Systematic review of physiologically based kinetic lactation models for transfer of xenobiotic compounds to milk.

Lactational elimination has been described mathematically for nearly 50 years. Over 40 published articles, containing >50 physiologically based kinetic (PBK) lactation models were included in the systematic review. These PBK models described the lactational elimination of xenobiotic compounds in humans, rats, mice, and dairy cows and goats. A total of 78 compounds have been modelled, ranging from industrial chemicals, pesticides, to pain medication, antibiotics, and caffeine. Few models included several species or compounds, and models were thus generally not translational or generic. Three dairy cow models mechanistically described the intramammary disposition of pharmaceuticals after intramammary administration, including volume changes caused by milking, while empirically describing the remaining pharmacokinetics. The remaining models were semi- or whole body PBK models, describing long-term exposure of environmental pollutants, or short-term exposure of pharmaceuticals. The absolute majority described the disposition to the mammary gland or milk with perfusion limited compartments, but permeability limited models were available as well. With long-term exposure, models often included changes in milk volume and/or consumption by the offspring, and changes in body weight of offspring. Periodic emptying of the mammary gland, as with feeding or milking, was sparsely applied. Rodent models used similar physiological parameters, while values of physiological parameters applied in human models could range widely. When milk composition was included in the models, it most often included the fat content. The review gives an extensive overview of the applied functions and modelling strategies of PBK lactation models.

Physiological based pharmacokinetic and biopharmaceutics modelling of subcutaneously administered compounds - An overview of in silico models.

Subcutaneous injection is a commonly used route of drug administration for both small molecules and biologics. To facilitate the development of new subcutaneously administered drugs, methods for prediction of drug absorption from the injection site are essential. For this purpose, in silico models have increasingly been used. This report summarize the current state of in silico models for description and prediction of subcutaneous drug absorption. Original articles on physiologically based models describing subcutaneous administration published from 2010 and onward were reviewed. Eighteen physiologically based models were identified: eleven for small molecules and seven for biologics. Most models described the PK of one drug and for one species. In models for small molecules, the subcutaneous administration site was most often described as a depot compartment with first-order absorption into the plasma or blood. Most models for biologics divided administration and organ compartments into vascular and interstitial subcompartments. Mass transfer to these compartments was frequently described with convection and diffusion, according to the one- or two-pore theory. Tremendous improvement in the quantitative aspects of subcutaneous administration and subsequent absorption of physiologically based models has occurred the last decade. However, improvements related to data translation and generalization of these models were identified.

Overview of authorized drug products for subcutaneous administration: Pharmaceutical, therapeutic, and physicochemical properties.

There is a growing body of research about subcutaneously administered biologics, emphasizing the need for optimized bioavailability predictions. It is important to inform both translational and in silico models with properties of the drug products and compounds. However, the pharmaceutical, therapeutic and physicochemical properties of market authorized drug products for subcutaneous administration are currently not collated in the public domain. We provide an overview of subcutaneous administered drug products for humans and animals market authorized in EU, Canada, and the US. Data on the drug products were collected from the respective authorities, i.e. European Medicines Agency, Health Canada, and U.S. Food and Drug Administration. Physicochemical properties of active substances were gathered from DrugBank. Human drug products were often indicated for treatment of diabetes and anemia. EU veterinary drug products were often immunologicals. Canadian and US veterinary drug products often acted as antiinfectives for systemic use, on the genito-urinary system or as sex hormones. The final dataset with >1700 subcutaneous drug products is provided. In EU drug products, the majority of active substances were biologics. In the US, drug products most often contained small molecules. Solutions, emulsions and suspensions were the most common dosage forms. A minority of subcutaneous drug products were also registered for intramuscular or intravenous administration. The analysis presented here could aid further research, exploring formulation properties, prescription or sales of market authorized SC drug products and development of inclusive in silico models.

Gastrointestinal mucus in dog: Physiological characteristics, composition, and structural properties.

Gastrointestinal (GI) mucus is continuously secreted and lines the entire length of the GI tract. Essential for health, it keeps the noxious luminal content away from the epithelium. Our aim was to characterize the composition and structure of mucus throughout the various GI segments in dog. Mucus was collected from the stomach, small intestine (duodenum, jejunum, ileum), and large intestine (cecum, proximal and distal colon) from dogs. Composition was determined by multi-omics. Structural properties were investigated using cryoSEM and rheology. GI mucus contained 74-95% water and maintained a pH around 6.5. The proteome was similar across the different GI segments. The highest abundant secreted gel-forming mucin in the gastric mucus was mucin 5AC, whether mucin 2 had highest abundance in the intestinal mucus. Lipid and metabolite abundance was generally higher in the jejunal mucus than the colonic mucus. CryoSEM microscopy revealed smaller pore size in small intestinal mucus, which increased in the large intestine. All mucus samples showed shear-thinning behavior and characteristics of gel-like structure. In conclusion, the mucus is a highly viscous and hydrated material. These data provide an important baseline for future studies on human and canine intestinal diseases and the dog model in drug absorption.

