Antiverse

?? Big news: we're now working with Nxera Pharma to design novel GPCR-targeted antibodies for multiple diseases of high unmet need! Our multi-year partnership with Nxera will aim to bring transformative antibody therapies to patients. Approximately 220 GPCRs with known disease links are currently undrugged and antibodies are an essential tool to change this. This collaboration combines our expertise in generative AI antibody design with Nxera’s NxWave? platform – a powerful tool for GPCR target selection, validation and structural determination. The first project will be aimed at designing antibodies with agonistic functions for a challenging GPCR target. Read the press release ?? https://lnkd.in/eNfzDXrZ #Antiverse

?? With drug development costs ranging from $314 million to $2.8 billion and often taking decades to reach patients, improving efficiency is a priority. Singularity Hub explores how AI can be a tool to reduce drug failure rates and accelerate timelines in drug discovery – from identifying targets to screening candidates. However, AI is only as effective as the data behind it – small or low-quality datasets currently constrain its use in drug discovery, making accurate predictions and real-world breakthroughs more challenging. We design our epitope-specific libraries by generating high-quality data and continuously refining predictions through experimental feedback from our internal pipeline and industry partnerships. This iterative approach enables us to tackle complex targets like GPCRs and ion channels with greater accuracy, reducing discovery timelines and increasing the likelihood of clinical success. Read more ?? https://lnkd.in/gadkm_zX

Antibody discovery has long relied on trial and error, but we’re taking a different approach. Our generative AI antibody design platform evaluates the complex dynamics between epitope-paratope binding in challenging drug targets, like GPCRs and ion channels. Using structure and sequence data, our AI models create epitope specific libraries with high confidence against the target region. To ensure real-world clinical success, we synthesise these antibodies, screen them against hyperexpressing stable cell lines, and validate their function. Through this more efficient way of tackling complex drug targets, we deliver functional binders to our partners, helping them accelerate discovery timelines. Find out how we’re reshaping antibody discovery ?? https://www.antiverse.io/?

There's a lot of conversation on how AI is making drug discovery more efficient, but what does the actual data say? A recent review in Association for Clinical and Translational Science Science examines AI’s impact across drug development, from early discovery to regulatory approval. For elusive targets like GPCRs and ion channels, success rates are likely much lower than what’s reported, as there is less data available to train machine learning models. Biologics likely also see lower success rates due to their complex structures requiring more computational power and data to design effectively. However, we see significant untapped potential in these spaces. We are tackling these challenges by using generative AI to design epitope-specific antibody libraries for some of the hardest-to-drug targets. Our internal pipeline and pharmaceutical partnerships allow us to generate high-quality data for GPCRs, closing the data gap and enabling more accurate discovery. Read more ?? https://lnkd.in/evmvf--v?

?? We're hiring for a Chief Scientific Officer ?? We’re looking for a visionary CSO to lead the development of our cutting-edge biologics pipeline by leveraging our AI-driven antibody design platform. As CSO, you’ll build a strategy to execute several antibody design programmes, from target selection through to IND. You’ll blend the power of generative AI with state-of-the-art wet-lab technologies to create breakthrough therapies that could transform patients’ lives. We're looking for someone with expertise in GPCRs, ion channels, or solute carriers as well as: ?? 15+ years of experience in biologics and antibody development ?? Expertise in preclinical models, CMC, GMP, and IND processes ?? A natural leader who thrives in fast-paced, innovative environments with a passion for patient impact If that sounds like you and you'd like to join a team that’s pushing the boundaries of antibody discovery. Apply now ?? https://lnkd.in/e94wHdZh #Antiverse #Hiring

