Big data is an industry which is under pressure to reduce research costs but improve outcomes at the same time. But, big data is proving to be a very valuable asset for any industries. However, data cannot lead to productivity by itself. It’s about how the data can be analyzed, to assist in making smarter decisions about medical interventions and improved treatment decisions.
Medical research is set to benefit immensely from big data. It has added new dimensions to medical research, as researchers are now able to predict recurrences and suggest preventive steps.
Streamlining medical research
In medical research, time is very critical. Before big data, it took very long time for researchers to receive the results of any research. However, the researchers can today access large volumes of medical records and test results in a matter of minutes. This helps them to make swifter and smarter decisions.
Big data healthcare research has assisted scientists at the London Institute for Cancer Research to reduce the time taken to conduct complex analysis of breast cancer cells. This time has significantly reduced from decades to months. The research, which was published in Genome Research, revealed that changes in the shape of the breast cancer cells lead to changes in genetic activity.
Here, the healthcare researchers used large data sets to identify these connections and discover how cell changes are connected to the clinical outcomes of the patient. Because of this, doctors can predict the severity of cancer, depending on the appearance of the cells. This helps them to choose the treatment accordingly.
Boosting the value of clinical trials
Since the introduction of the first clinical trial in 1747, patients were assigned to groups randomly. However, big data collected from EMRs, clinical trials and insurance firms is very powerful, less expensive and has enabled researchers to find the results very quickly.
For instance, the Harmony Project in Spain, which is a part of the IMI Big Data for Better Outcomes program. The project relies on big data analytics to create a European map of hematologic malignancies. These tumors are ranked third regarding death rates and fifth in regards to their frequencies.
Big data has helped researchers to determine the risk of a particular disease. According to the Occupational Safety and Health Administration, over half a million workers have been exposed to potential toxic laser and electrosurgery annually.
Researchers rely on big data analytics to transform large unstructured datasets into interoperable formats. This has helped them to predict the procedures which are likely to produce smoke, the effects of being exposed to the smoke and the necessary steps required to protect against it.
Even though the benefits of big data are commonly associated with progressions in treating humans, technology has taken the benefits a step further to animals used in clinical research. Once medical researchers evaluate big data, they can predict possible medical outcomes and modify the tests accordingly.
Big data analytics in biomedical research has made it possible to share large medical data sets. By doing this, biomedical researchers have become faster, thus reducing stress for the animals. The open source data analysis has enabled researchers to see virtual animal models replacing their living counterparts.
Integrating big data and the Internet of Things has led to other alternatives like wearable devices. These devices have helped researchers to monitor the effects of a drug on a particular animal in its natural environment.
Medical industry yet to catch-up
Big data analytics has the potential of leading us to biomedical research breakthroughs. However, the medical industry is yet to catch-up. The industry faces significant barriers when it comes to its readiness to capture big data. Some of these challenges include:
- A fragmented data infrastructure,
- Siloed or inaccessible data,
- Lack of adequate storage,
- Increasing concerns about de-identification of data and patient confidentiality.
If medical research teams can spend less time structuring and organizing the data, and spend more time focusing on its results and insights, big data has the power to change medical research.