. The possibility does exist to leverage these data to develop digital pathology applications and new predictive models for other cancer types. Another such application would be to drive the design of more efficient and effective clinical trials. Also, with the ability to identify novel biomarkers that are correlated with survival, we can leverage this information to become more directly involved in drug discovery itself in addition to acting as a partner to others to expedite drug discovery. Speaker 200:06:03This has long been my vision as you know for the company. The successful results of this ovarian cancer study not only clinically validate our ability to successfully predict outcomes, they serve as a sort of proof of concept that supports further work toward that goal. With these compelling results in hand, we are accelerating our drug rescue, drug repurposing and drug combination initiatives and more fully leveraging our artificial intelligence, machine learning and wet lab capabilities to evaluate the drug response of hundreds of diverse patient tumors against hundreds of drugs in a fraction of the time and at a fraction of the loss of valuable samples. Turning now to another recent development. Last month, we announced the collaboration with Fujifilm to co market our EndoPrep sample treatment technology together with Fujifilm's IRISSTAR bacterial endotoxin detection reagent to reduce protein interference and bacterial endotoxin testing of biopharmaceutical products. Speaker 200:07:12For those interested in learning more, the first joint webinar will be held on Wednesday, May 29 at 10 am Eastern Time. Endotoxins also known as lipopolysaccharides, LTS, are components of the outer cell membrane of gram negative bacteria and are released when intact bacteria are disrupted. Sub nanogram levels of endotoxins can trigger immune responses such as inflammation and fever in patients, even leading to systemic shock and death. Endotoxins are highly resistant to sterilization processes and accurate detection and removal of endotoxins in biopharmaceuticals are required before entering animal trials or human clinical trials. Pyrostar is widely considered to be the best detection system for measuring endotoxin levels in biologic products. Speaker 200:08:10When paired with EndoPrep, it can accurately detect residual endotoxins in the presence of interfering glucans and reduce interference of most biologic products with detection assay. In a proof of concept study, we achieved reproducible and accurate measurements of endotoxin in the presence of specific interferon proteins in biologics. The study results indicate that 3 or 4 tested biologics went from not failing in the 50% to 200% detection of challenged endotoxin to falling in the 50% to 200% detection range as required by the FDA for clinical testing. In addition to demonstrating the versatility of our biologics technology, this collaboration will allow predictive oncology to make a significant positive impact on drug safety. We are very pleased to have the opportunity to work with Fujifilm on this project as they are a clear industry leader in the development of antitoxin solutions for injectable pharmaceuticals and biological products. Speaker 200:09:16We also announced recently that we are making meaningful progress with Flugen in the development of a first of its kind intranasal flu vaccine. This project is part of a $6,200,000 Phase 2b grant awarded by the United States Department of Defense. Pursuant to this agreement, we are utilizing our formulations expertise to help Flugen develop its M2SR vaccine that is soluble and stable in a refrigerated state, which is a vital part in the drug development process. Most importantly, this would also address the need for a longer vaccine shelf life to support global distribution, including remote locations. Unlike standard of care food vaccines, M2SR stimulates mucosal, humeral and cellular immunity. Speaker 200:10:11In an unprecedented challenge trial, M2SR demonstrated protection against infection and illness across 7 years of virus drift and M2SR induces a durable antibody response with potential to cover an entire flu season beyond. M2SR also has shown activity as a vaccine vector for other respiratory vaccines and infectious diseases, including a COVID-nineteen flu combination. With our proprietary HSC technology and artificial intelligence platform that efficiently analyzes more than 4,000 different drug formulation combinations using FDA approved excipients. We are able to find the optimal formulation tailored to the final product's application in only 3 to 6 months using as little as 20 micrograms of protein. Our novel design of experiments is a critical component currently being utilized for the development of Flugen's flu vaccine. Speaker 200:11:18This is exactly the kind of innovation that we strive to be part of and we look forward to the continued development of this groundbreaking advancement in the vaccine field. Moreover, as I mentioned in our last update, we have recently announced the development of our latest stem cell technology breakthrough, a novel protein expression method for G protein coupled receptors, GPCRs and other membrane protein classes. This capability supports drug discovery for a variety of diseases, including aggressive