2023 - A Coruņa - Spain

PAGE 2023: Software Demonstration
Simone Perazzolo

SAAM II: Selected Software Use Cases in Modern PK-PD Data Analysis

Simone Perazzolo, (1), (2)

(1) Nanomath LLC, USA, (2) University of Washington, USA

Introduction: Simulation Analysis and Modeling II (SAAM II) is perhaps the most renowned software for compartmental modeling. Compartmental modeling is the mathematical basis for pharmacokinetics (PK) and pharmacodynamics (PD) approaches. The original SAAM was developed in NIH laboratories in the late 1950s as an ordinary differential equation (ODE) solver and optimizer to deal with radiation dosimetry. Since then, it has evolved in scope until a completely re-engineered version was developed in the mid-1990s at the University of Washington – Department of Bioengineering. Their software development philosophy was to create a user interface (UI) mirroring the typical “circles and arrows” sketches used to represent compartmental systems and thus approach a new generation of users unfamiliar with scripting or command-line coding. Now, to model in SAAM II, no coding or scripting is indeed needed; users can drag-and-drop model components and solve/fit with a click in the UI, thus enabling “rapid prototyping” of models, even complex ones.

Several technical features of SAAM II are still current:

  • State-of-the-art ODE solving and parameter fitting algorithms;
  • Built-in optional Bayesian maximum a posteriori (MAP) fitting to accommodate parameter priors;
  • Algorithms coded in C for best computational performance, resulting in very short CPU times for solving and fitting models, and indirectly validated by >25 years of use;
  • Prototype group and batch analysis, incorporating two-stage methods (iterative and global).

When compared to other similar ODE-solving software, SAAM II was initially geared up for tracer and kinetic problems and has a general compartmental modeling capability which makes it useful for educational purposes. SAAM II currently has an active user base, including academics, pharmaceutical research and development scientists, and regulatory professionals.

Users broadly consist of:

  1. Beginner modelers: it allows implementation and running of simple ODE-based models by anyone (especially, but not exclusively, if requiring a balance of mass);
  2. Expert modelers: it provides relatively easy handling and “rapid prototyping” of complex PK and nonlinear PD, facilitating model selection for other software platforms.

However, while the last publication describing the software dates to 1998 [1], a few adjustments and especially new fields of applications have emerged since then. In this presentation, we want to highlight selected examples of where SAAM II can be relevant and useful in modern pharmacometrics data analysis and model development.

Objectives: 

  • To exemplify the application of SAAM II to pharmacometrics data analysis, and
  • To identify the niche where SAAM can support modern modeling and simulation.

Methods: We chose two models published in different emerging fields: long-acting HIV therapy [2] and targeted covalent binding [3]. Data from each paper were digitized and imported into SAAM II. The models were mechanistically based on nanoparticle multi-compartment drug delivery, in the HIV case, or a PK-PD model for targeted covalent drugs.

Results: Replicating these complex models from publications took no more than a few hours for each example, showing that the UI can efficiently support design and/or reproduction of model approaches. Subsequently, we studied the models for identifiability properties, sensitivity to parameter values, new dosage regimens, and changes to the model structure to accommodate nonlinearities or binding stoichiometry. These adjustments could also be quickly tested in the software to generate possible mechanistic hypotheses.

Conclusions: We believe SAAM II has a relevant user niche in current modeling and simulation practice. SAAM II is a useful platform for mechanistic prototyping of ODE-based models, due to its ease to design, replicate, and test hypotheses very quickly. Beginner modelers appreciate that they do not have to learn a coding language to ease their way into the modeling, whilst expert modelers value the seamless modeling flow from PK to PD (often, other software needs a certain degree of coding or have less intuitive user interfaces). More information about SAAM II is available at https://www.nanomath.us/saam2 or saam2@nanomath.us. 



References:
[1] P. H. Barrett et al., “SAAM II: Simulation, Analysis, and Modeling Software for tracer and pharmacokinetic studies,” Metabolism., vol. 47, no. 4, pp. 484–492, Apr. 1998, doi: 10.1016/s0026-0495(98)90064-6.

[2] S. Perazzolo et al., “Integration of Computational and Experimental Approaches to Elucidate Mechanisms of First-Pass Lymphatic Drug Sequestration and Long-Acting Pharmacokinetics of the Injectable Triple-HIV Drug Combination TLC-ART 101,” J. Pharm. Sci., vol. 109, no. 5, pp. 1789–1801, May 2020, doi: 10.1016/j.xphs.2020.01.016.

[3] Z. Yang, “Achieving a low human dose for targeted covalent drugs: Pharmacokinetic and pharmacodynamic considerations on target characteristics and drug attributes,” Biopharm. Drug Dispos., vol. 42, no. 4, pp. 150–159, Apr. 2021, doi: 10.1002/bdd.2263.


Reference: PAGE 31 (2023) Abstr 10670 [www.page-meeting.org/?abstract=10670]
Software Demonstration
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