Renovaro Secures Key U.S. Patent to Strengthen AI-Driven Drug Discovery and Diagnostics Platform

Rhea-AI Summary

Renovaro (NASDAQ: RENB) has secured a new USPTO patent for its AI-driven drug discovery and diagnostics platform. The patent, titled 'Methods, Systems, and Frameworks for Unbiased Data in Drug Discovery Predictions,' enhances the company's ability to integrate and harmonize diverse biomedical data sources for predictive modeling. This builds upon their previous patent from July 2022, strengthening their IP portfolio in AI and machine learning for healthcare applications. The technology enables real-time, reproducible predictive analytics at scale across distributed computing environments, addressing key challenges in pharmaceutical R&D and clinical practice. The platform's capabilities span rare disease research, clinical trials, and personalized medicine, positioning Renovaro for commercial partnerships and licensing opportunities in the life sciences sector.

Positive

• Secured new USPTO patent strengthening AI and machine learning IP portfolio
• Technology enables integration of diverse biomedical data sources for predictive modeling
• Platform supports distributed computing for real-time, scalable analytics
• Creates opportunities for commercial partnerships and licensing in life sciences

Negative

• None.

Insights

Biotech Patent Specialist

Renovaro's new patent strengthens IP portfolio, enhancing competitive position in AI-driven drug discovery with significant long-term value potential.

Renovaro's recently allowed patent application represents a meaningful enhancement to their intellectual property portfolio in the AI-driven drug discovery space. This patent specifically addresses one of the most challenging aspects of computational drug discovery: the integration and harmonization of heterogeneous biomedical data sources. The technology enables standardization of diverse data types—genomics, electronic health records, imaging, and clinical trial data—into unified frameworks suitable for predictive modeling.

The patent builds upon their existing IP (US 11,379,757) which covers machine learning pipeline optimization. What makes this new patent particularly valuable is its focus on distributed computing environments that enable real-time, reproducible analytics at scale—a crucial capability as datasets in drug discovery continue to grow exponentially in size and complexity.

From a competitive standpoint, this patent could provide Renovaro with significant differentiation in the increasingly crowded AI drug discovery market. The technology addresses a fundamental bottleneck in the industry: the siloed nature of biomedical data and the difficulty in creating standardized datasets for AI model training. Companies that can effectively solve this data harmonization challenge typically achieve higher success rates in their computational predictions, potentially leading to more efficient drug development processes.

This patent appears strategically aligned with Renovaro's business model, potentially enabling multiple revenue streams through direct application in their drug discovery programs and possible licensing opportunities to pharmaceutical partners seeking to enhance their own AI capabilities.

Expanded IP Portfolio Enhances Data Harmonization and Predictive Analytics Capabilities for High-Growth Biomedical Markets

LOS ANGELES, June 03, 2025 (GLOBE NEWSWIRE) -- Renovaro Inc. (NASDAQ: RENB), a clinical-stage precision medicine company, today announced that its subsidiary BioSymetrics has received a Notice of Allowance from the United States Patent and Trademark Office (USPTO) for a new patent application titled “Methods, Systems, and Frameworks for Unbiased Data in Drug Discovery Predictions” (Application No. 18/058,752).

This patent strengthens Renovaro’s AI and machine learning intellectual property portfolio by protecting novel methods for integrating and harmonizing diverse biomedical data sources—such as genomics, electronic health records, imaging, and clinical trial data—into a standardized framework for predictive modeling.

“This patent is a strategic milestone for Renovaro,” said David Weinstein, CEO of Renovaro. “Together with our previously granted patent, it forms the technological foundation of a scalable, end-to-end platform for AI-powered drug discovery and diagnostics and strengthens our position in the fast-growing market for data-driven therapeutics and clinical insights.”

Key Drivers for Renovaro:

• Expands Foundational IP: Builds on core patent (US 11,379,757), granted in July 2022, which protects machine learning pipeline optimization through advanced feature selection and model tuning.
• Addresses Real-World Challenges: Tackles integration of siloed and heterogeneous data—an unmet need in pharmaceutical R&D and clinical practice.
• Enhances Commercial Potential: Enables scalable, distributed computing for biomedical analytics across use cases in rare disease, clinical trials, and personalized medicine.
• Supports Revenue Growth Strategy: Protects Renovaro’s differentiated technology approach, critical for commercial partnerships, licensing opportunities, and platform deployment in life sciences and healthcare.

The new patent introduces methods that operate across distributed and parallel computing environments, allowing for real-time, reproducible predictive analytics at scale. This infrastructure is vital as the biopharma industry increases reliance on AI to improve efficiency, reduce costs, and accelerate time-to-market for new therapies.

This patent allowance reinforces Renovaro’s commitment to building category-defining technology platforms that drive value for patients, partners, and shareholders alike.

About Renovaro Inc.

Renovaro https://renovarogroup.com/ aims to accelerate precision and personalized medicine for longevity powered by mutually reinforcing AI and biotechnology platforms for early diagnosis, better-targeted treatments, and drug discovery. Renovaro Inc. includes RenovaroBio with its advanced cell-gene immunotherapy company and RenovaroCube that is leveraging AI for multi-omic diagnostics and drug development, and BioSymetrics which specializes in contingent AI for precision neurology. For more information, visit www.renovarogroup.com.

Forward-Looking Statements

This release contains forward-looking statements, including those relating to the pending litigation and the proposed merger. These statements involve risks and uncertainties and are subject to change based on future developments. Renovaro undertakes no obligation to update any forward-looking statements except as required by law.

Investor Relations

Chris Tyson
Executive Vice President
MZ Group - MZ North America
949-491-8235
RENB@mzgroup.us
www.mzgroup.us

For media inquiries, please contact:

karen@renovarocube.com

FAQ

What is the significance of Renovaro's (RENB) new patent for drug discovery?

The patent strengthens Renovaro's AI platform by protecting methods for integrating diverse biomedical data sources into a standardized framework for predictive modeling, enabling more efficient drug discovery and diagnostics.

How does RENB's new patent complement their existing technology?

The new patent builds on their July 2022 core patent for machine learning pipeline optimization, expanding their capabilities in data harmonization and distributed computing for biomedical analytics.

What markets will Renovaro's (RENB) patented technology serve?

The technology will serve markets in rare disease research, clinical trials, and personalized medicine, with applications across pharmaceutical R&D and clinical practice.

How will the new patent impact Renovaro's business strategy?

The patent enhances Renovaro's commercial potential by protecting their technology approach, enabling partnerships, licensing opportunities, and platform deployment in life sciences and healthcare.

What specific problems does Renovaro's new patented technology solve?

The technology addresses the challenge of integrating siloed and heterogeneous biomedical data, enabling real-time, reproducible predictive analytics at scale across distributed computing environments.