FidoCure Study Unlocks Breakthroughs in Deadliest Dog Cancer
PALO ALTO, Calif.--(BUSINESS WIRE)--Researchers at FidoCure and Stanford University have published a peer-reviewed article in Nature Scientific Reports titled, "Real-world evidence couples genomic biomarkers with therapeutic outcomes for canine hemangiosarcoma,' revealing how genomic profiling and targeted therapies can significantly improve patient outcomes for the largest unmet need for dogs: cancer.
The study analyzed data from 508 pet dog patients enrolled in the FidoCure ® Precision Medicine Platform with splenic hemangiosarcoma (HSA) and revealed survival benefits to patients treated with precision therapeutics. These findings highlight the value of using genomic profiling to personalize targeted therapy selection for canine cancer, as well as for genetically analogous human cancers, like human angiosarcoma.
"This study demonstrates the power of precision medicine in oncology, which we have known for decades is key in human patients, and now adds the dimension of cross-species comparisons," said George Demetri, MD, professor of medicine at Dana-Farber Cancer Institute and Harvard Medical School. "We're seeing tangible benefits of tailoring treatments to a dog's specific tumor profile, which could revolutionize how we approach cancer care for our canine companions. This also opens up the future dimensions of how we might learn lessons from our companion animals that could inform our research and therapies for humans with some of the most relentless cancers that afflict both humans and dogs. A big opening is clear for new research and therapy initiatives."
Hemangiosarcoma is the biggest unmet need for dogs, with patients that receive the fatal diagnosis often euthanized shortly after. The study is the first to reveal the relationships between specific genetic mutations, the use of targeted therapies, and survival outcomes for this canine cancer. The findings mark a significant advancement for precision medicine in veterinary oncology and further support the role of genomics in guiding more effective, individualized cancer care to transform one of the most aggressive cancers in dogs.
Key findings include:
The use of targeted therapies drove a 1.8-fold improvement in median survival compared to surgery alone; when combined with chemotherapy, this improvement increased to 2.6-fold.
We can predict survival benefit and treatment response by decoding specific genetic mutations—such as p53 and PIK3CA. In particular, the study found that NRAS mutations mark a distinct and less aggressive subtype of HSA, even after accounting for co-existing, high-risk mutations—suggesting genomic subtyping can play a key role in treatment plans.
This study provides rationale and proof of concept that canine HSA can be used as a preclinical 'model' to investigate the human correlate, angiosarcoma, a rare cancer where clinical trials are limited by difficulty with patient recruitment and mice models are not predictive. Canine trials can inform human drug programs aimed at advancing treatments and biomarkers in this scenario. FidoCure has already played a role in angiosarcoma for humans alongside global pharma Eisai.
"This study represents a major step forward in clinical care for canine hemangiosarcoma," said Christina Lopes, founder and CEO of FidoCure. "By leveraging AI, advanced genomic profiling, and targeted therapies, we are transforming a deadly cancer in dogs into a second chance at life—and gaining valuable insights for rare human cancers too.'
This is FidoCure's 4th peer-reviewed paper in two years and their second major study on hemangiosarcoma. The first HSA study, published in Veterinary and Comparative Oncology, was recognized as one of the Top 10 Most-Cited Articles of 2023 for the leading veterinary publication. Together, these studies provide some of the most comprehensive real-world data available for this cancer type, and they are helping to redefine what's possible in oncology—for both sides of the leash.
