Literature DB >> 33340340

Parameterization of Microsomal and Cytosolic Scaling Factors: Methodological and Biological Considerations for Scalar Derivation and Validation.

Michael J Doerksen1, Robert S Jones2, Michael W H Coughtrie1, Abby C Collier3.   

Abstract

Mathematical models that can predict the kinetics of compounds have been increasingly adopted for drug development and risk assessment. Data for these models may be generated from in vitro experimental systems containing enzymes contributing to metabolic clearance, such as subcellular tissue fractions including microsomes and cytosol. Extrapolation from these systems is facilitated by common scaling factors, known as microsomal protein per gram (MPPG) and cytosolic protein per gram (CPPG). Historically, parameterization of MPPG and CPPG has employed the use of recovery factors, commonly benchmarked to cytochromes P450 which work well in some contexts, but could be problematic for other enzymes. Here, we propose absolute quantification of protein content and supplementary assays to evaluate microsomal/cytosolic purity that should be employed. Examples include calculation of microsomal latency by mannose-6-phosphatase activity and immunoblotting of subcellular fractions with fraction-specific markers. Further considerations include tissue source, as disease states can affect enzyme expression and activity, and the methodology used for scalar parameterization. Regional- and organ-specific expression of enzymes, in addition to differences in organ physiology, is another important consideration. Because most efforts have focused on the liver that is, for the most part, homogeneous, derived scalars may not capture the heterogeneity of other major tissues contributing to xenobiotic metabolism including the kidneys and small intestine. Better understanding of these scalars, and how to appropriately derive them from extrahepatic tissues can provide support to the inferences made with physiologically based pharmacokinetic modeling, increase its accuracy in characterizing in vivo drug pharmacokinetics, and improve confidence in go-no-go decisions for clinical trials.

Year:  2020        PMID: 33340340     DOI: 10.1007/s13318-020-00666-w

Source DB:  PubMed          Journal:  Eur J Drug Metab Pharmacokinet        ISSN: 0378-7966            Impact factor:   2.441


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