NEW YORK (PRWEB) May 17, 2018
On May 16, 2018, the publication of the ASCO Abstract book, included multiple accepted abstracts from Precision Health AI focused on Real World Data driven analyses of the current state of cancer treatment, as well as specific AI-driven predictive models which identify optimal treatments and predict the potential for adverse events. Included in these Abstracts is a study abstract entitled "Artificial Intelligence Methods to Predict Chemotherapy-Induced Neutropenia in Breast Cancer Patients". The results from this study, which will be presented at the Annual ASCO meeting in Chicago June 1-5 2018, represent a major advancement in the prediction of a serious and common drug side effect - Chemotherapy Induced Neutropenia (CIN).
1 in 5 Chemotherapy patients experience neutropenia, or a reduction in immune function, as a side effect, which causes a surge in mortality of 20-30%. Development of neutropenia is often idiosyncratic and was previously unpredictable; yet not only does it lead to reduced quality of life - in some cases, it causes actual mortality. PHAI's OncoAdverse AI module predicts CIN with an AUCROC in some cases exceeding 0.9, exceeding the best published rates by >50%.
Other key findings from accepted Precision Health AI abstracts include:
- PHAI AI Models are not only highly predictive but represent true "Precision Medicine". In addition to high predictive value for Chemotherapy Induced Neutropenia, PHAI AI modules, available in the Eureka HealthAI Platform, demonstrated an expansion in predictive factors enabling a much more patient specific recommendation than existing models.
- Despite the emergence of targeted therapy, both testing and appropriate use of therapy remain inconsistent. PHAI found oncologist adoption of current rates of EGFR testing remain relatively low despite the emergence of multiple targeted therapies, and even when EGFR testing was completed, it did not always lead to the use of the appropriate targeted therapy.
- Use of Immuno-oncology(IO) Drugs shows wide variety of combinations and treatment regimens. Variation in care continues to occur in the use of IO therapies, and complex guidelines and combination therapies appear to be leading to inconsistent use of therapy by physicians.
"We believe findings presented in these abstracts represent the tip of the spear for AI-driven clinical decision making in oncology," said Dr. Brigham Hyde, CEO of Precision Health AI. "By combining the power of the Precision Health AI Definitive Oncology Dataset with focused oncology-specific AI development, Precision Health AI is enabling the System of Actionable Intelligence for Oncology."
Precision Health AI's new EurekaHealthTM AI Oncology platform is based on the company's vast longitudinal data set including its recent exclusive data partnership with ASCO and CancerLinQ, combined with other data partners in EMR and genomics. Together these datasets provide Precision Health AI unprecedented access to the largest clinical oncology data set available in the industry. This proprietary dataset enables more granularity than traditional research and predictive comparisons of outcomes in use today, which ultimately will accelerate data-driven insights for Life Sciences companies.
To get more information on these abstracts and see a demo of Precision Health AI's platform, visit booth #25109 at ASCO.
The approved abstracts as well as poster presentation hours can be viewed here:
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About Precision Health AI
Precision Health AI is developing the leading artificial intelligence (AI) platform for oncology built on the largest longitudinal clinical oncology dataset to enable the practice of precision medicine for better cancer patient care, getting the right treatment to the right patient at the right time. Insights from Precision Health AI will accelerate cancer-related drug development, trials and real-world evidence for the benefit of the cancer care ecosystem of oncologists, pharmaceutical companies, payers and patients. To learn more, visit http://www.precisionhealth.ai.