π Digital twins allow real-time modeling of processes, facilitating automation and optimizing performance.
π‘ Beyond process development, they streamline operations from R&D to production, reducing costs and time to market.
π AI is expected to further integrate and automate these systems, enhancing efficiency and product quality.
Introduction:
The article discusses the transformative impact of artificial intelligence (AI) on the use of digital twins in the biopharmaceutical industry. Digital twins, which are virtual models that replicate manufacturing processes, are becoming increasingly sophisticated and are being integrated across various stages of drug development and production, leading to enhanced efficiency and productivity.
- Digital twins initially served primarily in process development, but their applications are being expanded throughout the entire biopharmaceutical development chain, improving predictability and reducing experimentation time.
- They assist in commercial manufacturing by enhancing operational excellence, facilitating predictive reliability, and improving product quality through simulation and testing.
- Recent advancements have enabled digital twins to function as “soft sensors,” allowing real-time estimations of difficult-to-measure attributes, which allows for better process control.
- AI is facilitating the automation of digital twin modeling, significantly reducing the effort and time required for implementation, and leading to more robust models.
- The future of digital twins is expected to feature greater integration and autonomy, transforming from single-process models to comprehensive βdigital threadsβ that span the product lifecycle from research through to supply chain logistics.
Conclusion:
The integration of AI into digital twin technologies presents a promising future for the biopharmaceutical industry. As these tools continue to evolve, they will enhance efficiency, drive autonomous operations, and expedite the delivery of crucial therapies, ultimately revolutionizing manufacturing processes and product lifecycles.