cancers. Turning now to other collaborations we have discussed in the past. Let me give you a brief update on Sebergenx as well as the most recent submission to the Center for the Advancement of Science in States. Speaker 200:12:08You may recall that last February we announced the collaboration with SeverGenics to develop the first ever genomics based approach to precision radiation therapy and drug discovery using artificial intelligence. The objective of this collaboration is to leverage and maximize the combined power of predictive oncology's expertise in artificial intelligence and SievertGenics proficiency on biomarker development to identify novel radio protector and radio synthesizer drugs. Over the past year, we have made significant progress, having now evaluated, trained or developed models to predict changes in radio sensitivity for more than 3,000 different drug exposures, as well as using well established gene expression databases. These findings form the basis of an NIH SBIR Phase 1 grant to screen vast libraries of compounds to accelerate the potential development of drugs, drug combinations or repurchase drugs, to sensitize or protect human subjects from the effects of radiation. The significance of identifying these radio sensitizers and radio protectors extends well beyond drug repurposing, however. Speaker 200:13:22Using these models, for example, we would be able to proactively screen workers in the nuclear energy industry and military and in the clinical setting optimize the planning and treatment of patients receiving radiotherapy. So our work with FibroGenics has potentially broad utility across a number of important applications. And in the process, we have been able to expand those datasets, which may be leveraged in several important ways with respect to commercialization. 1st, to screen individuals for radiation sensitivity or resistance to optimize the clinical effect of radiotherapy. Second, to screen for interactions between sensitive or resistant patient tumor samples and therapeutic compounds and third, to identify, combine or develop novel or repurposed radio protective or radio sensitizing drugs. Speaker 200:14:18These are not isolated developments, but synergistic activities that have created new and more interesting opportunities, which has led to collaborations with Merck and Company, OCMS and Redwired Space. And now, I would like to turn this call over to Josh Blacher, our Chief Financial Officer. Josh? Speaker 300:14:39Thank you, Raymond. We concluded the Q1 of 2024 with $5,200,000 in cash and cash equivalents compared to $8,700,000 as of December 31, 2023 and $4,000,000 in stockholders' equity compared to $8,300,000 as of December 31, 2023. In April, we established a new at the market ATM financing vehicle, which will allow us to sell common shares from time to time. Our current dollar value capacity of the ATM is over $3,500,000 Our net loss per share for the Q1 of 2024 was $1.04 per basic and diluted share as compared to $0.86 per basic and diluted share for the Q1 of 2023. The company recorded revenues of $420,000 for the Q1 of 2024 compared to $240,000 for the comparable period in 2023. Speaker 300:15:37Revenues for the quarter ended March 31, 2024 and March 31, 2023 were primarily derived from the company's Indian Operating segment, which contributed revenues of $404,000 $216,000 for the quarters ended March 31, 2024 and 2023 respectively. General and administrative expenses primarily consist of management salaries, professional fees, consulting fees, administrative fees and general office expenses. G and A expenses increased by $291,000 to $2,600,000 in the 3 months ended March 31, 2024 compared to $2,300,000 in the comparable period in 2023. The increase was primarily due to increased professional fees, including audit and consultant fees, as well as increased business taxes, offset by decreased employee compensation, as well as decreased depreciation due to fully depreciated assets. Operating expenses primarily consist of expenses related to product development and prototyping and testing. Speaker 300:16:44Operations expenses increased by $224,000 to $1,100,000 in the 3 months ended March 31, 2024 compared to $879,000 in the comparable period in 2023. The increase was primarily due to increased employee compensation associated with our research and development efforts. Sales and marketing expenses consist of expenses required to market and sell our products, including staff related expenses for individuals performing this work. Sales and marketing expenses increased by $369,000 to $740,000 in 3 months ended March 31, 2024 compared to $370,000 in the comparable period in 2023. The increase was primarily related to severance related to a former executive. Speaker 300:17:33Net cash used in operating activities was $3,400,000 in the Q1 of 2024, roughly flat with cash used of $3,400,000 for the comparable period in 2023. The company incurred net losses of $4,200,000 $3,400,000 for the quarters ended March 31, 2024 and March 31, 2023 respectively. As of March 31, 2024, the company had an accumulated deficit of $172,000,000 as compared to $168,000,000 as of December 31, 2023. That concludes the financial overview. We will now open the call for questions. Speaker 300:18:13Operator? Operator00:18:16Thank