🔬 Around 5% of batches fail, impacting patient health and manufacturing revenues.
🧠 AI is crucial for complex advanced therapies with fewer established processes.
💰 Manufacturers of expensive gene and cell therapies need to optimize processes and reduce costs.
🌐 AI can enable learning transfer between similar therapies and support decision-making in the pharmaceutical industry.
📈 Companies will move to Industry 4.0 using machine learning for real-time predictions and support.
Introduction:
Artificial intelligence (AI) can play a significant role in accelerating the commercialization strategies of advanced therapy manufacturers by reducing costs and improving process understanding. Michael Sokolov, co-founder and COO of DataHow, a bioprocess modeling and operations support company, emphasizes the potential benefits of AI in process development and manufacturing in the biopharmaceutical industry.
- AI can enable robust manufacturing and help new drugs reach the market by providing decision support in process development.
- Advanced therapies, such as gene and cell therapies, face intense pressure to optimize processes and reduce costs.
- Machine learning and AI can help pharmaceutical companies gain value from their data and reduce the need for extensive iterations in the lab.
- Sharing data within and outside organizations, as well as using digital twin technology, can further support the optimization of processes and real-time predictions.
- Industry 4.0 will see the increasing use of AI and machine learning to provide well-documented results and support human decision-making.
Conclusion:
The use of AI in advanced therapy manufacturing can help companies accelerate their commercialization strategies by reducing costs, improving process understanding, and enabling robust manufacturing. By harnessing the power of machine learning and data sharing, pharmaceutical companies can optimize processes and ensure timely delivery of personalized therapies to patients, ultimately improving patient outcomes and maximizing the value of their data.
