Proteomics-Informed Prediction of Rosuvastatin Plasma Profiles in Patients With a Wide Range of Body Weight

Physiologically based pharmacokinetics modeling and transporter proteomics to predict systemic and local liver and muscle disposition of statins

Statins are used to reduce liver cholesterol levels but also carry a dose-related risk of skeletal muscle toxicity. Concentrations of statins in plasma are often used to assess efficacy and safety, but because statins are substrates of membrane transporters that are present in diverse tissues, local differences in intracellular tissue concentrations cannot be ruled out. Thus, plasma concentration may not be an adequate indicator of efficacy and toxicity. To bridge this gap, we used physiologically based pharmacokinetic (PBPK) modeling to predict intracellular concentrations of statins. Quantitative data on transporter clearance were scaled from in vitro to in vivo conditions by integrating targeted proteomics and transporter kinetics data. The developed PBPK models, informed by proteomics, suggested that organic anion-transporting polypeptide 2B1 (OATP2B1) and multidrug resistance-associated protein 1 (MRP1) play a pivotal role in the distribution of statins in muscle. Using these PBPK models, we were able to predict the impact of alterations in transporter function due to genotype or drug-drug interactions on statin systemic concentrations and exposure in liver and muscle. These results underscore the potential of proteomics-guided PBPK modeling to scale transporter clearance from in vitro data to real-world implications. It is important to evaluate the role of drug transporters when predicting tissue exposure associated with on- and off-target effects.

Membrane transporters in drug development and as determinants of precision medicine

The effect of membrane transporters on drug disposition, efficacy and safety is now well recognized. Since the initial publication from the International Transporter Consortium, significant progress has been made in understanding the roles and functions of transporters, as well as in the development of tools and models to assess and predict transporter-mediated activity, toxicity and drug-drug interactions (DDIs). Notable advances include an increased understanding of the effects of intrinsic and extrinsic factors on transporter activity, the application of physiologically based pharmacokinetic modelling in predicting transporter-mediated drug disposition, the identification of endogenous biomarkers to assess transporter-mediated DDIs and the determination of the cryogenic electron microscopy structures of SLC and ABC transporters. This article provides an overview of these key developments, highlighting unanswered questions, regulatory considerations and future directions.

In silico modeling and simulation of organ-on-a-chip systems to support data analysis and a priori experimental design

Organ-on-a-chip (OoC) systems are a promising new class of in vitro devices that can combine various tissues, cultured in different compartments, linked by media flow. The properties of these novel in vitro systems linked to increased physiological relevance of culture conditions may lead to more in vivo-relevant cell phenotypes, enabling better in vitro pharmacology and toxicology assessment. Improved cell activities combined with longer lasting cultures offer opportunities to improve the characterization of absorption, distribution, metabolism, and excretion (ADME) processes, potentially leading to more accurate prediction of human pharmacokinetics (PKs). The inclusion of barrier tissue elements and metabolically competent tissue types results in complex concentration-time profiles (in vitro PK) for test drugs and their metabolites that require appropriate mathematical modeling of in vitro data for parameter estimation. In particular, modeling is critical to estimate in vitro ADME parameters when multiple different tissues are combined in a single device. Therefore, sophisticated in silico data analysis and a priori experimental design are highly recommended for OoC experiments in a manner not needed with standard ADME screening. The design of the experiment should be optimized based on an investigation of the structural characteristics of the in vitro system, the ADME features of the test compound and any available knowledge of cell phenotypes. This tutorial aims to provide such a modeling framework to inform experimental design and refine parameter estimation in a Gut-Liver OoC (the most studied multi-organ systems to predict the oral drug PKs) to improve translatability of data generated in such complex cellular systems.

