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      BioDMET: a physiologically based pharmacokinetic simulation tool for assessing proposed solutions to complex biological problems

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          Abstract

          We developed a detailed, whole-body physiologically based pharmacokinetic (PBPK) modeling tool for calculating the distribution of pharmaceutical agents in the various tissues and organs of a human or animal as a function of time. Ordinary differential equations (ODEs) represent the circulation of body fluids through organs and tissues at the macroscopic level, and the biological transport mechanisms and biotransformations within cells and their organelles at the molecular scale. Each major organ in the body is modeled as composed of one or more tissues. Tissues are made up of cells and fluid spaces. The model accounts for the circulation of arterial and venous blood as well as lymph. Since its development was fueled by the need to accurately predict the pharmacokinetic properties of imaging agents, BioDMET is more complex than most PBPK models. The anatomical details of the model are important for the imaging simulation endpoints. Model complexity has also been crucial for quickly adapting the tool to different problems without the need to generate a new model for every problem. When simpler models are preferred, the non-critical compartments can be dynamically collapsed to reduce unnecessary complexity. BioDMET has been used for imaging feasibility calculations in oncology, neurology, cardiology, and diabetes. For this purpose, the time concentration data generated by the model is inputted into a physics-based image simulator to establish imageability criteria. These are then used to define agent and physiology property ranges required for successful imaging. BioDMET has lately been adapted to aid the development of antimicrobial therapeutics. Given a range of built-in features and its inherent flexibility to customization, the model can be used to study a variety of pharmacokinetic and pharmacodynamic problems such as the effects of inter-individual differences and disease-states on drug pharmacokinetics and pharmacodynamics, dosing optimization, and inter-species scaling. While developing a tool to aid imaging agent and drug development, we aimed at accelerating the acceptance and broad use of PBPK modeling by providing a free mechanistic PBPK software that is user friendly, easy to adapt to a wide range of problems even by non-programmers, provided with ready-to-use parameterized models and benchmarking data collected from the peer-reviewed literature.

          Electronic supplementary material

          The online version of this article (doi:10.1007/s10928-011-9229-x) contains supplementary material, which is available to authorized users.

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          Most cited references31

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          Utility of in vitro drug metabolism data in predicting in vivo metabolic clearance.

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            Plasma clearance of nonradioactive iohexol as a measure of glomerular filtration rate.

            Renal clearance of inulin is the best available indicator of GFR but cannot be used routinely for clinical purposes and is also difficult to perform for clinical investigation when repeated measurements are required. The aim of this study was to find a reliable alternative to inulin clearance that would allow one to avoid the use of radioactivity and problems related to the continuous infusion of the marker. The plasma clearance of unlabeled iohexol, a nonionic contrast agent, was used. Forty-one patients (creatinine clearance 6 to 160 mL/min per 1.73 m2) underwent simultaneous measurements of renal clearance of inulin and plasma clearance of iohexol. Iohexol was given as a single iv dose, and blood samples were drawn up to 600 min after the administration. Iohexol concentrations (by HPLC) were analyzed by a two-compartment, open-model system. A highly significant correlation between the plasma clearance of iohexol and the renal clearance of inulin over a wide range of GFR values was found. By analyzing the data with a simplified method that uses a one-compartment model corrected with the Bröchner-Mortensen formula, an excellent correlation with the inulin clearance was also observed. When only patients with moderate to severe renal failure were considered, a significant correlation between the two methods was found. A further comparison between GFR determined with iohexol and iopromide, a new low-osmolarity, low-viscosity contrast medium, was also performed in a subgroup of patients.(ABSTRACT TRUNCATED AT 250 WORDS)
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              Transport of macromolecules across microvascular walls: the two-pore theory.

              In this review we summarized the evidence favoring the concept that the major plasma proteins are passively transported across vascular walls through water-filled pathways by means of convection and diffusion. With regard to solute transport, a majority of microvascular walls seems to show a bimodal size selectivity. This implies the presence of a high frequency of functional small pores, restricting proteins, and an extremely low number of non-size-selective pathways, permitting the passage of macromolecules from blood to tissue, here denoted large pores. We discussed the general behavior of such a heteroporous system. A major consequence of two-pore heteroporosity is that large-solute transport must mainly occur due to convection through large pores at low filtration rates, that is, at normal or even zero lymph flows. Indeed, convection must be the predominating transport mode for most solutes across large pores when the net filtration rate is zero. Under these (transient) conditions, the convective leak of macromolecules across large pores will be counterbalanced by absorption of essentially protein-free fluid through protein-restrictive pores. In a heteroporous membrane, proteins can thus be transported by solvent drag across vascular walls in the absence of a net convection. Normally the steady-state transcapillary fluid flow (lymph flow) is about equally partitioned among small and large pores, which makes lymph essentially a "half and half" mixture of protein-free ultrafiltrate and plasma. With increasing fluid flows, however, the plasma filtrate will be progressively diluted, eventually reaching a protein concentration largely in proportion to the fractional hydraulic conductance accounted for by the large pores (alpha L). Under these high lymph flow conditions, not only the large-pore transport but also the small-pore transport (of smaller macromolecules) will become convective. At low lymph flows, however, the small-pore transport of smaller macromolecules is usually mostly diffusive. An important implication of capillary heteroporosity is that single-pore formalism is inadequate for correctly evaluating the capillary sieving characteristics. With the use of homoporous transport formalism, the "lumped" macromolecular PS and sigma will therefore vary as a function of transcapillary fluid flow (Jv). However, it is approximately correct to use single-pore formalism for conditions when Jv is very high during steady state. Thus, if minimal sieving coefficients can be measured for macromolecules, then these values will accurately reflect (1 - sigma).(ABSTRACT TRUNCATED AT 400 WORDS)
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                Author and article information

                Contributors
                Maria.Zavodszky@ge.com
                Journal
                J Pharmacokinet Pharmacodyn
                Journal of Pharmacokinetics and Pharmacodynamics
                Springer US (Boston )
                1567-567X
                1573-8744
                10 December 2011
                10 December 2011
                February 2012
                : 39
                : 1
                : 37-54
                Affiliations
                [1 ]Computational Biology and Biostatistics Laboratory, General Electric Global Research Center, One Research Circle, Niskayuna, NY 12309 USA
                [2 ]Pervasive Decisioning Systems Laboratory, General Electric Global Research Center, Niskayuna, NY USA
                Article
                9229
                10.1007/s10928-011-9229-x
                3258408
                22161221
                4c1f6a8e-d54a-4dba-9d80-c6309a077752
                © The Author(s) 2011
                History
                : 10 August 2011
                : 13 November 2011
                Categories
                Article
                Custom metadata
                © Springer Science+Business Media, LLC 2012

                Pharmacology & Pharmaceutical medicine
                pbpk modeling,imaging,biodistribution,mechanistic model,pharmacokinetics,whole body model

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