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      Consideration of Fractional Distribution Parameter fd in the Chen and Gross Method for Tissue-to-Plasma Partition Coefficients: Comparison of Several Methods

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      Pharmaceutical Research
      Springer Science and Business Media LLC

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          Physiologically based pharmacokinetic modelling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions.

          A key component of whole body physiologically based pharmacokinetic (WBPBPK) models is the tissue-to-plasma water partition coefficients (Kpu's). The predictability of Kpu values using mechanistically derived equations has been investigated for 7 very weak bases, 20 acids, 4 neutral drugs and 8 zwitterions in rat adipose, bone, brain, gut, heart, kidney, liver, lung, muscle, pancreas, skin, spleen and thymus. These equations incorporate expressions for dissolution in tissue water and, partitioning into neutral lipids and neutral phospholipids. Additionally, associations with acidic phospholipids were incorporated for zwitterions with a highly basic functionality, or extracellular proteins for the other compound classes. The affinity for these cellular constituents was determined from blood cell data or plasma protein binding, respectively. These equations assume drugs are passively distributed and that processes are nonsaturating. Resultant Kpu predictions were more accurate when compared to published equations, with 84% as opposed to 61% of the predicted values agreeing with experimental values to within a factor of 3. This improvement was largely due to the incorporation of distribution processes related to drug ionisation, an issue that is not addressed in earlier equations. Such advancements in parameter prediction will assist WBPBPK modelling, where time, cost and labour requirements greatly deter its application. (c) 2006 Wiley-Liss, Inc. and the American Pharmacists Association
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            Physiologically based pharmacokinetic modeling 1: predicting the tissue distribution of moderate-to-strong bases.

            Tissue-to-plasma water partition coefficients (Kpu's) form an integral part of whole body physiologically based pharmacokinetic (WBPBPK) models. This research aims to improve the predictability of Kpu values for moderate-to-strong bases (pK(a) > or = 7), by developing a mechanistic equation that accommodates the unique electrostatic interactions of such drugs with tissue acidic phospholipids, where the affinity of this interaction is readily estimated from drug blood cell binding data. Additional model constituents are drug partitioning into neutral lipids and neutral phospholipids, and drug dissolution in tissue water. Major assumptions of this equation are that electrostatic interactions predominate, drugs distribute passively, and non-saturating conditions prevail. Resultant Kpu predictions for 28 moderate-to-strong bases were significantly more accurate than published equations with 89%, compared to 45%, of the predictions being within a factor of three of experimental values in rat adipose, bone, gut, heart, kidney, liver, muscle, pancreas, skin, spleen and thymus. Predictions in rat brain and lung were less accurate probably due to the involvement of additional processes not incorporated within the equation. This overall improvement in prediction should facilitate the further application of WBPBPK modeling, where time, cost and labor requirements associated with experimentally determining Kpu's have, to a large extent, deterred its application. (c) 2005 Wiley-Liss, Inc. and
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              Metformin kinetics in healthy subjects and in patients with diabetes mellitus.

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Pharmaceutical Research
                Pharm Res
                Springer Science and Business Media LLC
                0724-8741
                1573-904X
                March 2022
                March 14 2022
                March 2022
                : 39
                : 3
                : 463-479
                Article
                10.1007/s11095-022-03211-3
                35288804
                78ae2a0a-57c8-4b9f-9efd-acc357d2729b
                © 2022

                https://www.springer.com/tdm

                https://www.springer.com/tdm

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