Generative AI is a type of artificial intelligence that can create new content based on existing content or data. The algorithm is developed by compiling large amounts of data, which serve as the foundation from which the AI model will learn. It functions by utilizing these algorithms to generate outputs that previously would have required human inputs. These outputs may include images, music, text, software, and graphics. Curious about how Generative AI could be applied? Download the eBook below as we explore use-cases for product quality and GxP compliance.
How Does Generative AI Work?
A generative AI algorithm analyzes the patterns and relationships within the data to compile the variables controlling its content. The AI model continuously refines its parameters to simulate human-generated content. As the AI generates more content, its outputs become more sophisticated and human-like.
Despite the many potential positive applications for generative AI, there are also downsides and dangers. Generative AI has the potential for spreading misinformation, malicious, biased, or sensitive content. In response to these dangers, in April 2023, the European Union proposed new copyright rules for generative AI that would require companies to disclose any copyrighted material used to develop these tools.
Generative AI, Product Quality, and GxP Compliance
Given the widespread applicability of Generative AI, the question arises as to whether potential practical applications to product quality and GxP compliance exist. Although not yet a common application for Generative AI, product quality and GxP compliance may be able to benefit from its use. Practitioners usually rely on their own experience and expertise to formulate their approaches to the specific situation, such as developing proactive processes or remediating existing ones. Typically, at most, these practitioners may consult with a colleague(s) for additional input and/or to corroborate their own approaches.
The result is that the resolution to any given situation is limited by the expertise of the person(s) doing the work, with possible input from an additional person(s). Perhaps generative AI solutions could be developed that utilize the collective wisdom and experience of many subject matter experts as well as available historical information. These solutions would then be able to provide a more comprehensive set of options as well as tailored solutions to the situation at hand. In this eBook, we dive into some areas for consideration and examples of how Generative AI could be applied.
The Future of Generative AI for Product Quality and GxP Compliance
As is the case with the effective adoption of nearly any new technology, detailed analyses need to be performed to determine the suitability of generative AI to the specific application. Given the reality of busy schedules and competing priorities, it’s easy to postpone or ignore investigating application possibilities. Doing so may result in missed opportunities for significant benefits and losses due to competitors capitalizing on the opportunity.
Generative AI should be viewed as a useful tool to be leveraged strategically by those in product quality and GxP compliance, particularly in an increasingly digital, complex, and evolving landscape. Best practices as to how it’s developed and deployed in the areas of product quality and GxP compliance are far from fully established. Generative AI is expanding rapidly into the life sciences, and it’s important to understand its implications and how it can be best integrated into your specific situation. Our team of consultants has the expertise and experience to assist you with navigating the future of generative AI in product quality and GxP compliance.
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