Users generate petabytes of data every hour. This data is ridiculously huge and mind boggling to comprehend. Though we have extensive methods which can take care of processing the data, still we see that the rate at which this is processed is way slower than it should be. Big Data is one such technique which can accelerate the process of data comprehension though the data inflow is constantly increasing. One of the most challenging task is to organize data from life science research. This is hard due to two important reasons, first the data is insanely huge and the second is that the calculations required are complex and takes time. However, organizing such kind of data into rows and columns is not an easier task. This whole process is optimized by involving Big Data techniques coupled with AI (Artificial Intelligence).

Here are Five Ways in which Big Data and AI will impact Life Sciences Firms:

1. Many have already forecasted that 2018 will be the year of AI. As a matter fact 2018 will be a home to many emerging technologies including IoT and 5G. The number of healthcare devices connected to the internet will drastically increase and this data will also add onto the existing petabytes of data derived from drug research or protein analysis, or DNA structuring. It is extremely important to have correct predictions and values regarding life sciences because one mistake and it can cause someone their life. When Big Data is coupled with AI, the accuracy is predicted to increase and also the amount of human intervention decreases. This also makes the drugs and other products manufactured less expensive
2. The quality of research will highly improve with the patient feedback. IoT enables the researchers and doctors to access the patient’s status in real-time which makes it much easier to access the data. The received data can be seamlessly processed using Big Data and AI
3. These two emerging technologies give hope to underappreciated research projects due to lack of sound technical support. Genetics is one of the areas of life sciences which can highly benefit with this kind of support. The data involved in the research is so huge that it can take days to compile everything.
4. Clinical trials will be more prevalent since the data can now be analysed faster and efficiently without the need of high functioning hardware. Still the infrastructure needed to make this happen is huge, but the efficiency outweighs the investment.
5. EMR (Electronic Patient Reports) are stored in hospital computers and with the help of cloud, Big Data and AI we can predict the condition of the patient and change the treatment accordingly. This can also predict the viability of certain procedures and success rate in treatments. If needed these details can be seamlessly transferred to the current hospital in which the patient is admitted.

No doubt Big Data has conquered the world of data organizing and predicting. It has impaled the need to be statistically well versed in mathematics to perform complex predictions. With much simpler algorithms and robust hardware support Big Data and AI will greatly affect the way we conduct research and analysis in Life Sciences Firms in 2018.