you. Ladies and gentlemen, we will now be conducting a question and answer session. Ladies and gentlemen, since there are no questions in the queue, I now have the Speaker 200:19:03Thank you very much, everyone. I just wanted to again say that we are very pleased with our progress with the new developments that we've been able to initiate over the last few months. We appreciate your ongoing support and we look forward to our next update in the next quarter. Thank you very much. Operator00:19:25Thank you. The conference of Predictive Oncology has now concluded. Thank you for your participation. You may now disconnect your lines.Read morePowered by Conference Call Audio Live Call not available Earnings Conference CallPredictive Oncology Q1 202400:00 / 00:00Speed:1x1.25x1.5x2x Earnings DocumentsPress Release(8-K)Quarterly report(10-Q) Predictive Oncology Earnings HeadlinesPredictive Oncology develops new approach to identifying viable abandoned drugsApril 16, 2025 | markets.businessinsider.comRenovaro says Predictive Oncology terminated merger agreementApril 5, 2025 | markets.businessinsider.comTrump’s treachery Trump’s Final Reset Inside the shocking plot to re-engineer America’s financial system…and why you need to move your money now.April 25, 2025 | Porter & Company (Ad)Predictive Oncology Stock Price, Quotes and ForecastsApril 2, 2025 | benzinga.comPredictive Oncology Reports Year-End 2024 Financial Results and Provides Corporate UpdateApril 1, 2025 | globenewswire.comPredictive Oncology (POAI) Uses AI to Slash Drug Discovery Timelines & Boost Cancer ResearchMarch 27, 2025 | insidermonkey.comSee More Predictive Oncology Headlines Get Earnings Announcements in your inboxWant to stay updated on the latest earnings announcements and upcoming reports for companies like Predictive Oncology? Sign up for Earnings360's daily newsletter to receive timely earnings updates on Predictive Oncology and other key companies, straight to your email. Email Address About Predictive OncologyPredictive Oncology (NASDAQ:POAI) operates as a science-driven company on the oncology drug discovery. It provides various solutions for the oncology drug development. The company, through the integration of scientific rigor and machine learning, has developed the ability to advance molecules into medicine by introducing human diversity earlier into the discovery process with the pairing of artificial intelligence and the biobank of approximately 150K tumor samples. It operates through four segments: Helomics, zPREDICTA, Soluble, and Skyline. The Helomics segment provides services that include the application of AI, collaboration projects, and clinical testing. The zPREDICTA segment develops organ-specific disease models that provide 3D reconstruction of human tissues representing each disease state and mimicking drug response for testing of anticancer agents. The Soluble segment provides services using a self-contained automated system that conducts self-interaction chromatography screens using additives and excipients included in protein formulations resulting in soluble and physically stable formulations for biologics. This segment also offers protein stability analysis services; protein solubility kits that allow rapid identification of soluble formulations; and proprietary technologies for bacterial endotoxin detection and removal. The Skyline segment provides STREAMWAY System, a wall-mounted fully automated system, which virtually eliminates exposure to blood, irrigation fluid, and other infectious fluids found in the healthcare environment. The company was formerly known as Precision Therapeutics Inc. and changed its name to Predictive Oncology Inc. in June 2019. Predictive Oncology Inc. was incorporated in 2002 and is headquartered in Eagan, Minnesota.View Predictive Oncology ProfileRead more More Earnings Resources from MarketBeat Earnings Tools Today's Earnings Tomorrow's Earnings Next Week's Earnings Upcoming Earnings Calls Earnings Newsletter Earnings Call Transcripts Earnings Beats & Misses Corporate Guidance Earnings Screener Earnings By Country U.S. Earnings Reports Canadian Earnings Reports U.K. Earnings Reports Latest Articles Market Anticipation Builds: Joby Stock Climbs Ahead of EarningsIs Intuitive Surgical a Buy After Volatile Reaction to Earnings?Seismic Shift at Intel: Massive Layoffs Precede Crucial EarningsRocket Lab Lands New Contract, Builds Momentum Ahead of EarningsAmazon's Earnings Could Fuel a Rapid Breakout Tesla Earnings Miss, But Musk Refocuses and Bulls ReactQualcomm’s Range Narrows Ahead of Earnings as Bulls Step In Upcoming Earnings Cadence Design Systems (4/28/2025)Welltower (4/28/2025)Waste Management (4/28/2025)AstraZeneca (4/29/2025)Booking (4/29/2025)DoorDash (4/29/2025)Honeywell International (4/29/2025)Mondelez International (4/29/2025)PayPal (4/29/2025)Regeneron Pharmaceuticals (4/29/2025) Get 30 Days of MarketBeat All Access for Free Sign up for MarketBeat All Access to gain access to MarketBeat's full suite of research tools. 