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Industry Landscape
The HealthTech AI Oncology industry is rapidly expanding, driven by the need for efficient clinical trial recruitment, real-world data utilization, and personalized patient care. AI and ML are transforming how oncological data is processed, enabling faster insights and improved patient outcomes. Focus on diversity and inclusion in trials is also a key driver.
Total Assets Under Management (AUM)
Healthcare Artificial Intelligence Market Size in United States
~USD 22.5 billion (2023)
(37.5% CAGR)
The market is driven by; - Increasing adoption of AI in drug discovery and development. - Rising demand for personalized medicine. - Growth of big data in healthcare.
Total Addressable Market
100 billion USD
Market Growth Stage
Pace of Market Growth
Emerging Technologies
Federated Learning for RWD
Federated learning allows AI models to be trained on decentralized datasets, such as those held by multiple hospitals, without sharing raw patient data, significantly enhancing data privacy and enabling broader real-world data insights.
Explainable AI (XAI) in Clinical Decision Support
XAI provides transparency into AI's decision-making process, crucial for building trust and facilitating adoption by clinicians, especially in high-stakes areas like oncology treatment recommendations and trial eligibility.
Digital Twins for Patient Pathways
Creating virtual models of individual patients based on their medical data can enable personalized treatment simulations and prediction of therapy responses, optimizing patient care and clinical trial design.
Impactful Policy Frameworks
21st Century Cures Act (2016) - Information Blocking Rule (2020/2021)
This rule, implemented under the 21st Century Cures Act, generally prohibits healthcare providers, IT developers, and health information exchanges from engaging in practices that are likely to interfere with access, exchange, or use of electronic health information (EHI).
This policy mandates greater interoperability and access to EHI, directly benefiting Realyze Intelligence by making it easier to access and integrate with diverse EHR systems for data abstraction and analysis.
HIPAA Privacy Rule and AI (Ongoing interpretation)
While not a new policy, the application and interpretation of the HIPAA Privacy Rule regarding the use of protected health information (PHI) in AI and machine learning models are constantly evolving, particularly concerning de-identification and data sharing.
Strict adherence to HIPAA regulations and evolving interpretations is crucial for Realyze Intelligence to maintain data security and patient trust, impacting their data governance and model development processes.
FDA's AI/ML-Based Software as a Medical Device (SaMD) Action Plan (2021)
The FDA's action plan outlines a framework for the regulation of AI/ML-based SaMD, focusing on a 'total product lifecycle' approach that allows for algorithm modifications while ensuring safety and effectiveness.
As Realyze Intelligence's solutions could be classified as SaMD, this policy provides a clearer regulatory pathway for their AI-powered tools, potentially streamlining market entry and ensuring compliance for clinical applications.
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