Intelligent Predictive Modeling Using Big Data for Drug Selection in Pharmaceutical Industry
Main Article Content
Abstract
In Pharmaceutical Industries huge amounts of structured, unstructured and semi structured data have been generated. This data is heterogeneous in nature and can be referred to as Big Data. There is a need to manage and analyze this data for taking various decisions regarding drug selection. There are various big data analytical tools and techniques exist with the help of which we can analyze massive amount of data. In this paper we discuss about the various tools and techniques available to analyze the data and selecting the best tool for carting out the predictions regarding right product (drug) selection.
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
