Project

Research Area | Novel Ethical, Secure and Explainable Artificial Intelligence based Digital Medicines and Treatments

We have described validation of novel machine learning architectures for designing faster, safer, and more efficacious digital medicines in our published research findings. This work has  significant impact on the ethical decisions facing patients and their families, and regulatory decisions for the United States Food and Drug Administration (FDA) and European Medical Agencies (EMA) (Project link). For example: Phase 3 clinical outcome trials evaluating new therapies, and vaccines are among the most complex experiments performed in medicine. Around 50% of Phase 3 trials fail (Project link). The US FDA states that a common theme is the difficulty of predicting clinical results in a wide patient base. More importantly, the barriers to this cost healthcare industries, government, and academic research hospitals millions of dollars each year, as well as drive up costs, delay life-saving treatments to patients, and in some cases lead to adverse events . We invent ethical, secure and explainable AI and machine learning systems which learn from diverse and inclusive datasets (Project link, Project link). Our researc… View full description

We have described validation of novel machine learning architectures for designing faster, safer, and more efficacious digital medicines in our published research findings. This work has  significant impact on the ethical decisions facing patients and their families, and regulatory decisions for the United States Food and Drug Administration (FDA) and European Medical Agencies (EMA) (Project link). For example: Phase 3 clinical outcome trials evaluating new therapies, and vaccines are among the most complex experiments performed in medicine. Around 50% of Phase 3 trials fail (Project link). The US FDA states that a common theme is the difficulty of predicting clinical results in a wide patient base. More importantly, the barriers to this cost healthcare industries, government, and academic research hospitals millions of dollars each year, as well as drive up costs, delay life-saving treatments to patients, and in some cases lead to adverse events . We invent ethical, secure and explainable AI and machine learning systems which learn from diverse and inclusive datasets (Project link, Project link). Our research classifies, predicts and enriches novel digital endpoints to benefit patient health, eliminate adverse events, and improve outcomes while managing diseases and pioneers a regulatory path for AI and ML in medical care  (Project link).