ABOUT FIDOCURE
FidoCure is an AI-driven precision oncology company transforming cancer in dogs through novel targeted therapies. FidoCure has created the world's largest canine cancer dataset, with over 2 billion data points collected from patients treated in its network of 1,350 veterinary clinics worldwide. Learn more at www.fidocure.com.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
3 hours ago
- Yahoo
HSS Study at EULAR 2025 Congress Uses an AI Model to Predict Readmissions of Pregnant Women with Lupus Based on Social Determinants of Health
BARCELONA, Spain, June 14, 2025--(BUSINESS WIRE)--Hospital for Special Surgery (HSS) presented a research study at the European Alliance of Associations for Rheumatology (EULAR) Annual Meeting showing that an artificial intelligence (AI)-based model can predict readmissions of pregnant women with lupus by looking at patients' social factors and clinical comorbidities. Systemic lupus erythematosus (SLE), commonly known as lupus, is a chronic autoimmune disease in which the immune system attacks the individual's own healthy tissue, causing pain, inflammation, and eventually damage to various organs. It commonly affects young women, and pregnancy is a particularly vulnerable period for this high-risk population. Although lupus-related medical complications affect pregnancy outcomes, social determinants and economic conditions, known as social determinants of health (SDOH), may also be important in shaping maternal health outcomes. "Pregnant women with lupus have five times higher maternal mortality compared to those without lupus," said Sandhya Shri Kannayiram, MBBS, MD, rheumatology fellow at HSS and principal author of the study. "There is little data on how social factors, including Income, Insurance, housing stability, access to transportation, availability of utilities, and literacy, along with clinical comorbidities, affect pregnancy outcomes in individuals with lupus." To better understand how SDOH impact readmissions for pregnant patients with SLE, the team used ten-year data (from 2011 to 2021) from the National Readmissions Database of the US, encompassing approximately 66,000 hospitalizations in the United States, and counted the number of readmissions within 30 days of discharge during pregnancy and delivery. "We found that approximately 2,500 [pregnant women with lupus] were readmitted to the hospital within 30 days," said Dr. Kannayiram. "We used a supervised 'glass box' machine learning model called the Explainable Boosting Machine (EBM), which helped predict who is likely to return to the hospital within 30 days," said Dr. Kannayiram. She explained that EBM is a form of machine learning with a type of AI that learns from data to make predictions. "It's an AI model that can be trained on the dataset to predict outcomes with transparency and accuracy compared to traditional statistical models," she added. The team specifically examined the major social determinants from the database that may influence readmissions during pregnancy in SLE, including Income and insurance status (public, private, or self-pay). Dr. Kannayiram explained that the results obtained showed patients living in lower-income neighborhoods were nearly twice as likely to be readmitted compared to those from wealthier areas, and those with Medicaid or Medicare insurance were more likely to be readmitted within 30 days. Patients discharged to locations other than home, such as rehabilitation facilities or nursing homes, were also more likely to return. However, they also found unexpected correlations. "We found that the size of hospitals was highly related to readmissions, rather than the location, such as cities or rural areas," said Dr. Kannayiram, with large hospitals being the ones with more readmissions. Additionally, unlike most pregnancy studies, where older mothers are usually at higher risk, this study found that younger women with lupus were more likely to be readmitted. Dr. Kannayiram said that this result may be related to severe lupus in younger individuals since about half of the readmitted patients had Medicare coverage, which may suggest a high prevalence of disability or kidney disease within that younger population. By using the predictive AI model, the team also discovered that income and insurance status were among the top five predictors of 30-day readmission during pregnancy and delivery-related hospitalizations, explained Bella Mehta, MBBS, MS, MD, rheumatologist at HSS and lead author of the study. She noted that these results could inform targeted interventions, such as policy actions to advocate for improved Medicaid and Medicare coverage, as well as post-discharge care coordination. "Integrating SDOH screening into prenatal care for SLE patients, and incorporating a multidisciplinary team of social workers, could reduce preventable readmissions and improve maternal outcomes," added Dr. Mehta. According to Dr. Mehta, in future studies, the team plans to analyze in detail how individual-level social factors, such as housing instability, food insecurity, education, mental health, transportation access, and patient demographics, interact with clinical comorbidities to determine pregnancy outcomes for women with SLE. "This study underscores the vital intersection between clinical care and structural inequality," said Dr. Mehta. "The lupus community and broader maternal health initiatives must not only consider disease management but also address the social factors that influence outcomes." Poster details Title: Predictors of 30-Day Readmissions in Pregnant Patients with Systemic Lupus Erythematosus: The Role of Social Determinants of HealthAuthors: Sandhya Shri Kannayiram, Yiyuan Wu, Lisa Sammaritano, Michael Lockshin, Rich Caruna, D. Ware Branch, Jane E. Salmon, Bella n°: 2325Presentation: June 14th, 2025. 