Intelligent Manufacturing in Life Sciences
Optimization of the drug supply chain using AI
Modern drugs are often produced across many manufacturing plants that are often globally distributed. Further, more and more drugs are produced by a consortium of companies or via contractor companies. A vaccine is manufactured in one location and has to be transported to another location to finalize the production. From there its distribution across the world is organized. As supply chains are becoming more complex they are more prone to errors and shortcomings.
Applying artificial intelligence to biopharma manufacturing facilities and processes enables life sciences companies to stream factory and sensor data to analytics engines which generate novel insights. These insights can then help companies predict process bottlenecks, identify quality control issues, and proactively suggest corrective actions. Companies can also use AI to better predict demand and supply, recommend the next best action to supply chain operators.
Modulos AutoML makes it easy for supply chain engineers to find the best ML algorithms by automating the process of feature extraction, hyperparameter tuning and model selection. This enables supply chain engineers to combine their own domain expertise in their industry with Modulos’ expertise on ML to optimize the drug supply chains.