Process Design Center

Is AI reliable enough for application in the bio-based industries? Can it actually make processes more efficient? And does it really lead to new insights, or are we dealing with an automated parrot that repeats past results? The Bio-based Industries Consortium (BIC) shows some examples of how artificial intelligence is being used in the bio-based industries. Process Design Center's expert system is one of them. "... based on the answers you give, certain possibilities are ruled out. Follow up questions refine the diagnosis. In the end, a number of solutions remain, for which the probabilities can be calculated..." Check the full story at: https://lnkd.in/euuRB-KS

This #FLEXIWednesdays, instead of focusing on the #FLEXIZYME project, we’re taking a look at a real-world case that demonstrates how #machinelearning (ML) is transforming biotechnological processes globally. Let’s explore how another #biotech company successfully leveraged #ML to optimize enzyme performance and streamline production. 🚀 Case Study: Ginkgo Bioworks and Machine Learning in Enzyme Engineering 🚀 Ginkgo Bioworks, a leading biotech company, faced a significant challenge in optimizing enzymes for industrial applications. Ginkgo used machine learning algorithms to predict the performance of different enzyme variants. They trained their ML models using #data from thousands of enzyme experiments, enabling the system to analyze enzyme sequences, reaction conditions, and performance metrics. The model could then predict how various enzymes would behave in specific environments. Key Outcomes: 🔸 Faster Enzyme Development: What previously took years of lab work could now be done in months. ML helped Ginkgo narrow down the most promising enzyme variants for testing, cutting development time drastically. 🔸 Higher Efficiency: By predicting enzyme activity and stability under different conditions, Ginkgo was able to optimize production processes, leading to higher yields and less waste. 🔸 Sustainable Production: With ML-optimized enzymes, Ginkgo reduced energy consumption and waste in their processes, making them more sustainable while maintaining high performance levels. 🌱 How FLEXIZYME Aims to Leverage Machine Learning 🌱 FLEXIZYME will adopt similar ML techniques to accelerate enzyme selection, optimize real-time reactions, and reduce resource consumption in fatty amine production. We will be at the forefront of integrating ML into its production methods, revolutionizing how we approach sustainable biotechnological production. 📢 Follow us for weekly updates every Wednesday! 📢 This project has received funding by the Circular Bio-based Europe Joint Undertaking (CBE JU) under Grant Agreement No 101157528. ITENE | Bio Base Europe Pilot Plant | Centre for Research & Technology Hellas (CERTH) | CluBE-Cluster of Bioeconomy and Environment of Western Macedonia | Coreysa | CSIC | ENCO Engineering and Consulting srl | GECCO Biotech | LAVANTIA | LIPSA | National Technical University of Athens IPSEN Industrial Process Systems Engineering Unit | Process Design Center | ROELMI HPC - Società benefit | Syensqo | University of Groningen | Università di Pisa | VOION LAND PRODUCTS

Kicking of a new bio-based project, introducing a new service 'Idea Factory' and updates to our flagship software product Prosyn. Follow PDC and subscribe to our newsletter at https://lnkd.in/eXNVKUzk

We are honored that our PMMA recycling project together with Trinseo (former Arkema) was selected as “Project of the Month” by the CORDIS platform! https://lnkd.in/e_JrY3Pt

For those who are interested: https://lnkd.in/etsMznvH