ENPICOM

Attending #NextGenBiomed2025? Don't miss our talk today! 📢 Maximize AI Potential in Biologics Discovery & Development: From Model Training to Consumption – 12:00 PM. And if you want to dive deeper into AI-driven biologics discovery, visit us at booth #47. See you there! #AI #biologics

Today, I joined a fantastic panel discussion chaired by Andrew Buchanan. For nearly an hour, we explored how AI/ML is shaping biologics drug discovery. Here are the key takeaways 1️⃣ Data matters more than models. AI relies on high-throughput, structured, and well-annotated data. If data pipelines aren’t robust and built for scale, they become bottlenecks instead of enablers. 2️⃣ AI engineers don’t speak biology, and biologists don’t speak AI. Finding people who can bridge that gap is rare, and training AI specialists in drug discovery takes time and resources. 3️⃣ Benchmarking is critical for progress. Continuous benchmarking ensures models are improving and performing reliably in real-world scenarios. This underscores the need for robust MLOps practices to streamline model deployment, monitoring, and iteration. 4️⃣ Moving from proof-of-concept to production demands a cultural shift. AI adoption requires long-term management commitment and user adoption, yet many teams underestimate the changes and sustained effort needed to go beyond proof-of-concept. 🎯 TL;DR Data, data, data, automation, adoption. AI won’t deliver impact unless a unified platform is established that consolidates how data is generated, processed, and collected at scale, and ML models are continuously tested, tracked, and made available to scientists. #NextGenBiomed2025 #AntibodyDiscovery #AI #ML

Rise and shine, London! 🇬🇧 We’re here for #NextGenBiomed2025 and ready for a great day of discussions, insights, and innovation. Don’t miss The Role of AI/Machine Learning in Biologics Drug Discovery today at 14:45, where Nicola joins experts from AstraZeneca and Sanofi to discuss digital transformation, ML/Computational tools impacting antibody R&D, and more. 📍 Visit us at booth #47 to talk about your AI adoption challenges and strategies, let’s chat! #AI #drugdiscovery

We spoke with Nicola Bonzanni, Founder & CEO of ENPICOM, about what they’re excited to share at NextGen Biomed 2025 next week! 💫 ENPICOM is transforming biologics discovery with their bioinformatics solutions, empowering scientists to accelerate breakthroughs. Don’t miss their insights at the event! There's still time to register: https://lnkd.in/eRT8xXdM #NextGenBiomed2025 #BiologicsDiscovery #Bioinformatics #AI

Excited to be heading to #NextGenBiomed2025 in London next week! 🎤 Nicola Bonzanni, our Founder & CEO, will join experts from AstraZeneca and Sanofi for a panel discussion on The Role of AI/Machine Learning in Biologics Drug Discovery – Wednesday at 14:45. 🎤 Néstor Vázquez Bernat, PhD, Head of Application Science, will take the stage to present Maximizing AI Potential in Biologics Discovery & Development: From Model Training to Consumption – Thursday at 12:00. Looking forward to exchanging ideas, learning from the best, and, of course, catching up over coffee! Will you be there? Let’s connect. #biologics #AI

Software should work for scientists, not the other way around. That’s why UX is a core pillar at ENPICOM. We’re always looking for ways to make our platform more intuitive, efficient, and seamless for biologics discovery and optimization. Recently, we ran a dedicated two-day UX sprint to enhance usability. Huge thanks to everyone involved, especially our software team, for their dedication. Excited to see these improvements roll out so quickly! #ux #innovation #ENPICOM

🎉 The ENPICOM team has a new home! We’ve moved to a brighter and more inspiring space in the heart of Den Bosch. Still in the same historic building, but now with even more room to advance ML-aided biologics discovery. A bigger space for bigger plans - 2025 is already shaping up to be an exciting year! And of course, our hardworking coffee machine made the move too - so if you’re in the area, stop by for a chat. We’ll have a fresh cup waiting for you! ☕️ #NewOffice #Growth #ENPICOM

Realizing the transformative potential of AI requires the ability to systematically test, improve, and deploy ML models at scale. In a recent presentation, Néstor Vázquez Bernat, PhD, our Head of Application Science, addressed the key challenges in applying machine learning to biologics discovery. Discover how a unified platform can streamline AI workflows, enabling seamless integration from model training to deployment. https://lnkd.in/eenA5PUZ #MLOps #drugdiscovery

What is MLOps, and why should biologics discovery companies pay attention? While much of the industry focuses on building exceptional AI models to accelerate drug discovery, the true potential of these technologies can only be realized when companies can move fast and systematically test, improve, or discard models at scale. Organizations that master MLOps will unlock faster iteration cycles, greater scalability, and a smoother path to regulatory approval. Learn more in our blog: https://lnkd.in/emrFbN4K

Last week, I came back from the inaugural Biologics event in San Diego ☀️. What a great event! One of my biggest takeaways? The AI in biologics community is thriving 🌱. Yet, as progress is happening across all fronts, it’s crucial to remember that success in this space relies on a concerted effort between lab scientists and ML scientists. As Sai Reddy and his team highlight in their recent paper: “Ultimately, to advance immune receptor specificity prediction, we consider it essential to maintain and strengthen collaboration between wet-lab and computational researchers. By doing so, each may better understand the nuances and limitations of experimental data generation and of computational processing and ML model development. This will lead to improved experimental design and higher-quality datasets, eventually making it possible to train accurate and generalizable ML models capable of predicting and designing immune receptor specificity.” Collaboration 🤝 is key! #AI #Biologics #MachineLearning #MLOps