How Technologies are Impacting the Life Sciences Industry
By Jeremy Williams, Life Science Review
| Saturday, January 23, 2021
The life sciences industry is applying emerging technologies as it is helping them to grow and creating many opportunities in the medical field.
FREMONT, CA: The life sciences industry has always been driven by research and innovation. Today, it’s still rapidly advancing because of ground-breaking drug development, medical advancement opportunities, and massive investments to accelerate drug launches. Along with a considerable amount of investment in drug discovery and research, life science organizations are also taking the initiative to change business intelligence, analytical abilities, and data management. They are doing this by embracing artificial intelligence (AI), natural processing language (NLP), digital transformation, automation, and machine learning (ML).
In the recent few years, life science organizations have prioritized heavily on digitalization, IT infrastructure, and cloud regardless of their size. Furthermore, most large-scale life science companies consider replacing traditional technology-based solutions with cloud-based scalable equipment. The market researchers predict that life science companies will focus more on data management, AI, data strategy, automation, and analytics in the future.
Here are some of the new data technology trends that are impacting the life science industry
CONTINUOUS FOCUS ON DATA QUALITY
The life science industry prioritizes IT applications, producing data quality reports, highlighting adverse impact notification, gathering data quality statistics, and enabling automated alerts.
Furthermore, the data stewards, business users, and even executive users search for data quality reports before they start depending on business dashboards. The life science companies are also investing in automated and configurable data quality solutions to become easy for them to adopt any business changes. The industry's primary reasons to focus on data quality are related to lack of visibility on data quality, low data quality, and limited and manual validations.
CHANGING OPERATIONS INTO A DEVOPS CULTURE
The emerging trend of AI and ML is becoming popular among life science companies because they can automate DevOps, making them more technology-driven and helping them achieve the following results.
• Dealing with technology transformation as a continuous journey of improvement
• Monitoring and rewarding cost rationalization with innovative and reinvesting in automation
• Better quality of code and rapid recovery from application failures
• Establish trust with an innovative-driven culture in IT Operations
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