?We’ve been featured in Startups Magazine alongside Ochre Bio and Qureight in a piece spotlighting how AI startups are advancing drug discovery. Antibody development is a cornerstone of modern medicine, yet traditional discovery methods struggle with complex targets like GPCRs and ion channels. These targets remain largely unexplored in antibody therapeutics, despite their potential to treat a wide range of diseases, leaving a significant unmet patient need. By applying generative AI to antibody discovery, we're unlocking new possibilities for some of the hardest-to-treat diseases. Our platform uses structural and sequence data to design epitope-specific antibody libraries, increasing the likelihood of identifying functional binders. Unlike traditional trial-and-error approaches, our computational method significantly accelerates discovery – reducing timelines from years to just six months. Thank you Matthew Cafer for covering our work ?? https://lnkd.in/eDvjnnhs

?? Generative AI could reduce drug discovery costs by up to 67% Generative AI is reshaping the future of drug discovery and development by streamlining processes, reducing costs, and enabling more targeted approaches to drug development. EY-Parthenon explores how generative AI has the potential to drive progress in several key areas of drug discovery, including: 1?? Target identification to predict drug-target interactions and prioritise promising targets, 2?? Target validation to design custom compounds tailored to a specific target or disease, 3?? Hit generation to predict protein drug interactions, binding affinity and side effects to accelerate the identification of compounds, 4?? Lead optimisation – to identify candidates with ideal therapeutic properties. Learn how the pharmaceutical industry can benefit from AI applications within drug discovery and development, and the steps needed to successfully support it's integration ?? https://lnkd.in/gtg4ade7 #Antiverse

GPCRs and ion channels are some of the most challenging drug targets, but they don’t have to be... Drug discovery is a long and complex process, typically taking decades to move from target selection to patients. Timelines can be even longer for GPCRs and ion channels, as traditional discovery methods are often inefficient and unreliable, leading to countless repetitions of clinical trials as drugs fail to make it to market. Over the past seven years, our team of engineers, computer scientists, and biologists have been dedicated to changing this. By designing precision antibodies using our generative AI platform, we can reduce drug discovery timelines from years to months. We do this by using in silico techniques to create large epitope-specific antibody libraries, enabling rapid progression from target identification to functional binders. Learn more about how we are redefining drug discovery ?? https://www.antiverse.io/ #Biotechnology #DrugDiscovery #Antiverse

G-protein coupled receptors (GPCRs) are linked to hundreds of diseases, yet only three FDA-approved antibodies currently target them – a minute fraction of the 80+ antibodies available on market. The neglect of GPCRs in antibody discovery leaves a massive gap in treatment options for patients. Through computational antibody design, our generative AI platform helps bridge this gap. Epitope specific libraries create binders with higher confidence against targets, allowing us to open the GPCR antibody druggable space, bringing new therapies to patients. Our platform comprises three core components: 1?? Epitope-specific library design? 2?? Proprietary hyper-expressing cell lines? 3?? Multiparameter clustering AI module Our technology is already helping three global pharmaceutical companies design antibodies for challenging targets and accelerate the development of novel antibody therapeutics, while also advancing our own internal pipeline of transmembrane targets. Learn more about our antibody design platform: https://lnkd.in/e2khrNU3 #Antiverse #DrugDiscovery

J.P. Morgan Healthcare Conference was a brilliant way to start the year! Murat Tunaboylu, Michael Mahdavi and MOON-IL KANG from our team caught up with familiar faces, met new ones, and explored connections that will help shape the next phase of biotech and bring innovation to to life faster, at scale, and with greater impact. While the outlook for 2025 varies, one thing is clear – innovation is moving forward, with a strong focus on data-driven decision-making and real-world impact. ?Here are our key takeaways: ?? Biotech is stabilising, and investment is picking up, but it’s all about fundamentals. Strong science and good data will define success in 2025 ?? While interest in AI’s role in drug discovery remains strong and pharma continues to weigh build vs buy strategies, the emphasis on reproducible data and robust testing was a clear priority. ?? Precision-led antibody design is gaining traction with great discussions at our WuXi AppTec Global Forum roundtable that highlighted growing interest in AI-driven approaches for challenging targets like GPCRs If you didn’t make it to J.P. Morgan and would like to learn more about our technology, schedule a meeting: https://lnkd.in/eRBgmd6R