Proteome deconvolution of liver biopsies reveals hepatic cell composition as an important marker of fibrosis

Human liver tissue is composed of heterogeneous mixtures of different cell types and their cellular stoichiometry can provide information on hepatic physiology and disease progression. Deconvolution algorithms for the identification of cell types and their proportions have recently been developed for transcriptomic data. However, no method for the deconvolution of bulk proteomics data has been presented to date. Here, we show that proteomes, which usually contain less data than transcriptomes, can provide useful information for cell type deconvolution using different algorithms. We demonstrate that proteomes from defined mixtures of cell lines, isolated primary liver cells, and human liver biopsies can be deconvoluted with high accuracy. In contrast to transcriptome-based deconvolution, liver tissue proteomes also provided information about extracellular compartments. Using deconvolution of proteomics data from liver biopsies of 56 patients undergoing Roux-en-Y gastric bypass surgery we show that proportions of immune and stellate cells correlate with inflammatory markers and altered composition of extracellular matrix proteins characteristic of early-stage fibrosis. Our results thus demonstrate that proteome deconvolution can be used as a molecular microscope for investigations of the composition of cell types, extracellular compartments, and for exploring cell-type specific pathological events. We anticipate that these findings will allow the refinement of retrospective analyses of the growing number of proteome datasets from various liver disease states and pave the way for AI-supported clinical and preclinical diagnostics.

Modeling Clinical Phenotype Variability: Consideration of Genomic Variations, Computational Methods, and Quantitative Proteomics

Advances in biomedical and computer technologies have presented the modeling community the opportunity for mechanistically modeling and simulating the variability in a disease phenotype or in a drug response. The capability to quantify response variability can inform a drug development program. Quantitative systems pharmacology scientists have published various computational approaches for creating virtual patient populations (VPops) to model and simulate drug response variability. Genomic variations can impact disease characteristics and drug exposure and response. Quantitative proteomics technologies are increasingly used to facilitate drug discovery and development and inform patient care. Incorporating variations in genomics and quantitative proteomics may potentially inform creation of VPops to model and simulate virtual patient trials, and may help account for, in a predictive manner, phenotypic variations observed clinically.

Neither Gastric Bypass Surgery Nor Diet-Induced Weight-Loss Affect OATP1B1 Activity as Measured by Rosuvastatin Oral Clearance

INTRODUCTION

Rosuvastatin pharmacokinetics is mainly dependent on the activity of hepatic uptake transporter OATP1B1. In this study, we aimed to investigate and disentangle the effect of Roux-en-Y gastric bypass (RYGB) and weight loss on oral clearance (CL/F) of rosuvastatin as a measure of OATP1B1-activity.

METHODS

Patients with severe obesity preparing for RYGB (n = 40) or diet-induced weight loss (n = 40) were included and followed for 2 years, with four 24-hour pharmacokinetic investigations. Both groups underwent a 3-week low-energy diet (LED; < 1200 kcal/day), followed by RYGB or a 6-week very-low-energy diet (VLED; < 800 kcal/day).

RESULTS

A total of 80 patients were included in the RYGB group (40 patients) and diet-group (40 patients). The weight loss was similar between the groups following LED and RYGB. The LED induced a similar (mean [95% CI]) decrease in CL/F in both intervention groups (RYGB: 16% [0, 31], diet: 23% [8, 38]), but neither induced VLED resulted in any further changes in CL/F. At Year 2, CL/F had increased by 21% from baseline in the RYGB group, while it was unaltered in the diet group. Patients expressing the reduced function SLCO1B1 variants (c.521TC/CC) showed similar changes in CL/F over time compared with patients expressing the wild-type variant.

CONCLUSIONS

Neither body weight, weight loss nor RYGB per se seem to affect OATP1B1 activity to a clinically relevant degree. Overall, the observed changes in rosuvastatin pharmacokinetics were minor, and unlikely to be of clinical relevance.

Quantitative Proteomics in Translational Absorption, Distribution, Metabolism, and Excretion and Precision Medicine

A reliable translation of in vitro and preclinical data on drug absorption, distribution, metabolism, and excretion (ADME) to humans is important for safe and effective drug development. Precision medicine that is expected to provide the right clinical dose for the right patient at the right time requires a comprehensive understanding of population factors affecting drug disposition and response. Characterization of drug-metabolizing enzymes and transporters for the protein abundance and their interindividual as well as differential tissue and cross-species variabilities is important for translational ADME and precision medicine. This review first provides a brief overview of quantitative proteomics principles including liquid chromatography-tandem mass spectrometry tools, data acquisition approaches, proteomics sample preparation techniques, and quality controls for ensuring rigor and reproducibility in protein quantification data. Then, potential applications of quantitative proteomics in the translation of in vitro and preclinical data as well as prediction of interindividual variability are discussed in detail with tabulated examples. The applications of quantitative proteomics data in physiologically based pharmacokinetic modeling for ADME prediction are discussed with representative case examples. Finally, various considerations for reliable quantitative proteomics analysis for translational ADME and precision medicine and the future directions are discussed. SIGNIFICANCE STATEMENT: Quantitative proteomics analysis of drug-metabolizing enzymes and transporters in humans and preclinical species provides key physiological information that assists in the translation of in vitro and preclinical data to humans. This review provides the principles and applications of quantitative proteomics in characterizing in vitro, ex vivo, and preclinical models for translational research and interindividual variability prediction. Integration of these data into physiologically based pharmacokinetic modeling is proving to be critical for safe, effective, timely, and cost-effective drug development.

