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How do Clinical Trials Work?
The Role of Predictive Analytics Software in Drug Development
The pharmaceutical industry brings us several benefits, including new drugs, so we can lead healthier and better lives, but the industry is not without its fair share of problems. Duplicating workflow, multiple data sources, and the risk associated with new drug discovery are just some of the problems the industry has to overcome in the discovery of new drugs. Fortunately, there is a solution thanks to predictive analytics software.
To appreciate what predictive analytics software brings to the table, we need to take a look at some of the challenges the industry faces. Developing new drugs is not an easy process. Medical researchers have to overcome a slew of problems to make a new drug. Some of these problems include the risk associated with drug discovery, communicating with other departments, and replicated workflows.
Developing new drugs comes with several risks. Some of these risks include but are not limited to, portfolio risks (does the medicine add value?), operational risks (data management), and resource risks. Pharmaceutical companies must manage all these risks while developing a new product. The challenge is further enhanced by the rise of the personalized medicine model, which more pharmaceutical companies are adopting.
Programmers and biostatisticians working in the clinical research industries have successfully used SAS for many years to transform data, generate safety and efficacy results, and submit data to FDA. SAS in Drug Development provides innovative capabilities to not only meet the historic needs of the industry, but to efficiently collaborate across trials, phases, therapeutic areas, departmental organizations and technologies, and ultimately get drugs, biologics and devices to market faster.