Mana.bio Presents Broad Improvements to Systemic Lipid Nanoparticle Tolerability by Leveraging a Novel AI-Driven Safety Model

• Mana’s lung-targeting AI model initially yielded a highly-specific, lung-tropic LNP
• Iterative in-silico / in-vitro cycles improved in-vivo potency by ~100X in 3-months 
• Data seamlessly translated from cell culture to mice to primates
• ML-safety prediction model broadly improved tolerability while maintaining lung potency and specificity

TEL AVIV, Israel, Dec. 11, 2024 /PRNewswire/ — Mana.bio, a seed-stage biotech company pioneering the use of  artificial intelligence (AI) and machine learning (ML) to design lipid nanoparticles (LNP) for delivering nucleic acid therapeutics, presented new findings this week. The team unveiled its programmable LNP delivery platform in October 2023 and has continued to demonstrate the power of AI/ML to more safely and effectively deliver RNA therapies to specific extrahepatic tissues, ushering the potential for new therapies across a wide range of unmet needs. These new data points were presented on December 10, 2024 at the 3rd annual LNP Immunogenicity & Toxicity Summit in Boston.

Data presented by Mana.bio demonstrated how initial ML models generated a lung LNP candidate exhibiting highly specific in-vivo delivery to the lungs. Further, after just three months of iterative in-silico and in-vitro data generation, the company’s improved predictive modeling yielded a second-generation LNP candidate that increased in-vivo potency by 100-fold. Thus demonstrating the predictive power of Mana’s AI platform, and the potential for accelerating the pace and reducing the cost of RNA therapeutic development.

“The speed at which our team was able to generate new data, implement changes, and train new models is phenomenal. This demonstrates our ability to expedite the drug development process by years as compared to traditional development timelines,” said Yogev Debbi, co-founder and CEO of Mana.bio. “It’s exciting to see how combining tech and bio approaches continue to help us solve industry-wide challenges to unlock the potential of RNA delivery and accelerate development of therapeutics for patients.”

Towards development of a best-in-class lung therapeutics, Mana.bio developed an ML model to predict critical LNP safety determinants including cellular, immunological, hematological and hepatotoxicity.  Data presented by Mana.bio illustrated the rapid pace at which the company was able to design and train novel ML-models and produce third generation LNP candidates exhibiting broadly improved tolerability while maintaining potency and specificity.

Mana’s platform combines data curated from public resources with empirical data generated in the company’s proprietary lab to train ML models, which generate novel lipids and LNP compositions for bespoke therapeutic applications. The company is able to monitor both wet-lab and dry-lab performance in real time, and has produced an extensive library of high-quality data points generated from thousands of LNP formulations. With these proprietary insights, Mana.bio has identified key LNP features required for optimizing potency and tolerability of systemically administered LNP to extrahepatic targets.

Since closing the company’s seed funding in 2023, the team has demonstrated in-vivo delivery to a number of extrahepatic organs and cell types. The Mana leadership team will be attending the JP Morgan Healthcare conference January 13-16 in San Francisco, CA. To learn more about Mana.bio, please visit www.mana.bio or reach out directly at info@mana.bio.

About Mana.bio
Mana.bio is a biotechnology company revolutionizing targeted RNA delivery using artificial intelligence-enabled LNP discovery and optimization. This approach accelerates research and enables reliable, tissue-specific delivery to unlock the full potential of RNA therapies. Mana.bio is pioneering the next wave of biotechnology advancement by merging AI and biological insights. For more information, visit www.mana.bio.

Sofia Spieler on behalf of Mana.bio
sofia@mana.bio 

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SOURCE Mana.bio