Repository Describing the Anatomical, Physiological, and Biological Changes in an Obese Population to Inform Physiologically Based Pharmacokinetic Models

Background

Obesity is associated with physiological changes that can affect drug pharmacokinetics. Obese individuals are underrepresented in clinical trials, leading to a lack of evidence-based dosing recommendations for many drugs. Physiologically based pharmacokinetic (PBPK) modelling can overcome this limitation but necessitates a detailed description of the population characteristics under investigation.

Objective

The purpose of this study was to develop and verify a repository of the current anatomical, physiological, and biological data of obese individuals, including population variability, to inform a PBPK framework.

Methods

A systematic literature search was performed to collate anatomical, physiological, and biological parameters for obese individuals. Multiple regression analyses were used to derive mathematical equations describing the continuous effect of body mass index (BMI) within the range 18.5–60 kg/m² on system parameters.

Results

In total, 209 studies were included in the database. The literature reported mostly BMI-related changes in organ weight, whereas data on blood flow and biological parameters (i.e. enzyme abundance) were sparse, and hence physiologically plausible assumptions were made when needed. The developed obese population was implemented in Matlab^® and the predicted system parameters obtained from 1000 virtual individuals were in agreement with observed data from an independent validation obese population. Our analysis indicates that a threefold increase in BMI, from 20 to 60 kg/m², leads to an increase in cardiac output (50%), liver weight (100%), kidney weight (60%), both the kidney and liver absolute blood flows (50%), and in total adipose blood flow (160%).

Conclusion

The developed repository provides an updated description of a population with a BMI from 18.5 to 60 kg/m² using continuous physiological changes and their variability for each system parameter. It is a tool that can be implemented in PBPK models to simulate drug pharmacokinetics in obese individuals.

Recent advances in the translation of drug metabolism and pharmacokinetics science for drug discovery and development

Drug metabolism and pharmacokinetics (DMPK) is an important branch of pharmaceutical sciences. The nature of ADME (absorption, distribution, metabolism, excretion) and PK (pharmacokinetics) inquiries during drug discovery and development has evolved in recent years from being largely descriptive to seeking a more quantitative and mechanistic understanding of the fate of drug candidates in biological systems. Tremendous progress has been made in the past decade, not only in the characterization of physiochemical properties of drugs that influence their ADME, target organ exposure, and toxicity, but also in the identification of design principles that can minimize drug-drug interaction (DDI) potentials and reduce the attritions. The importance of membrane transporters in drug disposition, efficacy, and safety, as well as the interplay with metabolic processes, has been increasingly recognized. Dramatic increases in investments on new modalities beyond traditional small and large molecule drugs, such as peptides, oligonucleotides, and antibody-drug conjugates, necessitated further innovations in bioanalytical and experimental tools for the characterization of their ADME properties. In this review, we highlight some of the most notable advances in the last decade, and provide future perspectives on potential major breakthroughs and innovations in the translation of DMPK science in various stages of drug discovery and development.

