Preclinical Research and Development
Throughout drug identification and development processes, MathWorks products can be used for defining and verifying drug objectives and candidates, including identifying and approving targets, identifying, and optimizing potential customers. By leveraging MATLAB® platform, researchers can access:
- A single, integrated environment to examine research areas such as bioanalytic, statistics, array analysis, microarray analysis, high content scanning, route analysis and image processing.
- Parallel, deployed and 64-bit information processing for high-efficiency calculation.
- Automated report generation and app deployment.
- Graphical and programmed functionality.
- Workflow automation capability.
Preclinical and Clinical Research
Researchers use MathWorks tools to evaluate the safety, dosage, and effectiveness of drugs in preclinical and clinical studies. In a flexible and customizable platform researchers can perform the complete workflow from modelling to analysis, including ADME and non-linear mixed effects (NLME) modelling.
MathWorks pharmakinetic and pharmadynamic (PK/PD) modelling environment SimBiology®, provides simple pointing and clicking tools that render PK / PD modelling analysis accessible for researchers with limited or no programming experience. Researchers can access an industry-tested simulation solution package and integrate PK/PD modelling into other functions such as parallel calculation, statistics and optimization.
While using MathWorks tools for clinical studies, scientist can exploit capabilities such as database integration and report generation to fulfill regulatory instructions.
Pharmaceutical Manufacturing
Typically, pharmaceutical manufacturing includes developing special process control strategies and analytics that is not easy to program in the traditional control systems used by manufacturing facilities.
MathWorks software provides the ability to develop hardware-independent apps for monitoring bulk, continuous processing, and model-based and multivariate statistical process control. This allows scientists and engineers to verify process stage strategy and analytics earlier when it is easier and cheaper to change design. Special abilities include:
- Generating C code and .NET apps
- Creating independent or web-based apps for process monitoring
- Accessing data from data bases, over OPC, or directly from devices.
