Overview
Antleron helps innovators design, optimize, and scale controlled bioprocesses with precision, speed, and reliability. The company accelerates therapy development and fine-tunes complex workflows through data-driven insight and scalable engineering.
Key people
In the news
- We often hear the same handful of questions when talking to CGT process developers about model-driven development. Here is how we answer them. 1. "𝙒𝙞𝙡𝙡 𝙩𝙝𝙞𝙨 𝙖𝙘𝙩𝙪𝙖𝙡𝙡𝙮 𝙬𝙤𝙧𝙠 𝙛𝙤𝙧 𝙢𝙮 𝙥𝙧𝙤𝙘𝙚𝙨𝙨?" Usually, yes. We take a structured, risk-based approach: define what the model needs to answer before we build anything. That scopes the model to be fit-for-purpose instead of over-engineered. We have applied this to HEK-based AAV production, MSC expansion, EV production, and personalized CAR-T. Each brings its own
- 𝙃𝙤𝙬 𝙢𝙖𝙣𝙮 𝙚𝙭𝙥𝙚𝙧𝙞𝙢𝙚𝙣𝙩𝙨 𝙬𝙤𝙪𝙡𝙙 𝙮𝙤𝙪 𝙧𝙪𝙣 𝙞𝙛 𝙢𝙖𝙩𝙚𝙧𝙞𝙖𝙡 𝙖𝙣𝙙 𝙡𝙖𝙗 𝙩𝙞𝙢𝙚 𝙬𝙚𝙧𝙚 𝙣𝙤𝙩 𝙝𝙤𝙡𝙙𝙞𝙣𝙜 𝙮𝙤𝙪 𝙗𝙖𝙘𝙠? That is the question our 𝘪𝘯 𝘴𝘪𝘭𝘪𝘤𝘰 experiment application answers. We built the application on custom process models we developed inside Antleron Nexus. Because each model is grounded in mechanistic principles and trained on your own biological data, the digital experiments it runs stay directly relevant to your program, not generic simulations. The models are dynamic
- Van experiment naar impact bij de patiënt. Dat is precies waar wij bij Antleron elke dag mee bezig zijn. Op 21 oktober gaat onze CEO Jan Schrooten hierover in gesprek tijdens de Health Tech Sessions - Hardware & AI, samen met UZ Leuven en Nyxoah. Benieuwd hoe regeneratieve geneeskunde de sprong maakt naar schaalbare zorgoplossingen? Kom luisteren! From experiment to real impact for patients. That's exactly what drives us at Antleron every day. On October 21, our CEO Jan Schrooten will discuss this during the Health Tech Sessions -
- 𝗖𝗲𝗹𝗹 𝘁𝗵𝗲𝗿𝗮𝗽𝘆 𝗰𝗮𝗻 𝘄𝗼𝗿𝗸 𝗯𝗲𝗮𝘂𝘁𝗶𝗳𝘂𝗹𝗹𝘆 𝗶𝗻 𝘁𝗵𝗲 𝗹𝗮𝗯 𝗮𝗻𝗱 𝗰𝗮𝗻 𝘀𝘁𝗶𝗹𝗹 𝗳𝗮𝗶𝗹 𝘁𝗼 𝗿𝗲𝗮𝗰𝗵 𝗽𝗮𝘁𝗶𝗲𝗻𝘁𝘀. 𝗖𝗼𝘀𝘁 𝗶𝘀 𝗼𝗳𝘁𝗲𝗻 𝘁𝗵𝗲 𝗿𝗲𝗮𝘀𝗼𝗻. Most teams find out what their process costs after it is designed, once the expensive choices are already locked in. We built the cost of goods application in our Antleron Nexus platform to move that answer to the front. It runs on a validated hybrid model of your own process, grounded in mechanistic principles and a focused set of
- BILS 2027 is invitation-only. GBX CIRCLE builds the room by relevance, not by registration count. Our CEO Jan Schrooten is one of the people invited to the Day 2 plenary, 11 February in Berlin, standing alongside the people who carry biomanufacturing's hardest problems day to day. His session, Carrying Biology to Scale, is about where AI changes how biology reaches scale, not just how a facility runs. That scale-up is what stands between a promising therapy and the patients waiting for it. If you are one of the people in that
- One week to go, Barcelona Antleron is ready to discuss how our solutions can help you process. Scaled-down models built to produce data that translates cleanly from bench to GMP scale. A digital toolbox: hybrid models and other digital solutions enabled through Antleron Nexus. Closed automated production which results in more reproducible batches with fewer open steps. Our CEO, Jan Schrooten, will be attending Advanced Therapies Europe next week. Reach out and let's find time for a discussion. 📍 InterContinental, Barcelona 📅
- 𝗗𝗼 𝘄𝗲 𝗹𝗼𝘀𝗲 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝗼𝗳 𝗼𝘂𝗿 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗼𝗻𝗰𝗲 𝗔𝗻𝘁𝗹𝗲𝗿𝗼𝗻 𝗯𝘂𝗶𝗹𝗱𝘀 𝘁𝗵𝗲 𝗺𝗼𝗱𝗲𝗹 𝗯𝗲𝗵𝗶𝗻𝗱 𝗼𝘂𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀? We hear this from CGT teams considering our digital solutions, especially once the underlying process model starts driving decisions they used to make themselves. Fair concern. Here is how we think about it. Once a model is validated, we deploy it on Antleron Nexus, our web-based platform, as applications your team runs directly. You explore
- Barcelona, 7 to 9 September. We will be at Advanced Therapies Europe, where regulatory planning, manufacturing and market access all sit on one programme. Our mission at Antleron is to get cell and gene therapies to more patients, faster and more affordably. We work at the point where digital innovation meets GMP reality, combining scaled-down models and closed, automated manufacturing with hybrid digital twins that pair mechanistic understanding with machine learning. The aim is CMC robustness and process economics that still hold
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