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There are 4 speakers on the call. Operator00:00:00Ladies and gentlemen, good morning and thank you for standing by. Welcome to the Predictive Oncology Q1 2024 Earnings Conference Call. At this time, all participants are in a listen only mode. After the speakers' presentation, there will be an opportunity to ask your questions. Please be advised that today's conference is being recorded. Operator00:00:23And I would now like to hand the conference over to your speaker, Mr. Glenn Garman, Investor Relations. Mr. Garman, please go ahead. Speaker 100:00:33Welcome and thank you everyone for dialing into Predictive Oncology First Quarter 2024 Financial Results Call. First, you'll hear from our Chief Executive Officer and Chairman of the Board, Raymond Vannari. Then our Chief Financial Officer, Josh Blacher, will review our financials. Certain matters discussed on this call contain forward looking statements. These forward looking statements reflect our current expectations and projections about future events and are subject to substantial risks, uncertainties and assumptions about our operations and the investments we make. Speaker 100:01:05All statements other than statements of historical facts included in the call regarding our strategy, future operations, future financial position, future revenue and financial performance, projected costs, prospects, plans and objectives of management are forward looking statements. The words anticipate, believe, estimate, expect, intend, may, plan, would, target and similar expressions are intended to identify forward looking statements, although not all forward looking statements contain these identifying words. Our actual future performance may differ materially from that contemplated by the forward looking statements as a result of a variety of factors, including, among other things, factors discussed under the heading Risk Factors in our filings with the SEC. Except as expressly required by law, the company disclaims any intent or obligation to update these forward looking statements. And now I'd like to turn the call over to Raymond Vounari, Chief Executive Officer. Speaker 100:02:05Raymond? Speaker 200:02:07Thank you, Glenn, and good morning, everyone. Thank you for joining today. I would like to begin this morning with an update on a truly groundbreaking study that we recently completed with UPMC Magee Women's Hospital in Pittsburgh. This was a retrospective multi year study to determine if we could leverage our artificial intelligence capabilities to build multi omic machine learning models that would be better than clinical data alone in predicting both short and long term survival outcomes among ovarian cancer patients. Ovarian cancer represents a significant unmet need in oncology with epithelial ovarian cancer being the deadliest of all gynecologic malignancies. Speaker 200:02:56While these cancers are sensitive to frontline chemotherapy in approximately 75% of the cases, these women will ultimately experience disease relapse in an equal percentage, which is incurable. Outside of primary chemotherapy, there is no universal treatment decision path to determine the agent, sequence and timing of the standard of care for chemotherapy agents. The Magee study was designed to identify key features that drive overall survival endpoints. It included data from 235 ovarian cancer patients from 2010 through 2016. A broad array of inputs, including patient data, whole exome sequencing, whole transcriptome sequencing, drug response profile and digital pathology profiles are used to train the 160 models that we included in the study. Speaker 200:03:59We are very pleased to report that we were able to deliver strong predictive models with high levels of accuracy and our machine learning capabilities demonstrated the ability to identify prognostic subgroups within an ovarian cancer patient population. Further validating the significance of these study results, we announced a few weeks ago that an abstract detailing the study has been accepted for presentation at the very prestigious American Society of Clinical Oncology Annual Meeting, better known as ASCO, which is being held May 31 through June 4 in Chicago. The presentation, which will be delivered by Doctor. Brian Orr, gynecologic oncologist at the Hollings Cancer Center, Assistant Professor at the Medical University of South Carolina and Lead Investigator of the study is scheduled for Monday, June 3 at 9 am Central Time. As we stated last quarter, the potential implications for the MEKIA and other clinical decision makers are significant, as these models can be used as an important decision support tool to better tailor therapies to individual patients and positively affect overall survival. Speaker 200:05:17The implications for predictive oncology extend beyond that, however. We believe there are many opportunities to utilize this information for purposes other than clinical utility. The possibility does exist to leverage these data to develop digital pathology applications and new predictive models for other cancer types. Another such application would be to drive the design of more efficient and effective clinical trials. Also, with the ability to identify novel biomarkers that are correlated with survival, we can leverage this information to become more directly involved in drug discovery itself in addition to acting as a partner to others to expedite drug discovery. Speaker 200:06:03This has long been my vision as you know for the company. The successful results of this ovarian cancer study not only clinically validate