Liquid Biopsy for Patient Characterization in Cardiovascular Disease: Verification against Markers of Cytochrome P450 and P-Glycoprotein Activities

Precision dosing strategies require accounting for between-patient variability in pharmacokinetics together with subsequent pharmacodynamic differences. Liquid biopsy is a valuable new approach to diagnose disease prior to the appearance of clinical signs and symptoms, potentially circumventing invasive tissue biopsies. However, the possibility of quantitative grading of biomarkers, as opposed to simply confirming their presence or absence, is relatively new. In this study, we aimed to verify expression measurements of cytochrome P450 (CYP) enzymes and the transporter P-glycoprotein (P-gp) in liquid biopsy against genotype and activity phenotype (assessed by the Geneva cocktail approach) in 30 acutely ill patients with cardiovascular disease in a hospital setting. After accounting for exosomal shedding, expression in liquid biopsy correlated with activity phenotype for CYP1A2, CYP2B6, CYP2C9, CYP3A, and P-gp (r = 0.44-0.70, P ≤ 0.05). Although genotype offered a degree of stratification, large variability (coefficient of variation (CV)) in activity (up to 157%) and expression in liquid biopsy (up to 117%) was observed within each genotype, indicating a mismatch between genotype and phenotype. Further, exosome screening revealed expression of 497 targets relevant to drug metabolism and disposition (159 enzymes and 336 transporters), as well as 20 molecular drug targets. Although there were no functional data available to correlate against these large-scale measurements, assessment of disease perturbation from healthy baseline was possible. Verification of liquid biopsy against activity phenotype is important to further individualize modeling approaches that aspire to achieve precision dosing from the start of drug treatment without the need for multiple rounds of dose optimization.

Drug disposition protein quantification in matched human jejunum and liver from donors with obesity

Mathematical models, such as physiologically‐based pharmacokinetic models, are used to predict, for example, drug disposition and toxicity. However, populations differ in the abundance of proteins involved in these processes. To improve the building and refinement of such models, they must take into account these interindividual variabilities. In this study, we used global proteomics to characterize the protein composition of jejunum and liver from 37 donors with obesity enrolled in the COCKTAIL study. Liver protein levels from the 37 donors were further compared with those from donors without obesity. We quantified thousands of proteins and could present the expression of several drug‐metabolizing enzymes, for the first time, in jejunum, many of which belong to the cytochrome P450 (CYP) (e.g., CYP2U1) and the amine oxidase (flavin‐containing) (e.g., monoamine oxidase A (MAOA)) families. Although we show that many metabolizing enzymes had greater expression in liver, others had higher expression in jejunum (such as, MAOA and CES2), indicating the role of the small intestine in extrahepatic drug metabolism. We further show that proteins involved in drug disposition are not correlated in the two donor‐matched tissues. These proteins also do not correlate with physiological factors such as body mass index, age, and inflammation status in either tissue. Furthermore, the majority of these proteins are not differently expressed in donors with or without obesity. Nonetheless, interindividual differences were considerable, with implications for personalized prediction models and systems pharmacology.

Conditions for maintenance of hepatocyte differentiation and function in 3D cultures

Spheroid cultures of primary human hepatocytes (PHH) are used in studies of hepatic drug metabolism and toxicity. The cultures are maintained under different conditions, with possible confounding results. We performed an in-depth analysis of the influence of various culture conditions to find the optimal conditions for the maintenance of an in vivo like phenotype. The formation, protein expression, and function of PHH spheroids were followed for three weeks in a high-throughput 384-well format. Medium composition affected spheroid histology, global proteome profile, drug metabolism and drug-induced toxicity. No epithelial-mesenchymal transition was observed. Media with fasting glucose and insulin levels gave spheroids with phenotypes closest to normal PHH. The most expensive medium resulted in PHH features most divergent from that of native PHH. Our results provide a protocol for culture of healthy PHH with maintained function - a prerequisite for studies of hepatocyte homeostasis and more reproducible hepatocyte research.

•

3D spheroid cultures were established in 384-well format

•

Eight different media variants were used to optimize the 3D cultures

•

Optimized William's medium was as good as expensive commercial medium

•

The 3D cultures were used to study drug metabolism and toxicity

Non-uniformity of Changes in Drug-Metabolizing Enzymes and Transporters in Liver Cirrhosis: Implications for Drug Dosage Adjustment

