ADC Manufacturing Report: Practices, Challenges, and Future Trends

Merck & Variational AI Strike a Game-Changing $349M Deal Merck & Co. is doubling down on innovation by partnering with Variational AI in a significant $349 million deal. This collaboration sets the stage for the development of promising small molecule candidates targeting two challenging areas. By harnessing artificial intelligence, the collaboration aims to push the boundaries of what's possible in drug discovery, paving the way for advancements that could have a substantial impact on healthcare. The integration of AI in drug development is not just a trend—it's a transformative tool that holds the potential to revolutionize how we approach complex medical challenges. This partnership exemplifies how leading pharmaceutical companies can harness AI's power to accelerate research and deliver innovative solutions faster and more effectively. What are your thoughts on the increasing role of AI in pharmaceutical collaborations? Could this be the key to unlocking new medical breakthroughs? [Merck & Co.](https://www.merck.com) | [Variational AI](https://www.variational.ai) #AIInPharma #DrugDiscovery #Innovation #Healthcare #Biotechnology #Merck

Takeda is expanding its partnership with Nabla Bio to design new biologics using AI-powered models. Another example of the shift of use of AI from “experimental” to core R&D strategy. The focus now is speed and precision to get to focused candidates faster. Where do you see AI making the biggest impact first — molecule design, screening, or clinical planning? Teams that pair these new tools with biology are starting to separate themselves by turning AI into a real advantage instead of just a buzzword on a slide. #AIDrugDiscovery #BiotechInnovation #PharmaStrategy https://lnkd.in/eCeCfntd

💡AI is transforming drug discovery - fast. From small molecules to biologics, AI is accelerating design, improving precision, and unlocking new therapeutic possibilities. Rouken Bio explores how deep learning, generative models, and closed-loop systems are reshaping antibody development and targeting complex diseases. 🔬 The future? Autonomous, personalised biologics - validated by wet lab expertise. 📖 Read more: 👉 https://bit.ly/4ofr9O2 #AIinBiotech #DrugDiscovery #Biologics #PrecisionMedicine #RoukenBio #ImmunologyCRO

A perspective on AI driven therapeutic discovery from Aimee Cliens. The successes, and the remaining challenges. #AItherapeutics #antibodytherapeutics #drugdiscovery #biologics

RoukenBio, this is an excellent deep dive into the accelerating role of AI in drug discovery. We fully agree that the future lies in combining the predictive power of computational tools with robust experimental validation. At MAbSilico, we employ a fully integrated AI-driven pipeline followed by experimental validations in our wet-lab, that significantly de-risks and accelerates the antibody discovery curve. Our methodology is built on a few core pillars: 1. Design & Prediction: We use structure-based biophysics to generate, optimize or characterize antibodies. 2. Multi-Parametric De-risking: We profile hits for developability (aggregation risk, PTM liabilities...) and off-target binding before we commit to costly wet-lab experiments. This ensures that the candidates advancing for synthesis have the highest probability of success. 3. Strategy & IP: Our MAbFactory platform with the most extensive manually curated data set from thousands of patents to map the competitive and epitope landscape of any target allows discovery teams to potentially identify novel epitopes giving the program built-in Freedom-to-Operate (FTO) advantage. The key is that the computational solutions do not just suggest hits; they deliver pre-validated, high-quality candidates to the wet lab, making the screening process more efficient and focused. We are happy to discuss, feel free to reach out! #AIDiscovery #Techbio #Biotech #DrugDesign #InSilico #Biologics #AntibodyEngineering #DrugDiscovery

"Artificial intelligence in drug development" - Nature Medicine An interesting overview of the recent advancements with AI in drug development. This paper summarizes how AI can be involved from identification of disease targets, drug discovery, preclinical and clinical studies and post-market surveillance. Though AI has its challenges and limitations, the evolving advancements and refinement of AI has the potential to improve the efficiency and cost-effectiveness of drug development in the coming future. #AI #DrugDevelopment #Pharma #Biotech

The "ABC" model — #AI + #BioTech / #BioPharma + #CXO — is reshaping the competitive landscape of the #ADC field. A new tripartite collaboration between Insilico Medicine, 迈威（上海）生物科技股份有限公司, and ChemExpress integrates cutting-edge capabilities across the drug development chain: from AI-driven molecule design, to antibody engineering, to small molecule synthesis. Key advantages of this integrated approach: ▫️ Parallel Development – shortening R&D cycles ▫️ Platform-driven Innovation – enabling modular, Lego-like candidate assembly ▫️ Optimized Therapeutic Window – through co-designed linker and payload strategies This synergy marks a shift from siloed progress to end-to-end collaboration — accelerating the future of ADC therapeutics. Read the full analysis here 👉 https://lnkd.in/eK2n4YyH #DrugDiscovery #Biotech #PrecisionMedicine #Innovation

MOLCURE Joins Forces with Boehringer Ingelheim to Discover and Develop Innovative Antibody Drugs for Multiple Targets Using Its AI-driven Platform Technology https://lnkd.in/eAxnihvr #biotech #AI #antibody MOLCURE Inc. Boehringer Ingelheim

Merck KGaA and Siemens have expanded their partnership to transform drug discovery and development with integrated digital and AI solutions. Following Siemens’ acquisition of Dotmatics (now Dotmatix), this collaboration will create unified digital workflows connecting research, development, and manufacturing. This partnership advances a digital-first, data-driven future for life sciences, enabling scientists to deliver life-changing therapies faster. #DrugDiscovery #LifeSciences #Biotechnology

Our representative, Shingo Nakamura, recently participated in a panel discussion on AI drug discovery at the CAS Life Science Summit in Tokyo, hosted by CAS, the American Chemical Society's information solutions division. The discussion was featured in the October 7th edition of Chemical Daily. Shingo highlighted a critical challenge for mRNA-targeted therapies: mRNA structural data is only about 1/100th the volume of protein structural data, which significantly restricts the application of AI. We are actively accumulating crucial mRNA data and deploying proprietary AI strategies to maximize the utility of these limited datasets. These strategic efforts will position us as a leader in mRNA-targeted AI drug discovery. #AIDrugDiscovery #mRNA #LifeScienceSummit #Biotech #Innovation #CAS #Pharmaceutical