Quantitative systems pharmacology (QSP) modeling has become increasingly important in pharmaceutical research and development, and is a powerful tool to gain mechanistic insights into the complex dynamics of biological systems in response to drug treatment. However, even once a suitable mathematical framework to describe the pathophysiology and mechanisms of interest is established, final model calibration and the exploration of variability can be challenging and time consuming. QSP models are often formulated as multi-scale, multi-compartment nonlinear systems of ordinary differential equations. Commonly accepted modeling strategies, workflows, and tools have promise to greatly improve the efficiency of QSP methods and improve productivity. In this paper, we present the QSP Toolbox, a set of functions, structure array conventions, and class definitions that computationally implement critical elements of QSP workflows including data integration, model calibration, and variability exploration. We present the application of the toolbox to an ordinary differential equations-based model for antibody drug conjugates. As opposed to a single stepwise reference model calibration, the toolbox also facilitates simultaneous parameter optimization and variation across multiple in vitro, in vivo, and clinical assays to more comprehensively generate alternate mechanistic hypotheses that are in quantitative agreement with available data. The toolbox also includes scripts for developing and applying virtual populations to mechanistic exploration of biomarkers and efficacy. We anticipate that the QSP Toolbox will be a useful resource that will facilitate implementation, evaluation, and sharing of new methodologies in a common framework that will greatly benefit the community.
TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThe recent years have seen the emergence of detailed field data acquisition and efficient modelling tools to characterize reservoirs and model their complex internal structure in a realistic way. This progress led to the detection of multi-scale fractures in most reservoirs, and enabled to interpret unexpected field production features such as early breakthroughs. Therefore, the availability of a workflow and an integrated modelling methodology becomes more and more crucial to take into account the geological information about fractures/faults into the reservoir dynamic simulation process for optimizing field productivity and reserves. This paper reviews and illustrates the overall methodology and the specifically-involved procedures and tools we have gradually built from the experience acquired in various fractured field case studies.The main steps of this multidisciplinary approach include (a) the detection, geological analysis and modeling of multiscale natural fracture network from seismic and well data, (b) its validation and calibration from dynamic field information such as well tests, (c) the choice of an equivalent simulation model applicable at reservoir scale, and its construction thanks to innovative flow up-scaling procedures applied to the realistic model provided by the geologist, (d) the implementation of predictive and numerically-efficient algorithms to represent the physics of flow transfers occurring both at local and large scale during multiphase field production.Thanks to this consistent workflow, field simulation models remain interpretable in geological terms, which is helpful for subsequent model updating. Thus, specialists in geosciences and reservoir engineers can cooperate in a very effective way to improve the management of fractured reservoirs.
A B S T R A C TComputed tomography scan imaging techniques have been used on core samples to investigate the effect of natural open fractures on reservoir flow in the Snøhvit Gas Condensate Field. Firstly, computed tomography (CT) scanning was used to describe the 3D geometrical properties of the fracture network including orientation and fracture density. Two types of fractures were observed: F1 fractures are short and stylolite related and F2 fractures are longer, cross-cutting the core and without any obvious relationship to stylolites. Secondly, monitoring of single and two phase flow experiments on samples containing these two types of natural open fractures was performed under 10 and 80 bar net confining pressure while using CT scanning. 1-phase miscible flooding experiment shows approximately 3 times higher flooding velocity in an open F2 fracture than in the matrix. 2-phase flooding by gas injection into a 100% water saturated core gave early gas breakthrough due to flow in the fracture and thereafter very little water production. The flow experiments showed that the presence of open fractures has a significant local effect on fluid flow even in a case with relatively high matrix porosity (200-300 mD). The sample containing F1 fractures showed a complex flow pattern influenced both by open fractures and stylolites. The CT scan data enables an exact representation of the fracture network in core scale simulation models and therefore improves the understanding of fracture influence on flow in a fractured porous medium. CT scanning of core samples provides an effective tool for integrating geology and fluid flow properties of a porous fractured medium.
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