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Will AI Play an Important Role in Quality Assurance and Quality Control Careers?

pharmaceutical quality assurance and quality control

The pharmaceutical industry is deeply connected to the technology sector, and frequently benefits from technological innovations and discovery. One particular sphere of technological innovation that has been making waves in many industries, including pharmaceuticals, is artificial intelligence (AI). Artificial intelligence is a broad term that refers to computer systems that perform tasks that would normally have required human intelligence. Practically speaking, this includes tools and methods like machine learning, neural networks, and more.

As a student pursuing a career in the pharmaceutical industry, you may be wondering: How could AI impact my career path? Keep reading to learn more about the impact of AI on pharmaceuticals, and potential effects on pharmaceutical quality assurance and control.

Artificial Intelligence Is Reshaping Pharmaceutical Research and Development

Currently, the area of pharmaceuticals that is seeing the greatest impact from AI is research and development. More specifically, many drug companies and researchers have begun to use AI to aid in the process of drug discovery, and more carefully predict what kinds of drugs will be the most effective for particular patients and health conditions.

pharmaceutical quality assurance training

Drug discovery is taking new directions with the assistance of artificial intelligence

AI is capable of processing data at speeds and in quantities that would be unrealistic for humans to do themselves. One exciting example of this principle being put to use is Pfizer’s partnership with IBM on Watson for Drug Discovery. Watson, IBM’s famous computer, is being used to identify potentially effective new cancer therapies. Instead of the 200-300 articles that a human researcher could review in one year, Watson for Drug Discover has combed over 25 million Medline article abstracts and 1 million medical journal articles in the hopes of finding better treatments for cancer patients. With Watson’s help, pharmaceutical professionals could focus on more promising prospects, potentially bringing even more drugs and treatments to market.

Cross-Company Pharmaceutical Quality Assurance and Quality Control With AI

The benefits of AI do not seem to be limited to research and development. In fact, they have already started to become evident in the pharmaceutical quality assurance and quality control process.

Generally, pharmaceutical companies have used “bands” of acceptability to determine whether a product fits within quality specifications. However, these bands by their nature are not as precise as they could be. With AI, products can be tested consistently across different companies with data-driven structures that can more accurately predict how small product variations will impact safety and sales performance across a wide range of markets and types of consumers. This is exciting news for students interested in pharmaceutical quality control careers, and evidence that AI is a phenomenon you might use in your career to boost accuracy and produce even better products.

AI’s Impact on Quality Assurance and Quality Control Methods Remains to Be Seen

With all of these interesting developments in mind, there is still much that remains to be seen when it comes to the impact of AI on a student’s quality assurance and quality control career. Much of AI’s influence is still concentrated in research and development processes, and AI in general is still a discipline that is quite expensive and difficult to predict.

Quality control and quality assurance students can nonetheless keep an eye on AI developments that are relevant to the pharmaceutical industry. With the right training program under your belt, increased technological capabilities in the industry will only bolster your ability to work effectively.

Do you want to know more about what your future in the pharmaceutical industry could look like?

Contact us at AAPS to learn more about our pharmaceutical quality assurance training program.

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