Physiological properties, composition and structural profiling of porcine gastrointestinal mucus.

The gastrointestinal mucus is a hydrogel that lines the luminal side of the gastrointestinal epithelium, offering barrier protection from pathogens and lubrication of the intraluminal contents. These barrier properties likewise affect nutrients and drugs that need to penetrate the mucus to reach the epithelium prior to absorption. In order to assess the potential impact of the mucus on drug absorption, we need information about the nature of the gastrointestinal mucus. Today, most of the relevant available literature is mainly derived from rodent studies. In this work, we used a larger animal species, the pig model, to characterize the mucus throughout the length of the gastrointestinal tract. This is the first report of the physiological properties (physical appearance, pH and water content), composition (protein, lipid and metabolite content) and structural profiling (rheology and gel network) of the porcine gastrointestinal mucus. These findings allow for direct comparisons between the characteristics of mucus from various segments and can be further utilized to improve our understanding of the role of the mucus on region dependent drug absorption. Additionally, the present work is expected to contribute to the assessment of the porcine model as a preclinical species in the drug development process.

Liver Cancer Cell Lines Treated with Doxorubicin under Normoxia and Hypoxia: Cell Viability and Oncologic Protein Profile.

Hepatocellular carcinoma is often treated with a combination of doxorubicin and embolization, exposing it to high concentrations and hypoxia. Separation of the possible synergistic effect of this combination in vivo is difficult. Here, treatment with doxorubicin, under hypoxia or normoxia in different liver cancer cell lines, was evaluated. Liver cancer cells HepG2, Huh7, and SNU449 were exposed to doxorubicin, hypoxia, or doxorubicin + hypoxia with different duration. Treatment response was evaluated with cell viability, apoptosis, oxidative stress, and summarized with IC50. The protein profile of a 92-biomarker panel was analyzed on cells treated with 0 or 0.1 µM doxorubicin during 6 or 72 h, under normoxia or hypoxia. Hypoxia decreased viability of HepG2 and SNU499. HepG2 was least and SNU449 most tolerant to doxorubicin treatment. Cytotoxicity of doxorubicin increased over time in HepG2 and Huh7. The combination of doxorubicin + hypoxia affected the cells differently. Normalized protein expression was lower for HepG2 than Huh7 and SNU449. Hierarchical clustering separated HepG2 from Huh7 and SNU449. These three commonly used cell lines have critically different responses to chemotherapy and hypoxia, which was reflected in their different protein expression profile. These different responses suggest that tumors can respond differently to the combination of local chemotherapy and embolization.

Porcine and Human In Vivo Simulations for Doxorubicin-Containing Formulations Used in Locoregional Hepatocellular Carcinoma Treatment.

It is important to be able to simulate and predict formulation effects on the pharmacokinetics of a drug in order to optimize effectivity in clinical practice and drug development. Two formulations containing doxorubicin are used in the treatment of hepatocellular carcinoma (HCC): a Lipiodol-based emulsion (LIPDOX) and a loadable microbead system (DEBDOX). Although equally effective, the formulations are vastly different, and little is known about the parameters affecting doxorubicin release in vivo. However, mathematical modeling can be used to predict doxorubicin release properties from these formulations and its in vivo pharmacokinetic (PK) profiles. A porcine semi-physiologically based pharmacokinetic (PBPK) model was scaled to a human physiologically based biopharmaceutical (PBBP) model that was altered to include HCC. DOX in vitro and in vivo release data from LIPDOX or DEBDOX were collected from the literature and combined with these in silico models. The simulated pharmacokinetic profiles were then compared with observed porcine and human HCC patient data. DOX pharmacokinetic profiles of LIPDOX-treated HCC patients were best predicted from release data sets acquired by in vitro methods that did not use a diffusion barrier. For the DEBDOX group, the best predictions were from the in vitro release method with a low ion concentration and a reduced loading dose. The in silico modeling combined with historical release data was effective in predicting in vivo plasma exposure. This can give useful insights into the release method properties necessary for correct in vivo predictions of pharmacokinetic profiles of HCC patients dosed with LIPDOX or DEBDOX.

A Model-Based Approach To Assessing the Importance of Intracellular Binding Sites in Doxorubicin Disposition.