10:00 AM CEST About HSS HSS is the world's leading academic medical center focused on musculoskeletal health. At its core is Hospital for Special Surgery, nationally ranked No. 1 in orthopedics (for the 15th consecutive year), No. 3 in rheumatology by U.S. News & World Report (2024-2025), and the best pediatric orthopedic hospital in NY, NJ and CT by U.S. News & World Report "Best Children's Hospitals" list (2024-2025). In a survey of medical professionals in more than 20 countries by Newsweek, HSS is ranked world #1 in orthopedics for a fifth consecutive year (2025). Founded in 1863, the Hospital has the lowest readmission rates in the nation for orthopedics, and among the lowest infection and complication rates. HSS was the first in New York State to receive Magnet Recognition for Excellence in Nursing Service from the American Nurses Credentialing Center five consecutive times. An affiliate of Weill Cornell Medical College, HSS has a main campus in New York City and facilities in New Jersey, Connecticut and in the Long Island and Westchester County regions of New York State, as well as in Florida. In addition to patient care, HSS leads the field in research, innovation and education. The HSS Research Institute comprises 20 laboratories and 300 staff members focused on leading the advancement of musculoskeletal health through prevention of degeneration, tissue repair and tissue regeneration. In addition, more than 200 HSS clinical investigators are working to improve patient outcomes through better ways to prevent, diagnose, and treat orthopedic, rheumatic and musculoskeletal diseases. The HSS Innovation Institute works to realize the potential of new drugs, therapeutics and devices. The HSS Education Institute is a trusted leader in advancing musculoskeletal knowledge and research for physicians, nurses, allied health professionals, academic trainees, and consumers in more than 165 countries. The institution is collaborating with medical centers and other organizations to advance the quality and value of musculoskeletal care and to make world-class HSS care more widely accessible nationally and internationally. View source version on Contacts Tracy Hickenbottom/Rachael Rennich212-606-1197mediarelations@ Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
7 hours ago
- Yahoo
HSS Study at EULAR 2025 Congress Uses an AI Model to Predict Readmissions of Pregnant Women with Lupus Based on Social Determinants of Health
BARCELONA, Spain, June 14, 2025--(BUSINESS WIRE)--Hospital for Special Surgery (HSS) presented a research study at the European Alliance of Associations for Rheumatology (EULAR) Annual Meeting showing that an artificial intelligence (AI)-based model can predict readmissions of pregnant women with lupus by looking at patients' social factors and clinical comorbidities. Systemic lupus erythematosus (SLE), commonly known as lupus, is a chronic autoimmune disease in which the immune system attacks the individual's own healthy tissue, causing pain, inflammation, and eventually damage to various organs. It commonly affects young women, and pregnancy is a particularly vulnerable period for this high-risk population. Although lupus-related medical complications affect pregnancy outcomes, social determinants and economic conditions, known as social determinants of health (SDOH), may also be important in shaping maternal health outcomes. "Pregnant women with lupus have five times higher maternal mortality compared to those without lupus," said Sandhya Shri Kannayiram, MBBS, MD, rheumatology fellow at HSS and principal author of the study. "There is little data on how social factors, including Income, Insurance, housing stability, access to transportation, availability of utilities, and literacy, along with clinical comorbidities, affect pregnancy outcomes in individuals with lupus." To better understand how SDOH impact readmissions for pregnant patients with SLE, the team used ten-year data (from 2011 to 2021) from the National Readmissions Database of the US, encompassing approximately 66,000 hospitalizations in the United States, and counted the number of readmissions within 30 days of discharge during pregnancy and delivery. "We found that approximately 2,500 [pregnant women with lupus] were readmitted to the hospital within 30 days," said Dr. Kannayiram. "We used a supervised 'glass box' machine learning model called the Explainable Boosting Machine (EBM), which helped predict who is likely to return to the hospital within 30 days," said Dr. Kannayiram. She explained that EBM is a form of machine learning with a type of AI that learns from data to make predictions. "It's an AI model that can be trained on the dataset to predict outcomes with transparency and accuracy compared to traditional statistical models," she added. The team specifically examined the major social determinants from the database that may influence readmissions during pregnancy in SLE, including Income and insurance status (public, private, or self-pay). Dr. Kannayiram explained that the results obtained showed patients living in lower-income neighborhoods were nearly twice as likely to be readmitted compared to those from wealthier areas, and those with Medicaid or Medicare insurance were more likely to be readmitted within 30 days. Patients discharged to locations other than home, such as rehabilitation facilities or nursing homes, were also more likely to return. However, they also found unexpected correlations. "We found that the size of hospitals was highly related to readmissions, rather than the location, such as cities or rural areas," said Dr. Kannayiram, with large hospitals being the ones with more readmissions. Additionally, unlike most pregnancy studies, where older mothers are usually at higher risk, this study found that younger women with lupus were more likely to be readmitted. Dr. Kannayiram said that this