ADAPT is a computational modeling platform developed for pharmacokinetic and pharmacodynamic applications. It is intended for basic and clinical research scientists and is designed to facilitate the discovery, exploration and application of the underlying pharmacokinetic and pharmacodynamic properties of drugs. ADAPT has been developed under the direction of David Z. D’Argenio in collaboration with Alan Schumitzky and Xiaoning Wang.
Since 1985, ADAPT has been developed and supported by the Biomedical Simulations Resource (BMSR) in the Department of Biomedical Engineering at the University of Southern California, under support from the National Institute for Biomedical Imaging and Bioengineering (P41-EB001978) and the National Center for Research Resources (P41-RR01861) of the National Institutes of Health. It is distributed by the BMSR at no charge to the user, under the terms of a Release Agreement. We ask that all users of ADAPT provide us with a completed Release Agreement so that we can maintain a database of ADAPT users.
System Requirements
- Operating System
- Windows 11/10/8/7
- Other Software REQUIRED
- Intel oneAPI Base Toolkit + HPC Toolkit
- Microsoft Visual Studio
Features in ADAPT 5
Individual Analysis
- Estimation module (ID) includes weighted least squares, maximum likelihood (ML), generalized least squares (GLS), maximum a posterior Bayesian estimation (MAP)
- Simulation module (SIM) includes capabilities for single and multisubject simulations
- Sample schedule design module (SAMPLE) provides the ability to calculate D- and C-optimal designs
Population Analysis
- Parametric population PK/PD modeling using maximum likelihood estimation via the EM algorithm with sampling (MLEM), as introduced by Schumitzky (1995) and by Walker (1996), with extensions and enhancements by Bauer & Guzy (2004).
- Iterated two-stage (ITS) analysis as proposed by Prevost (1977) and Steimer, Mallet and colleagues (1984).
- Convenient standard two-stage (STS) and naive pooled data (NPD) modeling, each with WLS, ML, and MAP estimators.