Doxorubicin is an anticancer agent, which binds reversibly to topoisomerase I and II, intercalates to DNA base pairs, and generates free radicals. Doxorubicin has a high tissue:plasma partition coefficient and high intracellular binding to the nucleus and other subcellular compartments. The metabolite doxorubicinol has an extensive tissue distribution. This porcine study investigated whether the traditional implementation of tissue binding, described by the tissue:plasma partition coefficient (Kp,t), could be used to appropriately analyze and/or simulate tissue doxorubicin and doxorubicinol concentrations in healthy pigs, when applying a physiologically based pharmacokinetic (PBPK) model approach, or whether intracellular binding is required in the semi-PBPK model. Two semi-PBPK models were developed and evaluated using doxorubicin and doxorubicinol concentrations in healthy pig blood, bile, and urine and kidney and liver tissues. In the generic semi-PBPK model, tissue binding was described using the conventional Kp,t approach. In the binding-specific semi-PBPK model, tissue binding was described using intracellular binding sites. The best semi-PBPK model was validated against a second data set of healthy pig blood and bile concentrations. Both models could be used for analysis and simulations of biliary and urinary excretion of doxorubicin and doxorubicinol and plasma doxorubicinol concentrations in pigs, but the binding-specific model was better at describing plasma doxorubicin concentrations. Porcine tissue concentrations were 400- to 1250-fold better captured by the binding-specific model. This model adequately predicted plasma doxorubicin concentration-time and biliary doxorubicin excretion profiles against the validation data set. The semi-PBPK models applied were similarly effective for analysis of plasma concentrations and biliary and urinary excretion of doxorubicin and doxorubicinol in healthy pigs. Inclusion of intracellular binding in the doxorubicin semi-PBPK models was important to accurately describe tissue concentrations during in vivo conditions.

In Vivo Drug Delivery Performance of Lipiodol-Based Emulsion or Drug-Eluting Beads in Patients with Hepatocellular Carcinoma.

Doxorubicin (DOX) delivered in a lipiodol-based emulsion (LIPDOX) or in drug-eluting beads (DEBDOX) is used as palliative treatment in patients with intermediate-stage hepatocellular carcinoma (HCC). The primary objective of this study was to evaluate the in vivo delivery performance of DOX from LIPDOX or DEBDOX in HCC patients using the local and systemic pharmacokinetics of DOX and its main metabolite doxorubicinol (DOXol). Urinary excretion of DOX and DOXol and their short-term safety and antitumor effects were also evaluated. In this open, prospective, nonrandomized multicenter study, LIPDOX (n = 13) or DEBDOX (n = 12) were injected into the feeding arteries of the tumor. Local (vena cava/hepatic vein orifice) and systemic (peripheral vein) plasma concentrations of DOX and DOXol were determined in samples obtained up to 6 h and 7 days after treatment. Tumor response was assessed using computed tomography or magnetic resonance imaging. The Cmax and AUC0-24 h for DOX were 5.6-fold and 2.4-fold higher in LIPDOX vs DEBDOX recipients, respectively (p < 0.001). After 6 h, the respective mean proportions of the dose remaining in the liver or drug-delivery system (DDS) were 49% for LIPDOX and 88% for DEBDOX. LIPDOX releases DOX faster than DEBDOX in HCC patients and provides more extensive local and systemic exposure (AUC) to DOX and DOXol initially (0-7 days). DEBDOX formulation has a release and distribution of DOX that is more restricted and rate controlled than LIPDOX.

Lipiodol does not affect the tissue distribution of intravenous doxorubicin infusion in pigs.

OBJECTIVES: In liver cancer treatment, lipiodol is used as a pharmaceutical excipient to improve delivery of the cytostatic drug doxorubicin (DOX). As DOX and its metabolite doxorubicinol (DOXol) cause serious off-target adverse effects, we investigated the effects of drug-free lipiodol or ciclosporin (CsA) on the tissue distribution (Kp ) of DOX and DOXol in relevant pig tissues. METHODS: Four treatment groups (TI-TIV) all received an intravenous DOX solution at 0 and 200 min. Before the second dose, the pigs received a portal vein infusion of saline (TI), lipiodol (TII), CsA (TIII) or lipiodol and CsA (TIV). After 6 h, the pigs were euthanised, and liver, kidney, heart and intestine samples were collected and analysed. KEY FINDINGS: The tissue DOX concentrations were highest in the kidney (TI-TIV). All the investigated tissues showed extensive DOX Kp . Lipiodol had no effect on the Kp of DOX to any of the tissues. However, the tissue concentrations of DOX were increased by CsA (in liver, kidney and intestine, P < 0.05). CONCLUSION: Lipiodol injected into the portal vein does not affect the tissue distribution of DOX and DOXol.

