Best Ways Pharmaceutical Companies are Using Data Analytics to Drive Innovation & Value-converted

1. Title: Best Ways Pharmaceutical Companies are Using Data Analytics to Drive Innovation & Value Did you know? "You can get data without information, but you can't get information without data." This quote by programmer and science fiction writer, Daniel K Moran, holds especially true in the 21st century. From governments and institutions to businesses and corporates, data analytics plays a huge role in every industry, including the Pharmaceutical Industry. Pharma companies use analytics to drive change and value, and generate success on a global level. They use this information to recognize patterns and trends, test out theories and see the efficacy of drugs and treatments. Now information can be disseminated like never before, and any Medicare business can charter a course towards discovery and innovation. Why is Analytics in the Pharmaceutical Industry needed? Here are just a few key ways in which insights can help: • Recording patient information is easier, quicker and more organized. • Predicting health risks and trends gives insights on the needs of the market. • Tracking drug performances and market response help fuel sales efficiency. • Faster creation and marketing of targeted medicines. • Reduced cost with greater utilization of resources. • Streamlining clinical operations and processes. Best ways in which Advanced Analytics in Pharma is helping corporations grow: 1.Fast and continuous drug discovery and development: The health and pharmacology sector invests heavily on their products. Just bringing in a new drug into the market can cost over $5 billion! That pushes organizations to examine previous test results. The analysis of big data can help accelerate the process of discovering new medicines or improving an existing one. A healthcare company is constantly fighting deadlines - either patents or expired drugs. Applying these analytics help in figuring out which area is most likely to yield results. 2.Improve clinical trials: Clinical trials have always been expensive and still continue to be so. But with effective insights and patient history, corporations can identify which individuals are more

2. suited to the trial. This eliminates unwanted patient trials and also introduces safety into processes. 3.Targeted marketing:Pharmaceutical Marketing Analysis assists scientists on the causes of specific diseases in certain populations. Some illnesses may only occur in certain parts of the world and big data can help micro-target such areas and find niche markets for the organization, thereby generating greater impact. 4.Better insights into patient persona behaviour: This becomes a service oriented step. Patient behaviour speaks volumes about the dos and don'ts of service delivery. Studying and understanding existing personas will help design strategies for specific demographics and groups. 5.Manage and reduce risk and implement safety measures: Medicines and treatments can either go extremely well or horribly wrong. That is why the risk factor in this sector is much higher. Messages and conversations surrounding medication can give a good understanding on what the consumers feel about the product. Listening in a virtual environment lets you identify threats early, so you stay one step ahead. This will save you costs and time, and help you make better decisions. 6.Predictive Analytics:Predictive Analysis in the PharmaceuticalIndustry shows where the organization, its products and services stand in the market. They also show potential growth opportunities and threats by analysing data from social media, demographic group studies, digital records etc. You can also check where your sales efforts have succeeded and where they have not. This gives you an edge over your competition and improves overall performance. Data Science in the Pharmaceutical Industry is a powerful, model strategy that you MUST incorporate in order to gain insight, improve functions, satisfy customers and much more! Data is the most powerful tool you've got.