our ability to successfully predict outcomes, they serve as a sort of proof of concept that supports further work toward that goal. With these compelling results in hand, we are accelerating our drug rescue, drug repurposing and drug combination initiatives and more fully leveraging our artificial intelligence, machine learning and wet lab capabilities to evaluate the drug response of hundreds of diverse patient tumors against hundreds of drugs in a fraction of the time and at a fraction of the loss of valuable samples. Turning now to another recent development. Last month, we announced the collaboration with Fujifilm to co market our EndoPrep sample treatment technology together with Fujifilm's IRISSTAR bacterial endotoxin detection reagent to reduce protein interference and bacterial endotoxin testing of biopharmaceutical products. Speaker 200:07:12For those interested in learning more, the first joint webinar will be held on Wednesday, May 29 at 10 am Eastern Time. Endotoxins also known as lipopolysaccharides, LTS, are components of the outer cell membrane of gram negative bacteria and are released when intact bacteria are disrupted. Sub nanogram levels of endotoxins can trigger immune responses such as inflammation and fever in patients, even leading to systemic shock and death. Endotoxins are highly resistant to sterilization processes and accurate detection and removal of endotoxins in biopharmaceuticals are required before entering animal trials or human clinical trials. Pyrostar is widely considered to be the best detection system for measuring endotoxin levels in biologic products. Speaker 200:08:10When paired with EndoPrep, it can accurately detect residual endotoxins in the presence of interfering glucans and reduce interference of most biologic products with detection assay. In a proof of concept study, we achieved reproducible and accurate measurements of endotoxin in the presence of specific interferon proteins in biologics. The study results indicate that 3 or 4 tested biologics went from not failing in the 50% to 200% detection of challenged endotoxin to falling in the 50% to 200% detection range as required by the FDA for clinical testing. In addition to demonstrating the versatility of our biologics technology, this collaboration will allow predictive oncology to make a significant positive impact on drug safety. We are very pleased to have the opportunity to work with Fujifilm on this project as they are a clear industry leader in the development of antitoxin solutions for injectable pharmaceuticals and biological products. Speaker 200:09:16We also announced recently that we are making meaningful progress with Flugen in the development of a first of its kind intranasal flu vaccine. This project is part of a $6,200,000 Phase 2b grant awarded by the United States Department of Defense. Pursuant to this agreement, we are utilizing our formulations expertise to help Flugen develop its M2SR vaccine that is soluble and stable in a refrigerated state, which is a vital part in the drug development process. Most importantly, this would also address the need for a longer vaccine shelf life to support global distribution, including remote locations. Unlike standard of care food vaccines, M2SR stimulates mucosal, humeral and cellular immunity. Speaker 200:10:11In an unprecedented challenge trial, M2SR demonstrated protection against infection and illness across 7 years of virus drift and M2SR induces a durable antibody response with potential to cover an entire flu season beyond. M2SR also has shown activity as a vaccine vector for other respiratory vaccines and infectious diseases, including a COVID-nineteen flu combination. With our proprietary HSC technology and artificial intelligence platform that efficiently analyzes more than 4,000 different drug formulation combinations using FDA approved excipients. We are able to find the optimal formulation tailored to the final product's application in only 3 to 6 months using as little as 20 micrograms of protein. Our novel design of experiments is a critical component currently being utilized for the development of Flugen's flu vaccine. Speaker 200:11:18This is exactly the kind of innovation that we strive to be part of and we look forward to the continued development of this groundbreaking advancement in the vaccine field. Moreover, as I mentioned in our last update, we have recently announced the development of our latest stem cell technology breakthrough, a novel protein expression method for G protein coupled receptors, GPCRs and other membrane protein classes. This capability supports drug discovery for a variety of diseases, including aggressive cancers. Turning now to other collaborations we have discussed in the past. Let me give you a brief update on Sebergenx as well as the most recent submission to the Center for the Advancement of Science in States. Speaker 200:12:08You may recall that last February we announced the collaboration with SeverGenics to develop the first ever genomics based approach to precision radiation therapy and drug discovery using artificial intelligence. The objective of this collaboration is to leverage and maximize the combined power of predictive oncology's expertise in artificial intelligence and SievertGenics proficiency on biomarker development to