result may be related to severe lupus in younger individuals since about half of the readmitted patients had Medicare coverage, which may suggest a high prevalence of disability or kidney disease within that younger population. By using the predictive AI model, the team also discovered that income and insurance status were among the top five predictors of 30-day readmission during pregnancy and delivery-related hospitalizations, explained Bella Mehta, MBBS, MS, MD, rheumatologist at HSS and lead author of the study. She noted that these results could inform targeted interventions, such as policy actions to advocate for improved Medicaid and Medicare coverage, as well as post-discharge care coordination. "Integrating SDOH screening into prenatal care for SLE patients, and incorporating a multidisciplinary team of social workers, could reduce preventable readmissions and improve maternal outcomes," added Dr. Mehta. According to Dr. Mehta, in future studies, the team plans to analyze in detail how individual-level social factors, such as housing instability, food insecurity, education, mental health, transportation access, and patient demographics, interact with clinical comorbidities to determine pregnancy outcomes for women with SLE. "This study underscores the vital intersection between clinical care and structural inequality," said Dr. Mehta. "The lupus community and broader maternal health initiatives must not only consider disease management but also address the social factors that influence outcomes." Poster details Title: Predictors of 30-Day Readmissions in Pregnant Patients with Systemic Lupus Erythematosus: The Role of Social Determinants of HealthAuthors: Sandhya Shri Kannayiram, Yiyuan Wu, Lisa Sammaritano, Michael Lockshin, Rich Caruna, D. Ware Branch, Jane E. Salmon, Bella n°: 2325Presentation: June 14th, 2025. 10:00 AM CEST About HSS HSS is the world's leading academic medical center focused on musculoskeletal health. At its core is Hospital for Special Surgery, nationally ranked No. 1 in orthopedics (for the 15th consecutive year), No. 3 in rheumatology by U.S. News & World Report (2024-2025), and the best pediatric orthopedic hospital in NY, NJ and CT by U.S. News & World Report "Best Children's Hospitals" list (2024-2025). In a survey of medical professionals in more than 20 countries by Newsweek, HSS is ranked world #1 in orthopedics for a fifth consecutive year (2025). Founded in 1863, the Hospital has the lowest readmission rates in the nation for orthopedics, and among the lowest infection and complication rates. HSS was the first in New York State to receive Magnet Recognition for Excellence in Nursing Service from the American Nurses Credentialing Center five consecutive times. An affiliate of Weill Cornell Medical College, HSS has a main campus in New York City and facilities in New Jersey, Connecticut and in the Long Island and Westchester County regions of New York State, as well as in Florida. In addition to patient care, HSS leads the field in research, innovation and education. The HSS Research Institute comprises 20 laboratories and 300 staff members focused on leading the advancement of musculoskeletal health through prevention of degeneration, tissue repair and tissue regeneration. In addition, more than 200 HSS clinical investigators are working to improve patient outcomes through better ways to prevent, diagnose, and treat orthopedic, rheumatic and musculoskeletal diseases. The HSS Innovation Institute works to realize the potential of new drugs, therapeutics and devices. The HSS Education Institute is a trusted leader in advancing musculoskeletal knowledge and research for physicians, nurses, allied health professionals, academic trainees, and consumers in more than 165 countries. The institution is collaborating with medical centers and other organizations to advance the quality and value of musculoskeletal care and to make world-class HSS care more widely accessible nationally and internationally. View source version on Contacts Tracy Hickenbottom/Rachael Rennich212-606-1197mediarelations@ Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Business Wire
7 hours ago
- Business Wire
HSS Study at EULAR 2025 Congress Uses an AI Model to Predict Readmissions of Pregnant Women with Lupus Based on Social Determinants of Health
BARCELONA, Spain--(BUSINESS WIRE)-- Hospital for Special Surgery (HSS) presented a research study at the European Alliance of Associations for Rheumatology (EULAR) Annual Meeting showing that an artificial intelligence (AI)-based model can predict readmissions of pregnant women with lupus by looking at patients' social factors and clinical comorbidities. Systemic lupus erythematosus (SLE), commonly known as lupus, is a chronic autoimmune disease in which the immune system attacks the individual's own healthy tissue, causing pain, inflammation, and eventually damage to various organs. It commonly affects young women, and pregnancy is a particularly vulnerable period for this high-risk population. Although lupus-related medical complications affect pregnancy outcomes, social determinants and economic conditions, known as social determinants of health (SDOH), may also be important in shaping maternal health outcomes. 'Pregnant women with lupus have five times higher maternal mortality compared to those without lupus,' said Sandhya Shri Kannayiram, MBBS, MD, rheumatology fellow at HSS and principal author of the study. 'There is little data on how social factors, including Income, Insurance, housing stability, access to transportation, availability of utilities, and literacy, along with clinical comorbidities, affect pregnancy outcomes in individuals with lupus.' To better understand how SDOH impact readmissions for pregnant patients with SLE, the team used ten-year data (from 2011 to 2021) from the National Readmissions Database of the US, encompassing approximately 66,000 hospitalizations in the United States, and counted the number of readmissions within 30 days of discharge during pregnancy and delivery. 