Mana.bio Showcases AI-Driven RNA Therapy Innovations at ASGCT 2025
Mana.bio has presented new data at the American Society of Gene & Cell Therapy (ASGCT) 2025 Annual Meeting, showcasing its advancements in AI-driven RNA therapy. In a press release, the company detailed its machine learning architecture designed to enhance the safety and specificity of lipid nanoparticles (LNPs) for RNA delivery.
The presentations at the meeting included three posters that demonstrated the platform's predictive capabilities for LNP safety and specificity. These findings are significant for the development of precision RNA therapies targeting T-cells and lung tissues. The posters, presented on May 14 and 15, 2025, in New Orleans, highlighted Mana.bio's ability to rapidly design and optimize LNPs, addressing key challenges in developing extra-hepatic RNA therapies.
Mana.bio's approach combines public data with lab-generated data to train machine learning models capable of predicting critical LNP attributes, such as physiochemical properties and tissue specificity. This innovation underscores the transformative potential of AI in accelerating the design process for genetic medicines aimed at treating cancer, autoimmune, and respiratory diseases.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Life AI Weekly or Daily AI Brief.
Also, consider following us on social media:
More from Life Sciences
Oct 17 Masimo Gets FDA Clearance for AFib Detection on Radius VSM Oct 16 Study Tests Smartphone AI for Children's Lung Sounds Oct 16 Manhattan Physician Invests in RunPractice Oct 16 Attilio appoints Buck Institute CEO Eric Verdin as cochairman Oct 16 Aignostics launches HETA Clinical for pathology workflowsLife AI Weekly
Weekly coverage of AI applications in healthcare, drug development, biotechnology research, and genomics breakthroughs.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Likang to Present AI Cancer Immunotherapy Platform in Abu Dhabi
Lunit and Discovery Life Sciences Partner on AI Tissue Analysis
Zealand Pharma signs AI obesity drug deal worth up to $1.2 billion
Manulife Launches Enterprise AI Platform
Phylo Launches Target Atlas for Drug Target Prioritization
Daily AI Brief: the AI news that matters, in your inbox.