identify novel radio protector and radio synthesizer drugs. Over the past year, we have made significant progress, having now evaluated, trained or developed models to predict changes in radio sensitivity for more than 3,000 different drug exposures, as well as using well established gene expression databases. These findings form the basis of an NIH SBIR Phase 1 grant to screen vast libraries of compounds to accelerate the potential development of drugs, drug combinations or repurchase drugs, to sensitize or protect human subjects from the effects of radiation. The significance of identifying these radio sensitizers and radio protectors extends well beyond drug repurposing, however. Speaker 200:13:22Using these models, for example, we would be able to proactively screen workers in the nuclear energy industry and military and in the clinical setting optimize the planning and treatment of patients receiving radiotherapy. So our work with FibroGenics has potentially broad utility across a number of important applications. And in the process, we have been able to expand those datasets, which may be leveraged in several important ways with respect to commercialization. 1st, to screen individuals for radiation sensitivity or resistance to optimize the clinical effect of radiotherapy. Second, to screen for interactions between sensitive or resistant patient tumor samples and therapeutic compounds and third, to identify, combine or develop novel or repurposed radio protective or radio sensitizing drugs. Speaker 200:14:18These are not isolated developments, but synergistic activities that have created new and more interesting opportunities, which has led to collaborations with Merck and Company, OCMS and Redwired Space. And now, I would like to turn this call over to Josh Blacher, our Chief Financial Officer. Josh? Speaker 300:14:39Thank you, Raymond. We concluded the Q1 of 2024 with $5,200,000 in cash and cash equivalents compared to $8,700,000 as of December 31, 2023 and $4,000,000 in stockholders' equity compared to $8,300,000 as of December 31, 2023. In April, we established a new at the market ATM financing vehicle, which will allow us to sell common shares from time to time. Our current dollar value capacity of the ATM is over $3,500,000 Our net loss per share for the Q1 of 2024 was $1.04 per basic and diluted share as compared to $0.86 per basic and diluted share for the Q1 of 2023. The company recorded revenues of $420,000 for the Q1 of 2024 compared to $240,000 for the comparable period in 2023. Speaker 300:15:37Revenues for the quarter ended March 31, 2024 and March 31, 2023 were primarily derived from the company's Indian Operating segment, which contributed revenues of $404,000 $216,000 for the quarters ended March 31, 2024 and 2023 respectively. General and administrative expenses primarily consist of management salaries, professional fees, consulting fees, administrative fees and general office expenses. G and A expenses increased by $291,000 to $2,600,000 in the 3 months ended March 31, 2024 compared to $2,300,000 in the comparable period in 2023. The increase was primarily due to increased professional fees, including audit and consultant fees, as well as increased business taxes, offset by decreased employee compensation, as well as decreased depreciation due to fully depreciated assets. Operating expenses primarily consist of expenses related to product development and prototyping and testing. Speaker 300:16:44Operations expenses increased by $224,000 to $1,100,000 in the 3 months ended March 31, 2024 compared to $879,000 in the comparable period in 2023. The increase was primarily due to increased employee compensation associated with our research and development efforts. Sales and marketing expenses consist of expenses required to market and sell our products, including staff related expenses for individuals performing this work. Sales and marketing expenses increased by $369,000 to $740,000 in 3 months ended March 31, 2024 compared to $370,000 in the comparable period in 2023. The increase was primarily related to severance related to a former executive. Speaker 300:17:33Net cash used in operating activities was $3,400,000 in the Q1 of 2024, roughly flat with cash used of $3,400,000 for the comparable period in 2023. The company incurred net losses of $4,200,000 $3,400,000 for the quarters ended March 31, 2024 and March 31, 2023 respectively. As of March 31, 2024, the company had an accumulated deficit of $172,000,000 as compared to $168,000,000 as of December 31, 2023. That concludes the financial overview. We will now open the call for questions. Speaker 300:18:13Operator? Operator00:18:16Thank you. Ladies and gentlemen, we will now be conducting a question and answer session. Ladies and gentlemen, since there are no questions in the queue, I now have the Speaker 200:19:03Thank you very much, everyone. I just wanted to again say that we are very pleased with our progress with the new developments that we've been able to initiate over the last few months. We appreciate your ongoing support and we look forward to our next update in the next quarter. Thank you very much. Operator00:19:25Thank you. The conference of Predictive Oncology has now concluded. Thank you for your participation. You may now disconnect your lines.Read morePowered by