Whether it be testing food, household cleaning products, or medications, toxicologists stay busy and work within many niches. The work they do largely determines what products we can use and how we’re supposed to use them. Not only do they test chemicals in the products they use, but many toxicologists also research the chemicals surrounding us.
Researching these chemicals takes a lot of time and resources, that is, until AI and smart systems have entered the field. Now, some toxicologists take advantage of artificial intelligence to quickly identify health hazards. However, AI is useful for much more than that.
Follow along as we take a deep dive into the use of smart systems and AI in toxicology.
The Role of AI in Toxicology
Toxicologists have more to do with public health than many people understand. They study the chemical and biological compounds around us and in the environment. Toxicologists also play a huge role in determining the effects and safety of pharmaceutical drugs.
Whether it be an environmental toxicologist or a pharmaceutical toxicologist, they can benefit from using artificial intelligence in many cases. Today, many toxicologists use AI to streamline their processes, assess risks, and analyze data. Using AI in toxicology not only saves time and money, but it also helps toxicologists reach meaningful conclusions more quickly.
The insights that AI can provide help toxicologists as much as they help the public. Detecting health hazards as quickly and efficiently as possible ultimately affects everyone, and AI can help with that. Smart systems and AI affect the way toxicologists detect health hazards in many ways, such as:
Discover and Understand New Drugs Before Clinical Trials
The process of developing new drugs typically goes on long before production is underway. Naturally, the process involves lots of research, trial, and error, which is why it takes so long. Unfortunately, that means it takes a long time for potentially life-saving drugs to hit the market and help people.
Today, toxicologists and developers can use AI to find new drug candidates much more quickly. More importantly, they can use AI to examine such drugs and determine their risks. If a substance seems too risky, they may either alter the compounds or move on to something else altogether.
This efficient process saves time and money, which are crucial in drug development. There is a reduced risk of dangerous clinical trials that could otherwise cause harmful side effects for participants. AI can ultimately help researchers and developers find strong drug candidates that are less likely to cause bad side effects.
Eliminate the Need for Animal Testing
For many years, animal testing has been a big part of toxicology and pharmacology. Researchers use animals to determine the dose of a substance that could be fatal for 50% of the test population. This is known as the LD50, and many people consider using animals to determine this to be quite cruel.
Luckily, the rise of smart systems, AI, and machine learning can largely reduce the need for animal testing in toxicology. Today, researchers can test a substance’s toxicity without resorting to animal testing. Drug developers can even determine a substance’s toxicity in the early stages of development.
Not only does this prevent animal testing, but it can also make the development process much easier. AI has its own ethical implications, but the prospect of stopping animal testing is enough to get many people on board. Some animal testing may still go on, but there is much less trial and error, meaning that fewer animals may be tested on.
Ensure Accuracy
Working as a toxicologist is a big responsibility, as their work goes hand in hand with public safety. Toxicology has evolved a lot in the past few decades, and a lot of that has to do with technology. Now, the rise of smart systems helps ensure accuracy and speed in toxicology.
That’s because toxicologists can now assess risk and probability much more easily. This provides more data that toxicologists can use to make informed decisions, which ultimately affect public health. Of course, toxicologists must still work hard and conduct research and tests.
However, the predictive nature of AI and many smart systems can help toxicologists narrow their focus, so they don’t waste time. The extra data and knowledge that AI provides make toxicologists even more accountable, as they now have a safety net. This unparalleled accuracy doesn’t replace the need for toxicologists, but it equips them with new, invaluable tools.
Improved Transparency
Transparency is everything in toxicology, as a toxicologist’s findings can affect the health of large groups of people. AI can help provide transparency in case studies and clinical trials, but only when using advanced smart systems. Some AI systems simply generate results without providing an explanation or any data, which is largely useless.
However, advanced systems can provide deep explanations about the information they generate. This can include data and information that can recontextualize a toxicologist’s findings. Now, toxicologists can include this data and information in their reports, which is helpful when made public.
Of course, many people don’t trust AI and would rather see the toxicologist’s findings. Luckily, using AI doesn’t render the toxicologist’s findings and assessments useless. Instead, toxicologists can use this information to aid their research and even explain it to the public. Data sharing can help people feel more comfortable about the substances around them in the environment and in their medicine cabinets.
The Role of AI in Toxicology Can’t Be Understated
Toxicologists have saved countless lives through their hard work, research, and discoveries. That’s because they’ve always kept up with new developments, methods, and technologies. Today, AI is the biggest development in toxicology, and embracing it is essential to ensure public health.
Gaining insight into new environmental chemicals and experimental drugs before testing them can save time and money. AI helps toxicologists learn more about their findings and identify risks without testing chemicals on animals. Smart systems and AI still feel new in the toxicology field, but that’s because they keep getting better and more efficient.
About the Author
Ryan Ayers is a researcher and consultant within multiple industries, including information technology, blockchain, and business development. Always up for a challenge, Ayers enjoys working with startups as well as Fortune 500 companies. When not at work, Ayers loves reading science fiction novels and watching the LA Clippers.
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