Physiologically Based Pharmacokinetic Approach Can Successfully Predict Pharmacokinetics of Citalopram in Different Patient Populations

Dysregulation of adipogenesis and disrupted lipid metabolism by the antidepressants citalopram and sertraline

Selective Serotonin Reuptake Inhibitors (SSRIs) are widely used medications for the treatment of major depressive disorder. However, long-term SSRI use has been associated with weight gain and altered lipid profiles. These findings suggest that SSRIs may have negative effects on metabolism. Exposure to certain chemicals called 'obesogens' is known to promote lipid accumulation and obesity by modulating adipogenesis. Here, we investigated whether citalopram (CIT) and sertraline (SER) interfere with the process of adipogenesis, using human mesenchymal stem cells (MSCs) in a 2D and a 3D model. Assessment of intracellular lipid accumulation by fluorescence staining was used as a measure for enhanced adipogenesis. To explore possible mechanisms behind SSRIs' effects, receptor mediated activity was studied using responsive cell lines for various nuclear receptors. Furthermore, RNA sequencing was performed in the 3D model, followed by differential gene expression and pathway analysis. A dose dependent increase in lipid accumulation was observed in both models with CIT and SER. For the 3D model, the effect was seen in a range close to reported steady-state plasma concentrations (0.065-0.65 μM for SER and 0.12-0.92 μM for CIT). Pathway analysis revealed unexpected results of downregulation in adipogenesis-related pathways and upregulation in phospholipids and lysosomal pathways. This was confirmed by an observed increase in lysosomes in the 2D model. Our findings suggest lysosomal dysfunction and disrupted lipid metabolism in mature adipocytes, leading to excessive phospholipid synthesis. Moreover, important adipogenic processes are inhibited, potentially leading to dysfunctional adipocytes, which might have implications in the maintenance of a healthy metabolic balance.

Phys-DAT: A physiologically-based pharmacokinetic model for unraveling the dissolution, transit and absorption processes using PhysPK®

BACKGROUND AND OBJECTIVE

In silico methods have become the key for efficiently testing and qualifying drug properties. Due to the complexity of the LADME processes and drug characteristics associated to oral drug absorption, there is a growing demand in the development of Physiologically-based Pharmacokinetic (PBPK) software with greater flexibility. Thus, the aims of this work are (i) to develop a mechanistic-based modeling framework of dissolution, transit and absorption (Phys-DAT) processes in the PhysPK platform and (ii) to assess the predictive power of the acausal MOOM methodology embedded in Phys-DAT versus reference ODE-based PBPK software.

METHODS

A PBPK model was developed including unreleased, undissolved and dissolved thermodynamic states of the drug. The gastrointestinal tract (GI) was represented by nine compartments and first-order transit kinetics was assumed for the drug fractions. Dissolution processes were described using solubility-independent or solubility-dependent mechanisms and pH effects. Linear transit and linear absorption mechanisms including gradual decrease absorption rate were considered to represent the passive diffusion process. Internal validation of the Phys-DAT model was performed through simulation-based analysis, considering different theoretical scenarios. External validation was carried out using in silico and in vivo data of GI segments and plasma concentrations. Both BCS I and II class drugs were included.

RESULTS

The model predicts plasma-concentration profiles of each compartment for undissolved, dissolved, and absorbed fractions using PhysPK® v.2.4.1. Internal and external validations demonstrate that the model aligned with the theoretical assumptions and accurately predicted Cmax, Tmax, and AUC 0-t for both BCS I and II drugs. Average Fold Error (AFE), Absolute Average Fold Error (AAFE), and Percent Prediction Error (PPE) calculations indicate good predictive performance, with predicted/observed ratios falling within the acceptable range.

CONCLUSIONS

Phys-DAT represents a mechanistic model for predicting oral absorption, including the dissolution, pH effect, transit, and absorption processes. PhysPK has shown to be a tool with strong prediction accuracy, similar to the obtained by ODE-based PBPK reference software, and the results obtained with the Phys-DAT model for oral administered drugs showed predictive reliability in healthy volunteers, setting the basis to determine the interchangeability of the acausal MOOM methodology with other modeling approaches.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

Assembling the P450 puzzle: on the sources of nonadditivity in drug metabolism

There is an increasing number of indications of an oversimplification in the premise that the cumulative properties of the human drug-metabolizing ensemble represent a simple aggregate of the properties of the constituting enzymes. Recent studies of the functional effects of hetero-association of multiple cytochrome P450 species and their interactions with metabolically related enzymes revealed a tight integration in the drug-metabolizing ensemble. In our opinion, the sources of interindividual variability in drug metabolism can be elucidated only when considering this ensemble as a multienzyme system, the functional parameters of which are determined by interactions between its constituents. In this article, we present a conceptual model providing a mechanistic explanation for the functional effects of the interactions between multiple P450 species and propose a clue to understanding the nonadditive behavior of the drug-metabolizing ensemble.

