A Complete Platform for Modeling and Simulation
The award-winning acslX environment provides integrated, end-to-end capabilities for model development, simulation execution, and results analysis. Models are specified using either familiar block diagram notation, or code-based descriptions using the CSL modeling language. By default, all model representations are translated into C or FORTRAN language source code for compilation and execution, ensuring the fastest possible performance and support for extremely large or complex models. Open application programming interfaces (APIs) are provided throughout the system to extend acslX functionality, allow the integration of custom or legacy code within acslX models, or to embed the generated simulation into end-user applications. Model code reuse is supported through easily creatable user-defined libraries of simulation blocks. acslXtreme provides a powerful simulation control scripting language and mathematical analysis environment based on the popular M language for mathematical computing.
Complex Problems in Computational Biology Require Flexible, Sophisticated Tools
As the descendant of the ACSL family of modeling and simulation tools, originally developed in 1974 and now widely used for PBPK and PK/PD modeling, acslX supports both textual and graphical languages for specifying complex biological models, and a Matlab-like scripting language for specification of parameter estimation, sensitivity analysis, Monte-Carlo, or Markov-Chain Monte Carlo analyses. For computationally intensive problems, acslX includes support for cluster/grid computing. Data integration capabilities with Microsoft Excel and Access are provided, and a PBPK/PK/PD toolkit is also available which includes linear and nonlinear PBPK models of various organs, exposure models for inhalation, oral and dermal exposures, and a variety of PD dose response models.
ADME WorkBench is built on the acslX computational engine, a software environment for modeling, simulation and analysis of complex nonlinear systems and processes.
Simple to learn and easy to use, acslX provides an intuitive environment for users at all levels and is versatile and powerful enough to address the most challenging simulation problems. Ready-to-use code blocks enable quick model assembly, while powerful analysis capabilities provide quick and accurate results. Industry-specific toolkits are tailored to the needs of each customer. acslX improves your modeling and simulation productivity through efficient development, easy integration with existing applications and systems, and robust analysis features.
A History of Solving the World’s Most Complex Modeling and Simulation Problems
acslX is used by scientists and engineers in fields including drug discovery and development, toxicology, aerospace engineering, automotive design, and industrial process engineering to solve complex mathematical problems.
acslX continues the tradition of its predecessor, ACSL, which was one of the first commercially available modeling and simulation tools designed for simulating continuous systems. ACSL has been validated through more than 30 years of continuous use by the world’s most demanding simulation professionals.
End-to-end capabilities for modeling, simulation and analysis of biological systems and data
- Develop models using both a rich, text-based simulation language and quick, intuitive graphical representations
- Create reusable libraries of models with graphical simulation blocks
- Create sophisticated scripts for controlling simulation runs and performing complex analyses using a Matlab-like scripting language
- Perform calibration, validation and uncertainty analysis using the sophisticated parameter estimation, sensitivity analysis, Monte-Carlo analysis and Bayesian analysis capabilities of acslX
- Facilitate data import and export with acslX’s integration with Microsoft Access and Excel
- Speed model creation with the PBPK/PK/PD toolkit of pre-built simulation blocks, and an SBML import utility for automatically generating acslX models from SBML-basedsystems biology models
- Employ cluster/grid computing resources for computationally intensive problems
Tools for Computational Biology at any Level
- Physiologically-based pharmacokinetic modeling
- Virtual tissues and organs
- Disease simulation
- Biochemical reaction network simulation
- Classical compartmental PK/PD modeling