The simcyp population based simulator: architecture, implementation, and quality assurance.

Masoud Jamei,Kairui Feng,Duncan Edwards,Steve Marciniak,Kris Wragg,Adrian Barnett,Amin Rostami-Hodjegan

doi:10.1186/2193-9616-1-9

Abstract

Developing a user-friendly platform that can handle a vast number of complex physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models both for conventional small molecules and larger biologic drugs is a substantial challenge. Over the last decade the Simcyp Population Based Simulator has gained popularity in major pharmaceutical companies (70% of top 40 - in term of R&D spending). Under the Simcyp Consortium guidance, it has evolved from a simple drug-drug interaction tool to a sophisticated and comprehensive Model Based Drug Development (MBDD) platform that covers a broad range of applications spanning from early drug discovery to late drug development. This article provides an update on the latest architectural and implementation developments within the Simulator. Interconnection between peripheral modules, the dynamic model building process and compound and population data handling are all described. The Simcyp Data Management (SDM) system, which contains the system and drug databases, can help with implementing quality standards by seamless integration and tracking of any changes. This also helps with internal approval procedures, validation and auto-testing of the new implemented models and algorithms, an area of high interest to regulatory bodies.

Highlights

The relative complexity of differential equations involved in physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models, together with the need for comprehensive drug and system data, has previously limited their use to a small group of modelling scientists; such models have been around since the 1930s. (Teorell 1937)
To check this, existing results generated by running defined Workspaces on early versions/builds need to be checked against results from the current released build of the Simulator to ensure that no unexpected discrepancies occured
The Autotest package was initially developed as Python Scripts but has since been recoded in C# to add extra layers of functionality

Summary

Introduction

The relative complexity of differential equations involved in physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models, together with the need for comprehensive drug and system data, has previously limited their use to a small group of modelling scientists; such models have been around since the 1930s. (Teorell 1937). Applications and acceptance of PBPK models joined with In Vitro – In Vivo Extrapolation (IVIVE) of Absorption, Distribution, Metabolism and Excretion (ADME) in drug development and regulatory assessment have significantly increased (Zhao et al 2011, Rostami-Hodjegan 2012). This trend can be attributed to many factors, including, the availability of user-. The Simulator development started with simple static drug-drug interaction calculations (“Static CYP DDI” section of Figure 1) This was expanded to dynamic models and the minimal PBPK model that was subsequently expanded to full PBPK models. The recent developments include handling of therapeutic proteins, the ability to add custom PD scripts and to model time-variant physiology in paediatric population as the subjects grow and in pregnant women over the duration of pregnancy

Methods

Results

Conclusion