AUTOMATION
How and Why Pharmaceutical Manufacturers Are Applying Artificial Intelligence DAVID GREENFIELD, DIRECTOR OF CONTENT, AUTOMATION WORLD TOP THREE TAKEAWAYS 1. The pharmaceutical industry seeks to optimize production with AI but has a long road ahead.
2. Advanced analytics are on the rise for creating opportunities to reduce manufacturing costs.
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dvances in the application of artificial intelligence (AI) are starting to have a significant impact on automation technologies used across industry—most notably with machine vision and analytics. And some of the more impactful applications of AI are happening in the pharmaceutical industries. It shouldn’t be too surprising that the pharmaceutical industries are looking to optimize production with AI, considering that single batch values for some drugs can exceed $3 million. Yet, research indicates that this industry lags behind many others when it comes to using analytics to improve production. According to David Leitham, Senior Vice President and General Manager, Pharmaceuticals, at Aspen Tech (a supplier of AI software for industrial manufacturers), while other industries have been
3. Pharma success stories find that AI applications reduce downtime and prevent production losses.
applying analytics and predictive capabilities to optimize performance and react rapidly to changes in demand, 87% of pharmaceutical industry executives admit their organizations have a poor digital culture. The data Leitham references comes from an AspenTech survey of 300 senior pharmaceutical executives in the U.K., U.S., Germany, France, Spain, and Sweden. This same survey also shows that 49% of respondents admit struggling to use data to improve time to market for their products. “COVID-19 not only triggered a rush to develop a vaccine, it had serious impacts on demand for drugs already in production,” said Leitham. “The whole velocity of the market has accelerated—but our research reveals that the pharmaceutical industry has much farther to travel before it gets up to speed.”
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Asset management, predictive maintenance, and analytics
↑ Pharma companies are turning to AI for production optimization.
Two areas of AI application focused on by pharmaceutical companies include asset performance management tools using advanced analytics to create manufacturing efficiencies and predictive maintenance systems to analyze failure patterns and provide anomaly alerts and advance warnings of pending equipment failures. “Opportunities to reduce manufacturing costs exist across all stages of the product lifecycle. Advanced analytics can reveal those opportunities, allowing pharma companies to take informed action to save money,” said Richard Porter, Global Director, Pharmaceuticals, at AspenTech. “Whether using multivariate analytics to identify process degradation and its impact on quality or predicting final product quality to reduce lab testing lag times, these techniques offer pharmaceutical companies a competitive advantage.” Porter also noted that multivariate analytics software can be
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