Intelligent Automation for Life Sciences Quality Operations

Intelligent automation offers innovative tools to help life sciences firms achieve increased efficiencies, reduced costs, improved customer service, and minimized risk in the changing times.

FREMONT, CA: Over the past years, technology has played a leading role in driving life sciences innovation and created significant disruption in the quality operations environment. One of the many revolutionizing technologies – intelligent automation – has become an inseparable part of life sciences business functions. From mitigating costs to simplifying data collection between different systems, intelligent automation presents several opportunities to enhance quality and efficiency. Many intelligent automation powered functions will improve the quality unit. Here are some quality areas where intelligent automation can drive beneficial outcomes.

• Audits

Intelligent automation technologies can help confront the trials of compliance effectively in the modern digital era. This includes automated response tools, non-conformity identification, and real-time monitoring. Artificial Intelligence that utilizes natural language processing and speech recognition can significantly decrease audit cycles, enabling more time to focus on preventive and corrective actions for identified compliance issues.

• Training

Today, quality leaders in the life sciences are slowly deploying machine learning for training to be more stimulating and resourceful for the employees.  

The use of machine learning can enhance the instructional content and deliver enhanced visual and auditory responses, which can then offer enriched personalized performance coaching to the learner.

• Quality Assurance

Intelligent automation technologies like machine learning and computer vision can help automate routine tasks like identifying defects and quality issues. These tools can identify quality issues by using camera systems that are extremely sensitive, exceeding the human eye's potentials. The data collected by these technologies can be analyzed in real-time to power operational process improvements.

• Forecasting

Intelligent automation technologies can help life sciences quality leaders with constructing more accurate forecasts. Deep learning and deep neural technology can envisage the voice of the customer. This further enables organizations to meet forecasted, and urgent customer needs. Within the supply chain, intelligent automation can help identify patterns of product demand. The technology can then make automatic adjustments happening due to disruptions and market changes.

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