A new company called Xaira Therapeutics just launched with over $1B+ billion in funding for using AI in drug discovery R&D. To give you some context, the last time we saw this level of fundraising was for Roivant Sciences, which focuses on creating companies around abandoned drugs, and Altos Labs, with $3B for cellular rejuvenation programming. But this is the 1st for an AI drug discovery R&D company. Interestingly, a significant portion of the company's technology originates from the Institute for Protein Design at the University of Washington, which is renowned for its work in protein science. This institute is led by Prof. David Baker, the co-founder of this and also the Charm Therapeutics. Read the full story here: https://lnkd.in/eCZfV4CW #drugdiscovery #artificialintelligence
Pankaj Mishra, PhD’s Post
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Wow, this is a big one - $1B to leverage GenAI for drug molecule design. Two links to Illumina: - Funding lead is Bob Nelson, who seed-funded Illumina, and - "teams and technologies from the genetic sequencing giant Illumina" "Drug R&D is an endeavor rife with failure — commonly cited figures estimate that only about 10% of drugs that make it to human testing are ever approved, and a far greater share fail before ever being tested in a person." "Xaira and several other new biotechs believe they can change that with new generative AI methods that can design complex molecules from scratch, find new targets, and cut months or even years from the process." Great example of the potential for GenAI to disrupt the entire drug development process. At Ryght we're applying GenAI to another major bottleneck - getting drugs through clinical trials (you can try the preview version at ryght.ai).
In biggest-ever bet on using AI to design drugs, biotech heavyweights launch Xaira with $1B+ in backing
https://endpts.com
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"Drug development teams have found significant data and modeling challenges in regard to tackling the complexities associated with #PDIinhibitors given the challenges with creating meaningful models, and accumulating and deciphering the data," said Panna Sharma, CEO and President of Lantern Pharma. "Our #AI platform, RADR®, can increase the confidence, insights, and comfort levels in developing data-driven development paths by modeling highly complex scenarios at a scale that only has become possible recently. It’s an ideal approach for Oregon Therapeutics, which has executed a series of highly targeted in vivo and in vitro experiments and is poised to make incredibly important and patient-centric decisions about the clinical future of the molecule. That's where RADR® can play a highly essential and market defining role." https://lnkd.in/g8XPQSsa #biotech #businessdevelopment #artificialintelligence
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Dive into the world of AI in biotech with us at the Egnyte Life Sciences Summit! 🧬 Don't miss the panel discussion on the "Impact of AI in R&D" featuring experts from Digitalis Ventures, Alnylam Pharmaceuticals, and Xilio Therapeutics, Inc. Learn what's hype and what's real in the world of AI. Register now: 🔗 bit.ly/4cVUFU9 #LifeSciences #BioTech #ArtificialIntelligence #ai
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We are pleased to confirm an agreement with emerging UK drug turnaround biotech Ignota Labs to collaborate on the exchange of data from Inaphaea's Biobank to generate insights, co-develop new assets, and explore joint business opportunities, including grant funding. Ignota Labs will analyse data from Inaphaea's Biobank to develop in-silico models. These models will help identify new oncology assets, with plans to co-develop them through Inaphaea's tCRO® services and Ignota's platform. Mark Eccleston, Director of Inaphaea BioLabs comments: "ValiRx has utilised Ignota Labs' in-silico tox screening services for its in house evaluation projects and was impressed with the performance. This agreement leverages the data sets from Inaphaea's biobank to further develop Ignota Labs' in-silico capabilities which will benefit our early stage evaluation as well as providing an exciting new AI approach to asset discovery." Find out more about the agreement here: https://lnkd.in/eP9Vrt8j #BioTech #DrugDiscovery #Assays #AssayDevelopment
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This is the moment to re-engineer the entire drug discovery and development process - driven by growing data sets and new methods that are accelerating progress in applications of AI to biology, chemistry, and medicine. That’s why Foresite Labs teamed up with ARCH Venture Partners to incubate Xaira Therapeutics, an integrated biotechnology company harnessing this emerging toolkit to deliver innovative medicines to patients faster. Xaira launches with unprecedented capabilities to amass and generate biological, biophysical, and biomedical data, to build and deploy models of increasing scope, and to apply these in a robust product development process. For example, Xaira incorporates AI models and protein design technologies developed in Dr. David Baker’s lab at the Institute for Protein Design, University of Washington, and data generation capabilities in part spun out from Illumina. We’re incredibly proud of the team, led by founding CEO Dr. Marc Tessier-Lavigne, and our Board of Directors , including Scott Gottlieb, Alex Gorsky, Carolyn Bertozzi, and others we will announce today. We also thank the interim management team from Foresite Labs who has been involved in this incubation. Backed by ARCH Venture Partners and Foresite Capital, with additional investments from F-Prime Capital, New Enterprise Associates (NEA), Sequoia Capital, Lux Capital, Lightspeed, and Menlo Ventures, Two Sigma Ventures, Parker Institute for Cancer Immunotherapy, SV Angel, among others, Xaira is supported with over $1 billion in committed capital. Learn more on Xaira and our launch from Andrew Dunn and Ryan Cross in Endpoints News.
