Physiologically-Based Pharmacokinetic-Pharmacodynamic Modeling of 1 ,25-Dihydroxyvitamin D3 in Mice

Ramakrishnan, Vidya; Yang, Quan; Quach, Holly P.; Cao, Yanguang; Chow, Edwin; Mager, Donald E.; Pang, K. Sandy

doi:10.1124/dmd.115.067033

Cited by 14 publications

(41 citation statements)

References 37 publications

(66 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Partition coefficient values for other organs were comparable to Ramakrishnan et al . (). This is of importance, due to the sparse number of vitamin D PBPK models available for comparison.…”

Section: Resultsmentioning

confidence: 97%

See 1 more Smart Citation

A physiologically based pharmacokinetic model of vitamin D

Sawyer

Tran

Evans

2017

J of Applied Toxicology

View full text Add to dashboard Cite

Despite the plethora of studies discussing the benefits of vitamin D on physiological functioning, few mathematical models of vitamin D predict the response of the body on low-concentration supplementation of vitamin D under sunlight-restricted conditions. This study developed a physiologically based pharmacokinetic (PBPK) model utilizing published human data on the metabolic cascade of orally derived, low-concentration (placebo, 5 μg and 10 μg) supplementation of vitamin D over the course of 28 days in the absence of sunlight. Vitamin D and its metabolites are highly lipophilic and binding assays of these compounds in serum may not account for binding by lipids and additional proteins. To compensate for the additional bound amounts, this study allowed the effective adipose-plasma partition coefficient to vary dynamically with the concentration of each compound in serum utilizing the Hill equation for binding. Through incorporating the optimized parameters with the adipose partition coefficient adaptation to the PBPK model, this study was able to fit serum concentration data for circulating vitamin D at all three supplementation concentrations within confidence intervals of the data. Copyright © 2017 John Wiley & Sons, Ltd.

show abstract

Section: Resultsmentioning

confidence: 97%

“…Following the methods of Ramakrishnan et al . (), this study scaled the blood flow to tissues by multiplying the blood flow by BP , the blood/plasma ratio, to model the rate of flow of plasma. The mass balance differential equations are based on Fig.…”

Section: Methodsmentioning

confidence: 99%

A physiologically based pharmacokinetic model of vitamin D

Sawyer

Tran

Evans

2017

J of Applied Toxicology

View full text Add to dashboard Cite

show abstract

“…The approach used here (i.e., organ perfusion data sets along with compartmental modeling) can be applied to the study of other organs (e.g., brain, kidney, and intestine), especially when the interplay between transport and metabolism is important. Similar approaches to model dynamic organ drug disposition can be used with other whole-body PK and PD models such as PBPK, hybrid-PBPK, and PK-PD models (Gertz et al, 2014;Ramakrishnan et al, 2016).…”

Section: Intracellular Unbound Atorvastatin Concentrationsmentioning

confidence: 99%

Intracellular Unbound Atorvastatin Concentrations in the Presence of Metabolism and Transport

Kulkarni¹,

Korzekwa²,

Nagar³

2016

Journal of Pharmacology and Experimental Therapeutics

View full text Add to dashboard Cite

Accurate prediction of drug target activity and rational dosing regimen design require knowledge of drug concentrations at the target. It is important to understand the impact of processes such as membrane permeability, partitioning, and active transport on intracellular drug concentrations. The present study aimed to predict intracellular unbound atorvastatin concentrations and characterize the effect of enzyme-transporter interplay on these concentrations. Single-pass liver perfusion studies were conducted in rats using atorvastatin (ATV, 1 mM) alone at 4°C and at 37°C in presence of rifampin (RIF, 20 mM) and 1-aminobenzotriazole (ABT, 1 mM), separately and in combination. The unbound intracellular ATV concentration was predicted with a five-compartment explicit membrane model using the parameterized diffusional influx clearance, active basolateral uptake clearance, and metabolic clearance.Chemical inhibition of uptake and metabolism at 37°C proved to be better controls relative to studies at 4°C. The predicted unbound intracellular concentration at the end of the 50-minute perfusion in the 1ABT , 1ABT1RIF, and the ATV-only groups was 6.5 mM, 0.58 mM, and 5.14 mM, respectively. The predicted total liver concentrations and amount recovered in bile were within 0.94-1.3 fold of the observed value in all groups. The fold difference in total liver concentration did not always extrapolate to the fold difference in predicted unbound concentration across groups. Together, these results support the use of compartmental modeling to predict intracellular concentrations in dynamic organ-based systems. These predictions can provide insight into the role of uptake transporters and metabolizing enzymes in determining drug tissue concentrations.

