How Artificial Intelligence Will Revolutionize Safety
Tuesday December 18, 2018
On June 20th 2018, the Oracle Health Sciences Global Business Unit hosted a webcast titled “How Artificial Intelligence Will Revolutionize Safety”. Leading experts within the industry, Bruce Palsulich, VP of Safety Product Strategy, and Rave Harpaz, Sr. Director of Research and Data, discussed how artificial intelligence (AI), and machine learning (ML) are poised to change the way we conduct safety measures while meeting productivity goals.
Many industries, including the life sciences, are experiencing pressure for increased production and distribution. Life Science organizations are looking at innovative research, accelerated new drug development, incorporation of technology, etc., to help achieve ever-demanding business goals. However, safety remains one of the main priorities within the industry.
Increasing Business Productivity With Artificial Intelligence
AI machines can do routine case processing (meaning the “end to end” flow) that does not require intervention by a human, and in most cases, results in better quality and consistency. The pharma industry for example has an obligation to attain and maintain regulatory compliance as well as drive cost effectiveness by utilization of AI. This may require that additional focus be placed on the proper assessment of risk.
But AI goes beyond just your basic robotic tasks. Using a set of neural networks, AI can mimic the functionality of humans by processing large sets of data and then using ML to arrive at independent conclusions. Firms are expanding AI applications across the product lifecycle to achieve operational productivity in order to attain volume goals. This industry involves a huge amount of data, both structured and unstructured, and to manage this data better, AI is the route to go. The reason for this is because AI and ML can pick up trends, patterns, and correlations that would have been otherwise missed. It also helps improves processes (and costs) through the analysis of large groups of data that would have taken humans much longer to accomplish.
AI Advantages Over Traditional Analytics & Clinical Decision Making
AI offers several advantages over traditional analytics and clinical decision-making techniques. Learning algorithms can become more precise and accurate as they interact with training data, allowing humans to gain unique insights into diagnostics, care processes, and patient outcomes. One of the biggest challenges for AI implementation is that the complexity involved has meant that there exists a shortage those who are skilled in this field. This is especially true in the life sciences industry which is constantly updating and improving.
The Arbour Advantage
Arbour Group has been a trusted advisor to over 250 life sciences companies. We can ensure that your IT policies and procedures contain the appropriate depth and breadth of coverage that will ensure regulatory compliance and reflect industry best practices. For more information, contact Arbour Group today!