Liver cirrhosis is a chronic disease that affects the liver structure, protein expression, and overall metabolic function. Abundance data for drug-metabolizing enzymes and transporters (DMET) across all stages of disease severity are scarce. Levels of these proteins are crucial for the accurate prediction of drug clearance in hepatically impaired patients using physiologically based pharmacokinetic (PBPK) models, which can be used to guide the selection of more precise dosing. This study aimed to experimentally quantify these proteins in human liver samples and assess how they can impact the predictive performance of the PBPK models. We determined the absolute abundance of 51 DMET proteins in human liver microsomes across the three degrees of cirrhosis severity (n = 32; 6 mild, 13 moderate, and 13 severe), compared to histologically normal controls (n = 14), using QconCAT-based targeted proteomics. The results revealed a significant but non-uniform reduction in the abundance of enzymes and transporters, from control, by 30–50% in mild, 40–70% in moderate, and 50–90% in severe cirrhosis groups. Cancer and/or non-alcoholic fatty liver disease-related cirrhosis showed larger deterioration in levels of CYP3A4, 2C8, 2E1, 1A6, UGT2B4/7, CES1, FMO3/5, EPHX1, MGST1/3, BSEP, and OATP2B1 than the cholestasis set. Drug-specific pathways together with non-uniform changes of abundance across the enzymes and transporters under various degrees of cirrhosis necessitate the use of PBPK models. As case examples, such models for repaglinide, dabigatran, and zidovudine were successful in recovering disease-related alterations in drug exposure. In conclusion, the current study provides the biological rationale behind the absence of a single dose adjustment formula for all drugs in cirrhosis and demonstrates the utility of proteomics-informed PBPK modeling for drug-specific dose adjustment in liver cirrhosis.

Short- and long-term effects of body weight loss following calorie restriction and gastric bypass on CYP3A-activity - a non-randomized three-armed controlled trial

It remains uncertain whether pharmacokinetic changes following Roux-en-Y gastric bypass (RYGB) can be attributed to surgery-induced gastrointestinal alterations per se and/or the subsequent weight loss. The aim was to compare short- and long-term effects of RYGB and calorie restriction on CYP3A-activity, and cross-sectionally compare CYP3A-activity with normal weight to overweight controls using midazolam as probe drug. This three-armed controlled trial included patients with severe obesity preparing for RYGB (n = 41) or diet-induced (n = 41) weight-loss, and controls (n = 18). Both weight-loss groups underwent a 3-week low-energy-diet (<1200 kcal/day) followed by a 6-week very-low-energy-diet or RYGB (both <800 kcal/day). Patients were followed for 2 years, with four pharmacokinetic investigations using semisimultaneous oral and intravenous dosing to determine changes in midazolam absolute bioavailability and clearance, within and between groups. The RYGB and diet groups showed similar weight-loss at week 9 (13 ± 2.4% vs. 11 ± 3.6%), but differed substantially after 2 years (-30 ± 7.0% vs. -3.1 ± 6.3%). At baseline, mean absolute bioavailability and clearance of midazolam were similar in the RYGB and diet groups, but higher compared with controls. On average, absolute bioavailability was unaltered at week 9, but decreased by 40 ± 7.5% in the RYGB group and 32 ± 6.1% in the diet group at year 2 compared with baseline, with no between-group difference. No difference in clearance was observed over time, nor between groups. In conclusion, neither RYGB per se nor weight loss impacted absolute bioavailability or clearance of midazolam short term. Long term, absolute bioavailability was similarly decreased in both groups despite different weight loss, suggesting that the recovered CYP3A-activity is not only dependent on weight-loss through RYGB.

A Tribute to Professor Per Artursson - Scientist, Explorer, Mentor, Innovator, and Giant in Pharmaceutical Research

This issue of the Journal of Pharmaceutical Sciences is dedicated to Professor Per Artursson and the groundbreaking contributions he has made and continues to make in the Pharmaceutical Sciences. Per is one of the most cited researchers in his field, with more than 30,000 citations and an h-index of 95 as of September 2020. Importantly, these citations are distributed over the numerous fields he has explored, clearly showing the high impact the research has had on the discipline. We provide a short portrait of Per, with emphasis on his personality, driving forces and the inspirational sources that shaped his career as a world-leading scientist in the field. He is a curious scientist who deftly moves between disciplines and has continued to innovate, expand boundaries, and profoundly impact the pharmaceutical sciences throughout his career. He has developed new tools and provided insights that have significantly contributed to today's molecular and mechanistic approaches to research in the fields of intestinal absorption, cellular disposition, and exposure-efficacy relationships of pharmaceutical drugs. We want to celebrate these important contributions in this special issue of the Journal of Pharmaceutical Sciences in Per's honor.