show abstract

“…Physiologically based pharmacokinetic (PBPK) modeling is an indispensable technique that is recognized as the preferred approach for the modeling of drugs and metabolites in a mechanistic fashion [1][2][3][4][5][6][7]. Built upon compartments of discrete volumes that are interconnected by blood flow, the model accommodates transmembrane barriers, transporters [8][9][10], disease conditions [11][12][13] and predicts drug-drug interactions [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

“…The same Equations (4 and 5) apply to the TM and SFM, with differences existing with f Q , being 1 for the TM and < 0.3 for the SFM. As shown in Figure 3, the % contribution for the removal by the intestine and liver of a drug in the circulation entering these tissues is dramatically different according to the TM and SFM, even for drugs [4] of identical CL int,met,L and CL int,met,I , simply because of the lower blood flow rate to the enterocyte region (f Q ) [47]. For the same given transport (CL in and CL ef ) and metabolic and secretory intrinsic clearances (CL int,met,I , CL int,sec,I and CL int,L =(CL int,met,L + CL int,sec,L )), the SFM predicts a lower F I than for the TM when the drug is given intravenously vs. that for the oral dose ( Figure 3A).…”

Section: Introductionmentioning

confidence: 99%

Unequivocal evidence supporting the segregated flow intestinal model that discriminates intestine versus liver first‐pass removal with PBPK modeling

Pang

Yang

Noh

2017

Biopharm & Drug Disp

View full text Add to dashboard Cite

Merits of the segregated flow model (SFM), highlighting the intestine as inert serosa and active enterocyte regions, with a smaller fractional (f < 0.3) intestinal flow (Q ) perfusing the enterocyte region, are described. Less drug in the circulation reaches the enterocytes due to the lower flow (f Q ) in comparison with drug administered into the gut lumen, fostering the idea of route-dependent intestinal removal. The SFM has been found superior to the traditional model (TM), which views the serosa and enterocytes totally as a well-mixed tissue perfused by 100% of the intestinal flow, Q . The SFM model is able to explain the lower extents of intestinal metabolism of enalapril, morphine and midazolam with i.v. vs. p.o. dosing. For morphine, the urine/bile ratio of the metabolite, morphine glucuronide MGurineMGbile for p.o. was 2.6× that of i.v. This was due to the higher proportion of intestinally formed morphine glucuronide, appearing more in urine than in bile due to its low permeability and greater extent of intestinal formation with p.o. administration. By contrast, the TM predicted the same MGurineMGbile for p.o. vs. i.v. The TM predicted that the contributions of the intestine:liver to first-pass removal were 46%:54% for both p.o. and i.v. The SFM predicted same 46%:54% (intestine:liver) for p.o., but 9%:91% for i.v. By contrast, the kinetics of codeine, the precursor of morphine, was described equally well by the SFM- and TM-PBPK models, a trend suggesting that intestinal metabolism of codeine is negligible. Fits to these PBPK models further provide insightful information towards metabolite formation: available fractions and the fractions of hepatic and total clearances that form the metabolite in question. The SFM-PBPK model is useful to identify not only the presence of intestinal metabolism but the contributions of the intestine and liver for metabolite formation. Copyright © 2016 John Wiley & Sons, Ltd.

show abstract

Physiologically-Based Pharmacokinetic-Pharmacodynamic Modeling of 1 ,25-Dihydroxyvitamin D3 in Mice

Cited by 14 publications

References 37 publications

A physiologically based pharmacokinetic model of vitamin D

A physiologically based pharmacokinetic model of vitamin D

Intracellular Unbound Atorvastatin Concentrations in the Presence of Metabolism and Transport

Unequivocal evidence supporting the segregated flow intestinal model that discriminates intestine versus liver first‐pass removal with PBPK modeling

Contact Info

Product

Resources

About