Why use SAS in pharmaceuticals?
Which Certification Course is best for BPharm and MPharm Professionals?
SAS provides analytics tools for large pharmaceutical companies to improve manufacturing processes and improve business performance to deliver effective medicines and effective therapies to patients. SAS Analytics tools provide insight into improving equipment performance and accurate demand forecasting.
Data Integration
Pharmaceutical organizations have a large amount of data, if it is in an unstructured form, it is necessary to collect appropriate data by performing data analytics on it. While data integration, it is necessary to check the quality of data, maintain the security of that data, and also maintain data by governance standards, etc. Once the data integration is done properly, pharmaceutical companies do data analytics on it in different ways and can use that data to achieve many goals. Data integration can be done using artificial intelligence and machine learning algorithms.
Real-time data available in Pharma organizations is used to optimize clinical trials. It increases production efficiency and can easily provide new formulations in minimum time and gives a competitive advantage to the Pharmaceutical Industry. A well-analyzed data can help to identify the mechanism of a disease and to build a prognostic model on it. So that the drug preparation process can be accelerated and preventive measures can be taken.
Data integration is very important in pharmaceutical organizations as it helps them to create an efficient healthcare system. Also, they are investing in new technologies to increase workflow efficiency and provide employment opportunities for clinical programmers. Data integration is essential not only for pharma companies but also for the development of healthcare company operations.
The data sources used by pharmaceutical companies for data integration are as follows.
Clinical Trials Process Reports
Clinical Research Projects
Health Insurance Companies Data
Electronic health records of patients
Tracking of Patients Statistics
Primary Data Sources — Patient Prescription History
FDA Research Data
Patient Testimonials Data
Biotech, Life Science Company — Sales Data
Social Media & Website Records — Patient self-data according to their search health-related data.
That is, Health Science, Biotech, health care, and pharmaceutical organization have a great need for data integration. Nowadays health-related data is available on different portals and some healthcare companies are uploading data. And of course, this data helps to stay up-to-date on health. But this raises not only compliance issues for companies but also privacy concerns.
In short, data integration in the pharmaceutical industry can be done to check the quality and accuracy of the collected data. This helps ensure the safety and efficacy of the medicine and the product. This requires a data management process in the pharmaceutical manufacturing industry.
Data integration challenges and benefits for Pharmaceutical Organizations
Medical Issues: Medical errors are one of the major occurrences not only in pharmaceuticals but also in the healthcare, health science, and biotech sector. It harms at least 1.5 million people every year. Patient safety is a major public health concern. Some global pharmacy organizations recognize the importance of this problem and take appropriate steps to prevent medication errors for patient safety. Global organizations such as FDA, ISMP, WHO, GPO, etc. can help assess the causes of medication errors.
Analyzing data and errors in healthcare delivery processes reduces the risk of medication errors and improves patient safety. They emphasize public safety, promote, as well as continuous monitoring of accuracy in dispensing, appropriate prescription and reliability in drug orders, and upgrades and reviews in pharmacy operating structure.
Cyber security: A healthcare company’s database contains very important information, if the confidentiality of that data is not maintained, it attracts many hackers to the system and the data is not secure.
Investment in IT development in health services: Due to the rapid availability of information and different IT technologies for data integration, investment and development of IT technology to make proper business processes are costly.
Premium Processing and Invoice: In this, if the invoice is made in the wrong way, it can create negative consequences. This creates a barrier between supply and purchase. It also requires automating accounts payable and automating invoice processing in pharmaceutical companies. Also, payments are processed every minute, and linking them to patient profiles becomes ambiguous.
Data Integration Benefits for Pharmaceutical Organizations
Flexibility: Data Integration allows customers to easily adapt to systems even as the business changes continuously.
Profitable: Data integration in pharmaceutical companies can be easily done through experts, for that Data Integration Tools in IT technologies are used. Like SAS Data Integration tools, (Competitors: Informatica, IBM, SalesForce, SAP, Microsoft, Oracle, etc. It benefits Pharmaceutical companies).
Data-driven root cause analysis
Root cause analysis allows analysis-related problem solving and optimization for development tasks thus gaining insights; as well Production capacity can be increased. In short, more operations in the industry can be enabled by using analytics to solve problems.
Predictive analytics with AI
Predictive analytics is the use of technologies such as SAS artificial intelligence and machine learning as well as statistical algorithms to predict future outcomes based on data. SAS uses Predictive Analytics Tools to provide the best assessment of what will happen in the future. In this, Predictive Analytics can be done using AIML Tools so that large amounts of data can be aggregated and analyzed easily.
All pharmaceutical companies use Predictive Modeling technologies such as Neural Networking. Regression Analysis and Clustering for manufacturing processes to ensure continuous product quality.
Why is predictive analytics important?
Top Industry Sectors using Predictive Analytics
Banking and Financial Services
Manufacturing Industries
Pharmaceutical, Health Insurance
Retail Organizations
Public sector and government
Information Technology
Telecommunication Organizations
Entertainment
Sports
Weather
Cybersecurity
Which SAS course is best for pharmacy Professionals?
Definitely, the Clinical SAS Certification course is best for Pharmaceutical Professionals. Clinical SAS Programmers have skills in SCISE, SDM, SDTM Etc. Clinical SAS Certification Guide: How to Become Certified in Clinical SAS? Can Pharmacy graduates take a SAS clinical course?
Conclusion: SAS is a Data Analytics platform designed for the Pharmaceutical Manufacturing industry. SAS enables users to use AIML, Machine Learning algorithms, as well as Predictive Analytics Tools, to perform data analytics tasks. This provides real-time data, as well as solutions to problems.
SAS Application Technology is being used for Clinical Trials and Data Analytics in pharmaceutical, healthcare, clinical research as well as biotech organizations. These clinical trials are making an impactful change in the lives of patients. The Scope of clinical SAS programming has seen rapid growth in the last few years. Clinical SAS programmers are in high demand and continue to grow. SAS has a good career in terms of salary increments. If you are new to this field then 3–4 lakhs annual income can be easily earned. After 3–4 years you can easily expect 8 to 12 lakhs. As you gain experience in big organizations and learn new skills your salary will increase by lakhs. So, After Bpharm or Mpharm — If you are planning to learn SAS Certification Join the Best Clinical SAS Certification Training Institute in Pune with Placements. If you want to pursue a career in clinical SAS then go ahead with Clinical Trials Online Course in Pune Which includes SAS Base, Advance SAS, SAS Report, and Statistics1.
Related: Start a career in Clinical SAS Programming
Related: What is Clinical SAS? Why SAS for Clinical Research Analytics? See the Details!!