Exploring Molecular Approaches in Amyotrophic Lateral Sclerosis: Drug Targets from Clinical and Pre-Clinical Findings

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease (MND) characterized by the death of upper and lower motor neurons (corticospinal tract) in the motor cortex, basal ganglia, brain stem, and spinal cord. The patient experiences the sign and symptoms between 55 to 75 years of age, which include impaired motor movement, difficulty in speaking and swallowing, grip loss, muscle atrophy, spasticity, and sometimes associated with memory and cognitive impairments. Median survival is 3 to 5 years after diagnosis and 5 to 10% of the patients live for more than 10 years. The limited intervention of pharmacologically active compounds, that are used clinically, is majorly associated with the narrow therapeutic index. Pre-clinically established experimental models, where neurotoxin methyl mercury mimics the ALS like behavioural and neurochemical alterations in rodents associated with neuronal mitochondrial dysfunctions and downregulation of adenyl cyclase mediated cAMP/CREB, is the main pathological hallmark for the progression of ALS in central as well in the peripheral nervous system. Despite the considerable investigation into neuroprotection, it still constrains treatment choices to strong care and organization of ALS complications. Therefore, this current review specially targeted the investigation of clinical and pre-clinical features available for ALS to understand the pathogenic mechanisms and to explore the pharmacological interventions associated with the up-regulation of intracellular adenyl cyclase/cAMP/ CREB and activation of mitochondrial-ETC coenzyme-Q10 as a future drug target in the amelioration of ALS mediated motor neuronal dysfunctions.

Physiologically based pharmacokinetic modelling of treprostinil after intravenous injection and extended-release oral tablet administration in healthy volunteers: An extrapolation to other patient populations including patients with hepatic impairment

AIMS

Pulmonary arterial hypertension (PAH) is characterized by increased pulmonary arterial pressure, resulting in right ventricular overload, right heart failure and eventually death. Treprostinil is a prostacyclin analogue that is used in the treatment of PAH. As an orphan drug, limited information is available regarding its disposition and its use in special populations such as elderly, paediatric and pregnant patients. The objective of the current study was to develop a robust physiologically based pharmacokinetic (PBPK) model for treprostinil intravenous injection and extended-release tablet as the first step to optimize treprostinil pharmacotherapy in patients.

METHODS

PBPK model was built using Simcyp simulator which integrated physicochemical properties, observed or predicted parameters for drug absorption, distribution and elimination for treprostinil, and population specific physiological characteristics. Three clinical trials after intravenous infusion and nine studies after oral administration of treprostinil extended-release tablet in healthy volunteers were used to develop and validate the model. The simulated PK profiles were compared with the observed data. Extrapolation of the model to patient populations including patients with hepatic impairment was conducted to validate the predictions.

RESULTS

Most of the observed data were within the 5^th and 95^th percentile interval of the prediction. Most of the percentage error in the PK parameters were within ±50% of the corresponding observed parameters. The developed model predicted the lung exposure of treprostinil to be approximately 0.17 times of concentration in plasma.

CONCLUSION

Predicted absorption, distribution, and metabolic enzyme kinetics gave an insight into the disposition of treprostinil in humans. Extrapolation of the established model to patient populations with hepatic impairment successfully documented the model reliability. The developed model has the potential to be used in the PK predictions in other special patient populations with different demographic, physiological and pathological characteristics.

A physiologically based pharmacokinetic analysis to predict the pharmacokinetics of intravenous isavuconazole in patients with or without hepatic impairment

Isavuconazole (ISA) is an azole antifungal used in the treatment of invasive aspergillosis and mucormycosis. Patients with mild and moderate hepatic impairment have lower clearance (CL) as compared to the healthy population. Currently, there is no data on ISA in patients with severe hepatic impairment (Child-Pugh Class C). The purpose of this study was to build a physiologically based pharmacokinetic (PBPK) model to describe the pharmacokinetics (PK) of intravenous ISA, and to predict changes in ISA disposition in different patient populations and in patients with hepatic impairment to guide personalized dosing. By incorporating the systemic and drug specific parameters of ISA, the model was initially developed in healthy population and validated with 10 independent PK profiles obtained from healthy subjects and from patients with normal liver function. The results showed a satisfactory predictive capacity, with most of the relative predictive errors being between ±30% for area under the curve (AUC) and C_max The observed plasma concentration-time profiles of ISA were well described by the model predicted profiles. The model adequately predicted the reduced CL of ISA in patients with mild and moderate hepatic impairment. Furthermore, the model predicted a decrease in CL of about 60% in patients with severe hepatic impairment. Therefore, we recommend reducing the dose by 50% in patients with severe hepatic impairment. The model also predicted differences in the PK of ISA between Caucasian and Asian population, with the CL ratio of 0.67 in Chinese vs Caucasian population. The developed PBPK model of ISA provides a reasonable approach for optimizing the dosage regimen in different ethnic populations and in patients with severe hepatic impairment.