Automation and digitalization
Automation and digitalization
Unlocking Flow Cytometry’s Secrets: Consistent Results Made Simple!
🔬⚖️ Consistent quality control & standardization are crucial in flow cytometry for accurate & reliable results. Discover BD FACSLyric™ Flow Cytometer! 👩🔬🔬📊 Note: BD is the sponsor of this article. Register on the website to learn more and download the application note.
Revolutionizing Nucleic Acid Manufacturing with Digital Innovation
📰 Scientists at Penn State highlight the need for digital innovation to enhance nucleic acid manufacturing efficiency. 💡💻🧬
Revolutionizing Bioprocessing with Advanced Image Analysis
🔍 Expanding Applications of Image Analysis explores the potential of imaging in bioprocessing and biotechnology, including machine learning and in situ microscopy. 📸
Mastering Lab Data: The Key to Quality Control
🔍 Data Integrity and Governance in a Quality Control Laboratory emphasizes the importance of accuracy and reliability in lab data. 📝🔒🔬 QualityControl DataIntegrity
Revolutionary Automated CAR-T Manufacturing: High Efficiency Lower Costs
📰 A French company is developing an automated system for manufacturing CAR-T cells at scale, reducing costs. 🏭💡🔬🌍💰👩🔬📅
Revolutionizing Bioprocessing with IoT Innovation
🌐💡 The IoT can revolutionize bioprocessing by connecting devices and exchanging data, leading to more efficient experiments and automation. 🚀
Revolutionizing Bioprocesses with Machine Learning
📢 Machine learning (ML) could revolutionize biopharmaceutical processes by creating predictive models. 🔬 Manufacturers need high-density process sensors to train ML algorithms. 🚫 Sensors should be noninvasive and prevent contamination. 🧫 Researchers have developed a noninvasive CO2 sensor for cell culture monitoring. 💡 Machine learning can still be applied even with limited real-time data. 📚 A machine learning-based method for protein quality assessment using limited data has been developed. 💪 ML has the power to simplify process monitoring and improve bioprocess outcomes.
Boosting Manufacturing Efficiency: AI’s Role in Cutting Costs and Enhancing Therapies
🧪 AI accelerates commercialization strategies by cutting costs and improving processes in advanced therapy manufacturing. 🔬 5 of batches fail, impacting health and revenues. 🧠 AI is crucial for complex therapies. 💰 Manufacturers need to optimize processes and reduce costs. 🌐 AI enables learning transfer and supports decision-making. 📈 Industry 4.0 will use machine learning for real-time predictions and support.
Novartis Revolutionizes Cancer Therapy Production with Automation
📢 Novartis automates new radioligand therapy plant in Indianapolis! Increased supply and timely production for prostate cancer therapy. 👨🔬🤖🏭💉
Revolutionizing Bioprocessing with Machine Learning
🤖 Machine learning (ML) reduces guesswork in bioprocessing by improving precision and minimizing errors. Factors like bio-kinetics, bioprocess responses, instrumentation, and environmental disturbances influence outcomes. ML can control bioreactors, identify errors in chromatography analysis, and selecting the right ML algorithm and model is crucial for real-time application. Combining ML-based tools with other analytical methods and correct data maximizes the benefits of ML in bioprocessing.
