When it comes to drug manufacturing, pharmaceutical companies hold an enormous amount of responsibility. Discovering and developing new drugs, targeting specific patient populations, running clinical trials, and evaluating drug efficacy are just a handful of the many tasks that the pharmaceutical industry faces daily.
Data collection and analytics are essential to the drug development process. Without reliable data, the pharmaceutical industry would not exist, and consumers would thoroughly doubt the effectiveness of medicine. Having the ability to make data-backed decisions is essential for success in this industry — which is where pharma analytics comes into play.
Pharma analytics involves harnessing the power of data analytics to improve operations in the pharmaceutical industry. Using analytics software to accelerate the data collection and analysis process allows pharmaceutical companies to work faster and more efficiently to deliver products to market and increase profitability.
The pharmaceutical industry has a longstanding history of relying on empirical data for drug development and distribution. However, sorting through all this data is a monumental task, prompting the industry to turn toward modern solutions such as pharma analytics software to gain deeper insight into critical data.
Pharma analytics is the usage and application of data analytics within the pharmaceutical industry. Integrating big data analytics solutions into the pharmaceutical manufacturing process allows companies to gain valuable insights to accelerate and optimize production.
Pharmaceutical manufacturers can integrate data analytics throughout every step of the drug development process, from research and discovery to development to clinical trials and beyond. Pharma analytics allows companies to gain greater insight into consumer demand, drug efficacy and other factors that are critical to overall performance.
Pharma analytics allows pharmaceutical companies to improve their decision-making throughout the drug development and marketing processes. Integrating advanced data into daily operations allows pharmaceutical manufacturers to make more informed business decisions and improve overall results.
Using pharma analytics allows pharmaceutical companies to enhance core processes throughout every stage of the drug development process. For example, pharma analytics can be implemented in the R&D stage to accelerate and optimize drug discovery. With groundbreaking tools such as machine learning (ML) and artificial intelligence (AI), pharma manufacturers can perform predictive analytics based on market research, chemical makeup, biological factors and other variables. This allows pharmaceutical companies to improve reliability and validity at an accelerated pace.
Pharma analytics is often integrated into various smart manufacturing solutions, including:
From preliminary research and development to delivering products to market, pharma analytics play a key role in every phase of the pharmaceutical manufacturing process.
Integrating pharma analytics into drug discovery, manufacturing, and distribution comes with enormous benefits, including:
Pharma analytics translates big data into actionable insights throughout every step of the manufacturing process. Using the insights gleaned from big data can help pharmaceutical companies optimize and accelerate operations for greater success.
What is pharma analytics?
The term “pharma analytics” refers to the use of data analytics within the pharmaceutical industry to optimize operations and promote innovation. Pharmaceutical companies can use data analytics to accelerate drug discovery and development, improve drug efficacy, enhance safety and risk management and gain insight into target patient populations.
How do pharmaceutical companies use analytics?
Pharmaceutical companies use pharma analytics to improve every step of the drug development and distribution process. From drug discovery and development to securing regulatory approval and distributing drugs to target populations, data analysis plays a huge role in the field of pharmaceutical manufacturing.
How is data analysis used in pharmacies?
Pharmacies can incorporate data analytics to improve operations in a multitude of ways, including ensuring compliance, improving efficiency and monitoring inventory. Pharmacies can use data analytics to compare in-house prescription data against DEA and state regulations to verify operating compliance. Data analytics can also help improve overall efficiency by optimizing order fulfillment and decreasing refill time to increase customer satisfaction and company productivity.
Predictive Maintenance Takes on Operational Risk