Big Data and Medical Research
Big data has many applications, but perhaps one of its most important uses is its potential to advance medical research, in turn, contributing to improving the quality of human life. Here, we will look at some of the ways big data is advancing medical research and healthcare:
Regional Healthcare Monitoring
Data can be utilized for the purposes of predictive medical research, thus aiding in the prevention of the spread of possible diseases. For instance, understanding patient populations and their healthcare needs by tracking the medical questions they search for as well as tracking the information they provide on medical sites is one way of furthering preventative care and research. This data has the potential to better predict regional outbreaks of various conditions and current public health concerns. In turn, healthcare providers are able to take adequate preventative measures and allocate the necessary resources to combat the regional escalation of a particular disease of health-related ailments. This was seen in 2014 when the Center for Disease Control utilized big data through a tool called “BioMosaic” to effectively track the Ebola outbreak, identify populations at risk, and prevent its spread.
Combating the Spread of STDs
Sexually transmitted diseases (STDs) and sexually transmitted infections (STIs) can be treated if reported in a timely manner. But issues like stigma, lack of sexual education, and more, often result in symptoms going unchecked. Big data can tap into local experiences and help both tech companies and healthcare providers fill information gaps and spread awareness about sexual health. For instance, Google shares user data with researchers to better monitor STD/STI rates. The aim here is to monitor user data in real-time so that researchers can be well-equipped to prevent widespread STD/STI outbreaks.
Additionally, accessing this information generates a large volume of data that can be analyzed by medical professionals to predict patterns amongst infected people, and pinpoint stages wherein disease testing as well treatment is most effective. This is especially handy as different STIs have different optimal testing and treatment times, depending on their incubation periods. In turn, this helps ensure strategic planning of treatment protocols as well as increase the chances of treatment success in those who are already infected.
Improving Pharmaceutical Drug Creation
It’s no secret that drug production is essential to the future of humankind. However, drug discovery and creation is only the first part of the process. For a pharmaceutical drug to be accepted into the market, it needs to go through multiple rounds of stringent testing. Testing new drugs is a challenge faced by pharmaceutical companies the world over, due to everything from strict legal protocols to finding patients who are willing to test new drugs.
Big data is useful here, and can significantly speed up the process and feasibility of drug testing through algorithmic procedures and machine learning. As opposed to carrying out actual lab experiments, big data facilitates computation drug discovery, allowing dug creators to apply data applications in the drug development process. Based on this, pharmaceuticals can build realistic models and simulations to test their products.
Improving Healthcare Support Systems
One of the chief advancements in medical technology is in healthcare robotics, which is expected to grow to $2.8 billion in revenue by 2021. Healthcare robotics includes specialties like surgical robot training, robotic nurses, smart prosthesis and bionics, as well as assistance in therapy, pills, telepresence, and logistics. The use of robotics powered by big data has the potential to greatly improve the quality of healthcare support, as is already being seen through few well-known robot nurses such as Robot Dinsow, who monitors patients and reminds them of medication; and Robot Paro who extends virtual relaxation and alerts caregivers. In general, data-powered robotics in healthcare is extremely useful for performing repetitive tasks like medication delivery, as well as assisting in staff training and healthcare education.
Today, the use of big data in medical research and advancement is of paramount importance. Artificial intelligence and machine learning are pioneering the ethical collection of medical data, the discovery of new drug therapies, and improved outcomes for patients. By analyzing public health concerns in real-time, big data can advance medical research in multiple fields, improve patient care, and prevent the spread of deadly diseases.