WHY PHARMACEUTICAL INDUSTRY NEEDS BIG DATA AND BIG DATA APPLICATIONS IN PHARMA INDUSTRY
Industry sectors such as telecommunications, advertising, healthcare, and finance have all benefited from the use of big data. Similarly, the pharmaceutical sector is developing as a result of the increased use of big data. The rise of big data in the pharmaceutical industry is assisting in the streamlining of several complex business activities and increasing overall efficiency.
As a result, nearly $4.7 billion has been invested in big data by investors in the healthcare and pharmaceutical industries. Pharmaceutical companies hope to create a number of innovative uses with continued investment.
Businesses can benefit from historical and real-time data sources such as social media, IoT devices, log files, and patient data using big data. Big data analytics can assist in the discovery of hidden patterns in such data, which can then be used to develop useful analytics. Pharmaceutical firms can use big data to adopt a data-driven approach to a variety of business processes.
Advanced analytics in the pharmaceutical and life sciences industry – including tools such as Artificial Intelligence, machine learning and data mining – has the potential to transform the Pharma Business Value Chain. Process automation and Data driven predictive insights have the ability to dramatically change how executives make strategic decisions and manage financial performance across all commercial areas.
AI applications within the healthcare industry have the potential to create $150 billion in savings annually for the United States, a recent Accenture study estimates
According to McKinsey, operating efficiencies, attainable from scaling the impact of advanced analytics in pharma industry range as high as 15 to 30 percent of EBITDA over five years, accelerating to 45 to 70 percent over a decade, based on discovering and optimizing new blockbuster therapies.
According to PWC, an advanced analytics capability could—depending on the type of product and lifecycle stage—deliver “at least a 10 percent net impact from a top- and bottom-line perspective,” GlaxoSmithKline’s Chief Data Officer, US commercial pharmaceuticals
According to an MIT study, only 13.8% of drugs are successful in passing clinical trials. To top that, a pharma company has to pay anywhere between US$ 161 million to US$ 2 billion for a drug to get through the complete process of clinical trial and get FDA approval
UTILIZING BIG DATA IN THE PHARMACEUTICAL INDUSTRY
Research and Development:
The use of big data in the pharmaceutical industry will aid executives in learning more about various treatments and how they are used. Businesses can make informed judgments during research and development with the help of these insights. As a result, pharmaceutical companies may use big data to design more effective medicines and lower unwanted effects.
After acquiring relevant data on the patient’s genetics, surroundings, and behaviour patterns, big data analytics is used to diagnose and treat a variety of ailments. Individual patients with varying symptoms can be treated with a combination of personalised medicine. The predictive model created from the patient’s previous data can also aid in the early detection of illnesses.
Focus on Sales and marketing:
Because of many demographic aspects, big data can assist pharma businesses in predicting the sale of a specific medicine. This will allow businesses to anticipate client behavior and tailor marketing to reach out to them. With the use of big data, accurate industrial trends may be forecasted and studied.
External and Internal Collaboration
Internal collaboration will be improved by streamlining drug discovery, clinical trials, and medical affairs. Contract research organizations (CROs), on the other hand, can assist pharma companies in making better drug decisions by providing insights from outsider researchers. Big data can assist pharmaceutical representatives in determining which medicines are suited for each patient. As a result of their unique combination of diseases, this will aid in the creation of customized treatment plans for each patient. Whether it’s for precision medicine, lowering the number of drug failures, or lowering the cost of research and drug discovery, big data analytics has a bright future in the pharmaceutical industry. With data being the new oil, any pharma business that wants to give better and faster treatment to humanity must exploit this resource.
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