4 Ways Big Data Will Disrupt Animal Testing in Biomedical Research
Big data is useful in all human endeavors. But the healthcare sector seems to pay more heed to the possibilities presented by big data. While the nature of the challenges big data aim to tackle in human healthcare industry might be different from that of the animal healthcare, the possibilities that medical practitioners and suitably qualified persons (SQP) in the animal healthcare industry can achieve with the gamut of valuable information from data are similar.
For example, the biomedical industry may not be totally concerned about how to keep a particular breed of animal from going into extinction as they would be about gaining approval to test a new antiretroviral medicine on them. But both the medical agents and the SQP could share data sets that would support the growth of the medicine industry.
In the pharmaceutical industry, a drug has to pass an animal test before testing is done on a small group of human volunteers. This makes using big data to validate claims and put concerns to rest the best approach. The following ways are how big data can support biomedical research that involves lab animals.
1. Data makes authorization seamless.
In biomedical research, where conducting tests that will impact the success of a drug on animals first is the norm, gaining approval for lab tests on certain animals such as the chimpanzee or rabbit can benefit from data.
From the lab animal identification process to analyzing complex data to formulate test results, the process for conducting tests on animals in the lab must be guided. Thus, the data generated independently by SQPs can be used to validate the tests carried out by the biomedical experts for future authorizations.
2. Speedy results.
With data, gone are the days where the biomedical research team has to wait for ages before results are seen. A pool of data can be immediately analyzed and the results collated and sent for further investigation. This will make efforts in biomedical research even faster and less stressful on animals.
With the traditional method of carrying out tests on animals, results can take longer than most animals can withstand, which puts their health at risk. Streamlined data, on the other hand, makes results readily available -- and with minimal stress on test animals results can be concluded and research will move to the next stage.
3. Reactions can be followed when tests are over.
Drugs often cause unexpected reactions in subjects. Even well-tested drugs.
The aim of carrying out tests on animals before drugs are approved for human use is to prevent drugs from causing harm to a human being. But drugs with delayed reactions such as allergic symptoms that would only surface weeks after the subject has taken the drug may pose a health threat to humans.
With continuous data collection, animal health SQPs can assist human medical practitioners with information that will be useful in determining if the use of a new drug will pose a potential future threat.
Animals can be safely returned to farm -- their natural habitat, and with animal wearable technology placed on tested animals, data can show if there are any reactions.
4. Data can aid tech in safer animal testing.
With improvements in technology trickling down into animal healthcare sector, big data will become even more valuable to tech companies. By analyzing previously generated data and factoring needed changes into new technology developed into biomedical research tools, tests can be safely carried out on animals without impacting their quality of life.
Manufacturers can rely on big data to develop meaningful futuristic wearable technology that animals can be fitted with.