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In the pharmaceutical industry, programming plays a vital role in data analysis, statistical modeling, and simulations. With numerous programming languages and tools available, it can be challenging to determine which ones are most commonly used. Here are the top 10 program codings commonly used in pharmaceutical research:

R: Known for its packages for data analysis and visualization, R is a powerful open-source programming language for statistical computing and graphics.

Python: Widely used in the pharmaceutical industry, Python offers a rich set of libraries for data analysis, machine learning, and scientific computing.

SAS: The commercial software suite SAS is commonly used for data analysis, reporting, and statistical modeling.

MATLAB: MATLAB is a popular numerical computing environment and programming language used for data analysis, simulation, and visualization.

Perl: Perl is a high-level programming language that is commonly used for data analysis, text processing, and system administration in the pharmaceutical industry.

SQL: The standard language for managing relational databases, SQL is commonly used for data management and querying in the pharmaceutical industry.

C++: C++ is a high-performance programming language used for developing software applications and simulations in the pharmaceutical industry.

Java: Java is widely used in the pharmaceutical industry for developing web-based applications and data analysis tools.

Excel: Microsoft Excel is a commonly used spreadsheet program in the pharmaceutical industry for data analysis and reporting.

Tableau: Tableau is a data visualization and business intelligence tool used for data exploration, analysis, and reporting in the pharmaceutical industry.

These top 10 program codings are just a few examples of the many programming languages and tools available for pharmaceutical research. Knowing which programming languages to use can make all the difference in the success of a project
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