In biggest-ever bet on using AI to design drugs, biotech heavyweights launch Xaira with $1B+ in backing
https://endpts.com
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🚀 Is #AI the future of drug development? AI #startups are transforming drug development, drastically reducing time and costs. With over €16 billion invested, the potential is undeniable. 🌎 While the USA and UK lead, this global shift promises faster, safer treatments. 🗞️ Read the full article through the link in the comments – thanks, Plattform Life Sciences, for publishing this insightful piece by Dr. Fei Tian and Andreas Kastenbauer. 👏🏼 🔗 Xaira Therapeutics, Genesis Therapeutics, Exscientia, BenevolentAI, Relay Therapeutics, BioXcel Therapeutics, Inc., Biofourmis,
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Digital twins of cells to precision medicine 🚀 Exciting news in AI-driven drug discovery! French startup DeepLife has secured a $10M Series A funding round to advance their platform, which creates "digital twins" of cells. This innovative approach enables pharmaceutical companies to simulate drug effects on cellular models, accelerating the repurposing of existing medications for new therapeutic uses. By leveraging AI to predict cellular responses, DeepLife is paving the way for more efficient and personalized healthcare solutions. This aligns with my vision of transitioning from reactive sickcare to proactive healthcare, where digital twins play a crucial role in anticipating and managing health outcomes. Kudos to Jonathan Baptista and team #digitaltwins #pharma #drugdiscovery #omics #multiomics Digital Twin Consortium Sven Eyckerman VIB
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Disruptive Pharma welcomes Phenaros! We’re excited to welcome Phenaros, a promising drug discovery company from Uppsala University, to our office and lab space. By sharing our resources, we’re creating a collaborative environment where both teams can benefit from fresh ideas and diverse perspectives. Having Phenaros on-site provides a unique opportunity for knowledge exchange, helping us strengthen our approach to innovation and improve our workplace dynamics. We believe that this shared space will foster creativity, mutual learning, and growth for both organizations. About Phenaros Pharmaceuticals: Phenaros specializes in AI-driven drug discovery, using phenomics (large-scale cell profiling) combined with automation to discover and repurpose drugs, especially for rare diseases. Their cutting-edge platform accelerates the development of new therapies, making drug discovery faster and more efficient. #Welcome #Collaboration #AI #Pharma #DrugDiscovery #Uppsalauniversity #DisruptivePharma
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Dr. Petrina Kamya, PhD, joins the Industry Leading Speaker lineup at the #AIDrivenDrugDiscoverySummit in Boston! Petrina will be presenting "Case studies on leveraging AI from Target Discovery to the Clinic." Learn from real examples of where #AI has made a difference to the #drugdiscovery and development space. - Understand how and when AI was leveraged in the drug discovery value chain. At AIDD 2024, you can learn from industry leaders from Amgen, GSK, Novo Nordisk, Sanofi, Takeda and more about real-world successes and failures to avoid common pitfalls. #AIDD #BostonBiotech #GenerativeAI #AIConferences #AIDD2024
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Debra Touw, Principal Scientist, Multi-Specifics at AbbVie presented how 12+ years of using Genedata has enabled them to optimize their biologics discovery and engineering workflows as they expanded to new molecule formats, therapeutic modalities, and R&D focus areas. Genedata integrates information from hybridoma, yeast and phage display, single B-cell, computational engineering, and external partners to create building blocks for new therapeutic candidates and lays the groundwork for AI/ML initiatives. With all data in one location, AbbVie can easily compile patent filings, explore legacy information, and manage data and processes across multiple sites. During the lively Q&A session, Debra addressed the question of onboarding by saying that people use Genedata Biologics because it makes life easier for them, for example, mass spec analysis is easier. #DigitalizingBiopharma #OpenForum
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Postdoctoral Research Fellow | Quantum and Computational Chemist | Electronic Structure Theory
10moIt would be interesting to know the actual correlation between startup funding, and successful new drug candidates discovered in 5-10 years.