Typical Vaccine Manufacturing Processes and How AI can help Speed up

AI plays a crucial role in anomaly detection, predictive maintenance, and enhancing quality testing processes.

Human errors often lead to low success rates.

AI can significantly reduce processing time and enhance speed through anomaly detection, resulting in fewer failed batches. It can also expedite quality control procedures, reducing long lead times. Additionally, AI-powered data fusion aids in swift regulatory filings.

Typical Processes before product is released for use and how AI can help speed up

AI-MLūü°ļ higher yields, Less batch Loss

Time Saved: Could be 3-6 months

AI-ML based Quality Control:

Typical lead time is 4 months, The AI-ML can reduce the time needed to 1 month and higher accuracy

Our Estimate of time that could be saved by implementing AI/ML

Base case: 14-16 Months

6 Months in Process Development

3 Months for initial Engineering Batches

1st Batch 35 days

Batch review and QC/Stability- 120 Days

AI/ML Powered- Vaccine Production: 6-8 Months

3 Months in Process Development (Anomaly detection, yield optimization)

2 Months for initial Engineering Batches (Trend Analysis, Yield Optimization)

1st Batch 35 days (Batch failure reduction, Higher yields, Predictive Maintenance)

Batch review and QC- 30 Days

Details can be provided details for each AI application, such as Data Fusion and Anomaly Detection, and explain precisely how they accelerate processes