Treatment of intermediate stage hepatocellular carcinoma: a review of intrahepatic doxorubicin drug-delivery systems.

The biopharmaceutical properties of doxorubicin delivered via two drug-delivery systems (DDSs) for the palliative treatment of unresectable hepatocellular carcinoma were reviewed with relation to the associated liver and tumor (patho)physiology. These two DDSs, doxorubicin emulsified with Lipiodol(®) and doxorubicin loaded into DC Bead(®) are different regarding tumor delivery, release rate, local bioavailability, if and how they can be given repeatedly, biodegradability, length of embolization and safety profile. There have been few direct head-to-head comparisons of these DDSs, and in-depth investigations into their in vitro and in vivo performance is warranted.

The effects of lipiodol and cyclosporin A on the hepatobiliary disposition of doxorubicin in pigs.

Doxorubicin (DOX) emulsified in Lipiodol (LIP) is used as local palliative treatment for unresectable intermediate stage hepatocellular carcinoma. The objective of this study was to examine the poorly understood effects of the main excipient in the drug delivery system, LIP, alone or together with cyclosporin A (CsA), on the in vivo liver disposition of DOX and its active metabolite doxorubicinol (DOXol). The advanced, multi-sampling-site, acute pig model was used; samples were collected from three blood vessels (v. portae, v. hepatica and v. femoralis), bile and urine. The four treatment groups (TI-TIV) all received two intravenous 5 min infusions of DOX into an ear vein: at 0 and 200 min. Before the second dose, the pigs received a portal vein infusion of saline (TI), LIP (TII), CsA (TIII) or LIP and CsA (TIV). Concentrations of DOX and DOXol were analyzed using UPLC-MS/MS. The developed multicompartment model described the distribution of DOX and DOXol in plasma, bile and urine. LIP did not affect the pharmacokinetics of DOX or DOXol. CsA (TIII and TIV) had no effect on the plasma pharmacokinetics of DOX, but a 2-fold increase in exposure to DOXol and a significant decrease in hepatobiliary clearance of DOX and DOXol were observed. Model simulations supported that CsA inhibits 99% of canalicular biliary secretion of both DOX and DOXol, but does not affect the metabolism of DOX to DOXol. In conclusion, LIP did not directly interact with transporters, enzymes and/or biological membranes important for the hepatobiliary disposition of DOX.

Quantification of tacrolimus and three demethylated metabolites in human whole blood using LC-ESI-MS/MS.

BACKGROUND: A bioalanytical method for the quantification of tacrolimus (TAC) and 3 metabolites, 13-O, 15-O, and 31-O-demethylated TAC (M-I, M-III, and M-II) in human whole blood using liquid chromatography, electrospray ionization, tandem mass spectrometry (LC-ESI-MS/MS) was developed and validated. METHOD: The analytes were extracted from 85 µL of blood by protein precipitation followed by solid-phase extraction and a concentration step. The analytes and the internal standard (IS, ascomycin) were separated on a C18 column using a slow gradient mobile phase elution, with an analysis time of 3.3 minutes. The ammonium-adduct ions with transitions of m/z 821.5 > 768.7 (TAC), 807.5 > 754.7 (M-I, M-III, M-II), and 809.4 > 756.7 (IS) were measured in selected reaction monitoring mode using electrospray ionization. RESULTS: Measuring ranges were 0.1-50 ng/mL for M-II, M-III, and TAC and 0.15-39 ng/mL for M-I. Imprecision in quantification was <20% for all analytes, whereas accuracy was within ±20%. Recovery was calculated to be >50% for all analytes. The sample's stability was proven for 1 month at -20°C and 72 hours at room temperature. Three freeze-thaw cycles had no significant effect on the stability. The prepared samples were stable at least 16 hours at 8°C. Analysis of 53 patient samples resulted in average concentrations of 7.2 for TAC, 0.8 for M-I, 0.4 for M-III, and 0.2 ng/mL for M-II. The total metabolite concentration was 17% (4%-52%) of the TAC concentration. The TAC concentration measured by LC-MS/MS was 36.1% ± 27.1% lower than by immunochemical (enzyme multiplied immunoassay technique) analysis. When adding the metabolite crossreactivity in the presence of TAC, the difference between the 2 methods was still 29.8% ± 28.3%, indicating that the overestimation of TAC concentration of enzyme multiplied immunoassay technique compared with liquid chromatography-tandem mass spectrometry cannot only be ascribed to the demethylated metabolites. CONCLUSIONS: An LC-ESI-MS/MS method for the quantitative analysis of TAC and 3 metabolites, using a 2-step sample preparation was successfully developed, validated, and applied on 53 patient samples.