Absci’s Post

Sharing a podcast with our dynamic CEO enterpreneur, Sean McClain, and Luke Timmerman. Curious to learn about Absci and the future of AI drug discovery, then you should listen to it! #absci, #ai, #artificial intelligence, #drug discovery

🔬 Exciting Collaboration: BioAI and Genomic Testing Cooperative Join Forces! 🌟 BioAI and Genomic Testing Cooperative have announced a strategic collaboration to support pharmaceutical companies and clinicians with advanced genomic testing solutions. This partnership aims to enhance precision medicine and improve patient outcomes through cutting-edge genomic technologies. 🌐 🔍 Key Highlights: -Strategic Alliance: Combining BioAI's expertise in artificial intelligence with Genomic Testing Cooperative's advanced genomic testing capabilities. -Enhanced Support: Providing comprehensive support to pharmaceutical companies and clinicians, enabling more accurate and personalized treatment plans. -Advancing Precision Medicine: Focused on leveraging genomic data to drive innovation and improve patient care. This collaboration marks a significant step towards integrating AI and genomic testing in healthcare, paving the way for more precise and effective treatments. Stay tuned for more updates on this groundbreaking partnership! 🚀 #BioAI #GenomicTestingCooperative #PrecisionMedicine #Genomics #AIinHealthcare #PharmaInnovation #ClinicalSupport #HealthcareCollaboration #MedicalAdvancements #PatientCare 4o

𝗧𝗮𝗸𝗲 𝗼𝗻 𝘁𝗵𝗲 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲. Accurate prediction of antibody-antigen complex structure remains difficult even for the latest AlphaFold 3. Why is this the case? ◆ 𝗟𝗶𝗺𝗶𝘁𝗲𝗱 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗱𝗮𝘁𝗮 𝗳𝗿𝗼𝗺 𝗣𝗿𝗼𝘁𝗲𝗶𝗻 𝗗𝗮𝘁𝗮 𝗕𝗮𝗻𝗸 (𝗣𝗗𝗕) ◆ 𝗛𝗶𝗴𝗵 𝘃𝗮𝗿𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗶𝗻 𝗖𝗗𝗥-𝗛𝟯 ◆ 𝗔𝗯𝘀𝗲𝗻𝗰𝗲 𝗼𝗳 𝗰𝗼-𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗮𝗿𝘆 𝘀𝗶𝗴𝗻𝗮𝗹𝘀 𝗶𝗻 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲 𝗮𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁𝘀 Despite these practical challenges, XtalFold, our proprietary structure modeling AI, has been successfully applied into dozens of antibody discovery projects. 𝗧𝗼𝗴𝗲𝘁𝗵𝗲𝗿, 𝗹𝗲𝘁'𝘀 𝗿𝗲𝘁𝗵𝗶𝗻𝗸 𝗯𝗶𝗼𝗹𝗼𝗴𝗶𝗰𝘀 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝘄𝗶𝘁𝗵 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗮𝗹 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀. Visit ailuxbio.com to explore next-generation applications inspired by XtalFold. #ailux #antibodies #ai #artificialintelligence #biologics #drugdiscovery #innovation 

We've developed IgDesign™, a powerful deep-learning method for antibody CDR design. With applications in de novo antibody design and lead optimization, IgDesign™ has the potential to help accelerate drug development and therapeutic antibody design projects. Highlights: - Experimentally validated AI model - Shown to design binders for 8 therapeutic antigens - Surpasses the performance of traditional methods Read the manuscript here: https://lnkd.in/gjEpSdTN #AI #Biologics #GenerativeAI #DrugDiscovery

We're proud to be initiating IND-enabling studies on ABS-101, a de novo designed and optimized anti-TL1A antibody with a potential best-in-class profile. Find out more about how our de novo generative AI foundation model engineers epitope-specific antibodies to access novel biology and our AI lead optimization models further engineer candidates to have an optimal clinical development profile: https://lnkd.in/gvci5qK3 #AI #Biologics #GenerativeAI #DrugDiscovery

Absci Senior Director of Alliance Management Fern M. will be speaking on a panel at the annual AUTM meeting next Monday. The panel will explore IP protection and commercialization of biological targets, various collaboration models for AI-based and traditional drug discovery companies, and more. We hope to see you there. https://lnkd.in/eTTqpbZY #AI #Biologics #GenerativeAI #DrugDiscovery