'We found that approximately 2,500 [pregnant women with lupus] were readmitted to the hospital within 30 days,' said Dr. Kannayiram. 'We used a supervised 'glass box' machine learning model called the Explainable Boosting Machine (EBM), which helped predict who is likely to return to the hospital within 30 days,' said Dr. Kannayiram. She explained that EBM is a form of machine learning with a type of AI that learns from data to make predictions. 'It's an AI model that can be trained on the dataset to predict outcomes with transparency and accuracy compared to traditional statistical models,' she added. The team specifically examined the major social determinants from the database that may influence readmissions during pregnancy in SLE, including Income and insurance status (public, private, or self-pay). Dr. Kannayiram explained that the results obtained showed patients living in lower-income neighborhoods were nearly twice as likely to be readmitted compared to those from wealthier areas, and those with Medicaid or Medicare insurance were more likely to be readmitted within 30 days. Patients discharged to locations other than home, such as rehabilitation facilities or nursing homes, were also more likely to return. However, they also found unexpected correlations. 'We found that the size of hospitals was highly related to readmissions, rather than the location, such as cities or rural areas,' said Dr. Kannayiram, with large hospitals being the ones with more readmissions. Additionally, unlike most pregnancy studies, where older mothers are usually at higher risk, this study found that younger women with lupus were more likely to be readmitted. Dr. Kannayiram said that this result may be related to severe lupus in younger individuals since about half of the readmitted patients had Medicare coverage, which may suggest a high prevalence of disability or kidney disease within that younger population. By using the predictive AI model, the team also discovered that income and insurance status were among the top five predictors of 30-day readmission during pregnancy and delivery-related hospitalizations, explained Bella Mehta, MBBS, MS, MD, rheumatologist at HSS and lead author of the study. She noted that these results could inform targeted interventions, such as policy actions to advocate for improved Medicaid and Medicare coverage, as well as post-discharge care coordination. 'Integrating SDOH screening into prenatal care for SLE patients, and incorporating a multidisciplinary team of social workers, could reduce preventable readmissions and improve maternal outcomes,' added Dr. Mehta. According to Dr. Mehta, in future studies, the team plans to analyze in detail how individual-level social factors, such as housing instability, food insecurity, education, mental health, transportation access, and patient demographics, interact with clinical comorbidities to determine pregnancy outcomes for women with SLE. 'This study underscores the vital intersection between clinical care and structural inequality,' said Dr. Mehta. 'The lupus community and broader maternal health initiatives must not only consider disease management but also address the social factors that influence outcomes.' Poster details Title: Predictors of 30-Day Readmissions in Pregnant Patients with Systemic Lupus Erythematosus: The Role of Social Determinants of Health Authors: Sandhya Shri Kannayiram, Yiyuan Wu, Lisa Sammaritano, Michael Lockshin, Rich Caruna, D. Ware Branch, Jane E. Salmon, Bella Mehta. Abstract n°: 2325 Presentation: June 14 th About HSS HSS is the world's leading academic medical center focused on musculoskeletal health. At its core is Hospital for Special Surgery, nationally ranked No. 1 in orthopedics (for the 15th consecutive year), No. 3 in rheumatology by U.S. News & World Report (2024-2025), and the best pediatric orthopedic hospital in NY, NJ and CT by U.S. News & World Report 'Best Children's Hospitals' list (2024-2025). In a survey of medical professionals in more than 20 countries by Newsweek, HSS is ranked world #1 in orthopedics for a fifth consecutive year (2025). Founded in 1863, the Hospital has the lowest readmission rates in the nation for orthopedics, and among the lowest infection and complication rates. HSS was the first in New York State to receive Magnet Recognition for Excellence in Nursing Service from the American Nurses Credentialing Center five consecutive times. An affiliate of Weill Cornell Medical College, HSS has a main campus in New York City and facilities in New Jersey, Connecticut and in the Long Island and Westchester County regions of New York State, as well as in Florida. In addition to patient care, HSS leads the field in research, innovation and education. The HSS Research Institute comprises 20 laboratories and 300 staff members focused on leading the advancement of musculoskeletal health through prevention of degeneration, tissue repair and tissue regeneration. In addition, more than 200 HSS clinical investigators are working to improve patient outcomes through better ways to prevent, diagnose, and treat orthopedic, rheumatic and musculoskeletal diseases. The HSS Innovation Institute works to realize the potential of new drugs, therapeutics and devices. The HSS Education Institute is a trusted leader in advancing musculoskeletal knowledge and research for physicians, nurses, allied health professionals, academic trainees, and consumers in more than 165 countries. The institution is collaborating with medical centers and other organizations to advance the quality and value of musculoskeletal care and to make world-class HSS care more widely accessible nationally and internationally.
