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EMEA Thought Leadership
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
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EMEA Thought Leadership
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn more -
Middle East & Africa
EMEA Thought Leadership
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn more
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Automated intelligence as a catalyst for change: the complex impact of AI in life sciences
Jan 25, 2024
Artificial intelligence (AI) is driving a major shift in the life sciences landscape. Gone are the days of hesitant speculation; AI is now firmly embedded in the daily workflows of researchers, clinicians and industry leaders, revolutionizing the way we approach healthcare and scientific discovery. To unpack this dynamic landscape, BioSpace hosted a thought-provoking podcast series featuring Lori Ellis, Head of Insights, in conversation with two industry experts: Mike King, Senior Director of Product and Strategy at IQVIA and Matt O'Donnell, Industry Executive Health & Life Sciences at Microsoft. In the two-part series, they discuss the multifaceted impact of AI on life sciences, its potential to reshape employee behavior and its role as a driver for broader societal progress.
AI has created massive waves in the life sciences industry. It is changing not only daily operations but also employee behaviors; it is even posing as a catalyst for positive societal change. The progression of AI technologies such as generative AI has brought a much-needed learning curve for the industry. The field has gained a deeper understanding of AI and how it can empower the human experience and drive more customer-focused, productivity-boosting activities. In the healthcare industry these advancements ultimately bring about advancements in patient care and patient outcomes.
A deeper understanding
There has been a marked shift from the initial hesitation around generative AI’s capabilities to a focus on harnessing its potential to enhance the human experience. One of the biggest influences to reduce this hesitation has been the showcased potential applying the technology to industry specific use cases. Additionally, there has been improved awareness of traditional AI tools being integrated into pharmaceutical processes for some time, and it is key for industry to emphasize that these automated technologies are not entirely new to operations to build public trust. Trust is important for advanced AI tools, but it is important to note that risk must be evaluated. Generative AI cannot just be applied to broad healthcare solutions without any human oversight – the potential impacts of risks associated with AI can be substantial and require mitigations.
The learning curve for the potential of AI applications in healthcare has been vast. From adapting AI to new processes to recognizing the challenges of AI hallucinations, critical insights on the use of AI technology have emerged. Particularly as the use of AI within life sciences continues to grow and more innovative use cases appear, leaders must emphasize a human-centered perspective on the development of AI. It should be viewed as a copilot for employee activities rather than as a blanket replacement for industry professionals. The need for human review and oversight is one of the most important insights gained. For the foreseeable future, human review and oversight will be key to finalizing any data or output from generative AI tools.
The shift in employee behavior
The view of AI within life sciences has oscillated between ‘everything is a disaster’ and ‘everything is awesome.’ Organizations have implemented advanced technologies as a one-size-fits-all solution, but AI solution’s must be application-specific. By utilizing AI tools correctly, individuals can be augmented with AI – taking away the burden of manual, repetitive activities and increasing data mining capabilities by the use of a ‘digital eye.’ This allows for a greater percentage of employee time to be devoted to strategic activities that require skilled expertise. By empowering employees to focus on more rewarding activities, overall organizational satisfaction and productivity will increase and this could have a positive effect on employee retention and company culture.
A catalyst for change
The use of AI within the pharmaceutical field can help highlight existing biases as well as bring transparency to bias in order to empower organizations to confront these. For example, AI systems provide an opportunity for clinical trial sponsors to evaluate the quality of data to identify if any population segments have been missed or if there is bias within the data received. These details are critical for bringing products to market and addressing their safety profiles across a broad range of demographics.
If AI tools identify certain populations that have been missed, there may be underlying issues that are not identified prior to market use, leading to potential harm or adverse events. The right tools to extract the right data have the potential to bring about better, safer global products for all populations. Though there are potential risks in utilizing AI tools, they have the potential to bring about positive societal change.
For more insight into the enlightening conversations between Lori, Mike and Matt, listen to the BioSpace Denatured podcast here: Integrating AI in life sciences to change employee behavior with Microsoft and IQVIA and Fast and furious evolution: how to ensure AI is catalyst for positive societal change with Microsoft and IQVIA.Related solutions
SmartSolve eQMS
Connected, integrated, compliant. Build, scale, and optimize your quality and regulatory workflows with SmartSolve®, IQVIA's transformative Enterprise Quality Management System, built for Life Sciences.