𝗘𝗻𝘃𝗶𝘀𝗶𝗼𝗻 𝘆𝗼𝘂𝗿 𝗽𝗼𝘀𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀: In a benchmark study to predict antibody-antigen complex structure, XtalFold outperforms AlphaFold-Multimer by a significant margin. ◆ 𝗛𝗶𝗴𝗵 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆: 70% prediction success rate ◆ 𝗛𝗶𝗴𝗵-𝘁𝗵𝗿𝗼𝘂𝗴𝗵𝗽𝘂𝘁 𝗼𝗻𝗲-𝘀𝘁𝗲𝗽 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻: bypassing separate structure modeling and molecular docking steps ◆ 𝗨𝗻𝗹𝗼𝗰𝗸𝗶𝗻𝗴 𝗻𝗲𝘄 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀: accelerating hit generation and enabling next-gen engineering 𝗧𝗼𝗴𝗲𝘁𝗵𝗲𝗿, 𝗹𝗲𝘁'𝘀 𝘁𝘂𝗿𝗻 𝗽𝗼𝘀𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 𝗶𝗻𝘁𝗼 𝗿𝗲𝗮𝗹𝗶𝘁𝗶𝗲𝘀. Visit ailuxbio.com to learn how XtalFold is illuminating biologics discovery. #ailux #antibodies #ai #artificialintelligence #biologics #drugdiscovery #innovation 

This past weekend, our President and CEO, Dr. Martin Crous, Ph.D, MBA, and our Chief Scientific Officer, Dr. Wei-Jen Lo, met up with Mr. Donnie Xu from Holymed at the AO Research Institute in Davos, Switzerland. The discussions focused on the success and strategic planning for the future of #BiostoneBiologics. #biologics #synthetics #medicaldevice #dentalimplants #veterenarianimplants #spinalimplants #orthopedicimplants 

𝑰𝒏𝒅𝒖𝒔𝒕𝒓𝒚 𝑩𝒍𝒐𝒈! Drug discovery has undergone a remarkable evolution, transitioning from serendipitous discoveries to a highly sophisticated and systematic approach driven by scientific rigor and technological advancements. Today, researchers are leveraging cutting-edge technologies to accelerate the development of new treatments and therapies that address complex medical challenges. 𝑬𝒙𝒑𝒍𝒐𝒓𝒆 𝒕𝒉𝒆 𝑬𝒏𝒕𝒊𝒓𝒆 𝑩𝒍𝒐𝒈: https://bit.ly/3We2JsS 𝑪𝒐𝒏𝒕𝒂𝒄𝒕 𝒖𝒔 𝒗𝒊𝒂 𝒆𝒎𝒂𝒊𝒍: info@worldbigroup.com #blog #drugdiscovery #leadership #drugdiscovery #innovation #genomics #sciencestudent #steam #scientist #biologics #medicinalchem #drugdiscovery #oncology #drugdiscoveryconference #ddipeu #worldbievents #scienceresearch #ddip24

I had a wonderful time at the Biologics 2024 Oligonucleotides Congress, a reminder of the power and potential of AI in advancing drug development. Reflecting on the vibrant discussions, it's evident that the future of drug development is intertwined with AI.  It’s also evident that the pace of innovation across biologics and oligonucleotide-based medicines is accelerating.   For oligonucleotide-based medicines, however, the challenge remains: creating quality data sets that are comprehensive, unbiased and appropriate for training relevant  AI/ML models.  Creating purpose-built prospective data has been a principal activity of Creyon Bio.  Our foundational innovations centered around optimizing and validating appropriate pharmacology assays and developing survey methods to make exploring the design space of oligonucleotide-based medicines tractable.  Retrospective or random data ultimately provide inadequate and overly biased learnings about how to engineer safe and active oligonucleotide-based medicines. There are no quality datasets available that allow for the learning that needs to happen to move from slow and failure prone trial-and-error screening to engineering for oligonucleotide-based medicines – we have to build them. It's not just about quantity; it's about building datasets that avoid biases that could skew our learnings. By focusing on data quality and diversity, we can ensure models built with leading AI/ML tools accurately predict drug safety and efficacy. We’ve committed to creating the right data and data infrastructure that fuels innovation and elevates us beyond the necessity of discovering molecules to a world where we engineer them.   #AI #innovation #oligonucleotides #Biologics24 @biologics-og