Scientists and engineers in the biotech and pharmaceutical industries use MATLAB and Simulink for multidisciplinary data analysis and end-to-end workflows.
With MATLAB, scientists and engineers can:
- Hybridize data from many data streams, including signal, image, text, and genetic
- Optimize pharmaceutical production through process engineering
- Perform modeling and simulation for drug discovery and development
- Design, implement, and deploy code to control new medical devices
- Create automatic output reports in Adobe Acrobat, or Microsoft Word and PowerPoint file formats
“Pfizer is integrating modeling, simulation, and statistical analysis throughout drug discovery and development. This approach helps reduce phase II attrition by guiding the selection of the best biological pathway, target, molecule, dosing regimen, and patient population.”
Using MATLAB and Simulink for Biotech and Pharmaceutical
Biomedical and Health Data Analysis
Using MATLAB, scientists and analysts can:
- Explore and clean data sets in biotech and pharmaceutical research
- Use app-based workflows to develop streamlined analysis schemes, and then scale and deploy the schemes in the cloud
- Synthesize multimodal data sources, including signal, image, date, device, genetic, and Internet of Things to build predictive analytical models
- Parallelize analysis to any number of computational nodes using nearly identical syntax as desktop approaches to scale from desktop development to high-performance computing clusters
Drug Discovery and Development
Using MATLAB, scientists and modeling teams can:
- Model and simulate PK/PD and quantitative systems pharmacology systems using SimBiology for simulated drug studies and parameter sensitivity analysis
- Develop predictive mathematical models for assessing drug efficacy and safety, target feasibility, and optimizing dose schedules
- Hybridize data streams for precision medicine
- Interact with existing databases to explore new applications of existing drugs
- Provide image quantification and model fitting in biodistribution studies
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Pharmaceutical Manufacturing
With MATLAB and Simulink, engineers can:
- Optimize yield during drug manufacturing, lowering costs and time-to-market
- Create digital twins in an industrial Internet of Things architecture to analyze real-time performance, improve operations, and perform predictive maintenance
- Use physics-based modeling, data-driven empirical modeling, or a combination thereof to increase manufacturing yield and quality
Preclinical and Clinical Research and Development
Scientists, engineers, and clinical researchers use MATLAB to:
- Calculate and determine relative importance of image features such as radiomics analysis
- Query databases of labeled legacy data and use deep learning to create auto segmentation tools
- Analyze whole slide data, including cell classification and semantic segmentation
- Parse, load, and analyze DICOM images
Learn More
- Deep Learning Overview for Medical Images | Deep Learning Webinars 2020, Part 6 (39:57)
- Developing in vivo Functional Imaging Technology with Micron-Scale Resolution Using Optical Coherence Tomography
- With MATLAB on Domino Data Lab, leverage GPU computing to accelerate image processing and deep learning
Biotech Device Development
With Model-Based Design, biotech device engineers can:
- Design and test medical devices using simulations, which reduces development time and enables early verification and validation at the system level
- Deploy software and algorithms on instruments in production using automatic code generation
- Create required technical documentation from software development and testing for compliance with FDA regulations and industry standards such as IEC 62304
Learn More
- MATLAB and Simulink for Medical Devices
- Analyze Medical Images in DICOM Format
- Mathematical Modeling for Design and Validation of Medical Devices (44:19)
- FDA Software Validation with MATLAB and Simulink
- Develop Medical Device Software in Compliance with the IEC 62304 Standard
- Developing IEC 62304-Compliant Embedded Software for Medical Devices
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