Data Mining in the Pharmaceutical Industry

Big Data can help in a range of steps included in clinical trials such as patient profiling so as to identify the right candidates through analytics of demographic information and historical data, assessing medication availability, surveying past clinical trial events, intervention for appropriate drug dosage, and remote patient monitoring. Moreover, it helps recognize the possible adverse and undesirable effects of a new drug even before they are

Data mining is a very useful business strategy that allows companies to improve their business model and overall

Data mining companies and pharmaceutical manufacturers are able easily access information about physicians’ prescribing behaviors. For instance, IMS Health, an American healthcare IT company, sends weekly updates to pharmaceutical sales representatives outlining the drugs that physicians prescribe. Data collected over time can reveal a physician’s prescribing history, his or her preference for brand-name drugs, and the probability of prescribing new drugs. The data can help pharmaceutical companies identify which physicians prescribe their companies’ drugs and can reinforce the physicians’ choices if needed. Drug companies are able to find out exactly when a physician

It became an issue for consumer, and they felt uncomfortable due to companies invaded consumers privacy without their consent. Another issue regarding data mining is there no clear policies around how the company uses data once they have collected the information. After Target received negative publicity regarding its original data mining approach, they change their strategy by mixing all their ads, so it not that obvious that they were spying on them. It makes customers’ to assume that everyone else gets same coupons and ads. Data mining has given Target awareness into the relationship between product sales and online reviews. Target retailers identify guests how write reviews, examining their history of purchasing and invited to write review on their products. This program was highly successful, leading Target to obtain incremental reviews and increase sales of those key products. More importantly, data mining has empowered companies to find new opportunities for growth, make better decisions to succeed business goals and safe money. The retailer industry utilizes data mining and customer analytics to support customer decisions. Exploring how collected data can be manipulated to identify customers buying patterns and increase profitability is a growing business

Data mining is another concept closely associated with large databases such as clinical data repositories and data warehouses. However data mining like several other IT concepts means different things to different people. Health care application vendors may use the term data mining when referring to the user interface of the data warehouse or data repository. They may refer to the ability to drill down into data as data mining for example. However more precisely used data mining refers to a sophisticated analysis tool that automatically dis­ covers patterns among data in a data store. Data mining is an advanced form of decision support. Unlike passive query tools the data mining analysis tool does not require the user to pose individual specific questions to the database. Instead this tool is programmed to look for and extract patterns, trends and rules. True data mining is currently used in the business community for market­ ing and predictive analysis (Stair & Reynolds, 2012). This analytical data mining is however not currently widespread in the health care community.

The wide goal of a medical decision support system is to provide either direct or indirect assistance in medical decision making by exploring an extensive medical knowledge base. Data mining takes a key role in knowledge discovery process in medical databases. For example, with rising popularity of gene therapy the data mining has been used widely in the genome mapping process. Identifying the disease causing gene is a primary objective of drug companies [20].

Data mining software allows users to analyze large databases to solve business decision problems. Data mining is, in some ways, an extension of statistics, with a few

Kudler is looking for ways to increase sales and customer satisfaction. To achieve this goal Kudler will use data mining tools to predict future trends and behaviors to allow them to make proactive, knowledge-driven decisions. Kudler’s marketing director has access to information about all of its customers: their age, ethnicity, demographics, and shopping habits. The starting point will be a data warehouse containing a combination of internal data tracking all customers contact coupled with external market data

Data mining uses computer-based technology to evaluate data in a database and identify different trends. Effective data mining helps researchers predict economic trends and pinpoint sales prospects. Data mining is stored in data warehouses, which are sophisticated customer databases that allow managers to combine data from several different organization functions.

When consumers shop online, data mining is collecting their buying habits and other online searches. With every search they do, their information is collected by companies as Acxiom. These companies collect data such as age, race, sex, education

Currently in the healthcare field, there is a big revolution underway. In years leading up till today, pharmaceutical companies and other medical research entities have been collecting years of research into medical databases. The amount of data available for research is massive. What to do with such vast and large amounts of data is the question. With such large amounts of data available, the need to analyze this data is imminent.

Today, the world’s trend in operating business focuses on data availability to enact the best suitable decision to improve, develop, and increase business revenues. Moreover, the availability of data helps to monitor and control the quality of provided products or services. However, the availability of data without proper analytics operations would have no meaning (1). Data analytics provide an important aid to an organization to figure out their position in the market in comparison with their competitors. Also, data analytics helps to identify what is the organization’s competitive ability in the market, what they should bet on, and what they should strive for. With that being said, many of today’s most successful organizations utilize

As coined in an article in the St. Louis Post-Dispatch by Aisha Sultan, “Data is the new world currency.” Data mining is the process of analyzing data from different perspectives and then summarizing it into useful information. In essence is it applying all different types of what if scenarios on large swaths of data to get possible results to aid in better decision making. This sort of decision making isn’t something new, it’s the technology aiding the decision making that is new. This has reduced the amount of time it takes in the decision making process and given the

45. Data mining provides organizations with an indispensable decision-enhancing environment to exploit new opportunities by transforming date into a strategic weapon

Since higher education has blurred the lines with traditional businesses, it is important to have the tools to assist them with valuable data and information, in making decisions. Using of data and having the right data mining tools can insure the institute’s success, in many forms, such as, identifying market trends, precision marketing, new products, performance management, grants and funding management, student life cycle management and procurement to mention a few. To get a better grasp on these benefits it’s important to understand data warehouse, data mining and the associated benefits.