Big Data to help pharmaceutics
Creation, testing and industrial production of pharmaceuticals are expensive. Besides, the end justifies the means far from always. Mistakes in calculations, research delaying and other troubles sometimes make pharmaceutical companies suffer serious losses. However, the Big Data technology is able to simplify the work significantly.
For instance, it will allow to:
- speed up the clinical investigation process (companies will be able to look for the most eligible volunteer patients for participation in medical experiments in real-time mode);
- establish efficient communications (one will be able not only to collect but also share data, obtaining new information and keeping in contact with other companies or independent scientists);
- improve pharmaceutical product sales (for example, the Big Data analysis will allow companies to select customers who need their solutions more than others);
- predict the efficiency of drugs (using the predictive modelling, pharmacists could select drugs for patients based on their genetics, disease history, and lifestyle).
What does prevent Big Data from being implemented into pharmaceutical sector?
As mentioned above, the development and production of pharmaceutical drugs require lots of money. But today, Big Data implementation will also require great investments from companies. They will not only have to pay for the technology but also significantly change common operational concepts, which requires efforts as well.
The need for privacy protection also prevents companies from implementing innovations. Unlike the analogue processes in other industries, the pharmaceutical sector potentially may reveal patient personal information.