Renal clearance in drug discovery and development: molecular descriptors, drug transporters and disease state

A strategy for evaluating the impact of processing of Chinese meteria medica on meridian tropism: the influence of salt-water processing of phellodendri chinensis cortex on renal transport proteins

Introduction

This study elucidated the potential mechanisms by which Phellodendri Chinensis Cortex with salt-water processing (SPC) enhances renal targeting efficacy, through investigating the effects of Phellodendri Chinensis Cortex (PC) on renal uptake and efflux transport capabilities before and after salt-water processing.

Methods

This study employed molecular docking, UPLC-TDQ-MS/MS, BCA, Western Blotting, and RT-PCR to assess the effects of raw Phellodendri Chinensis Cortex (RPC), SPC, berberine (BBR), and berberrubine (BBRR) on the transport capacity and expression of renal transport proteins OAT1, OAT3, OCT2, MATE1, MATE2K, P-gp, and MRP2 in HEK-293 cells.

Results

Analyses demonstrated that BBR and BBRR exhibited a strong affinity for OCT2, P-gp, MRP2. Compared to RPC, SPC can increase the uptake capacity and expression of OCT2, while it can decrease efflux capacity and expression of P-gp and MRP2. Simultaneously, BBRR showed similar effects on OCT2, P-gp, and MRP2, compared to BBR. Therefore, the enhanced renal targeting effect of SPC can be attributed to the differential impact of the partial conversion of BBR to BBRR on the transport capacity of the renal transporters OCT2, P-gp, and MRP2.

Conclusion

This study investigated the interactions between renal transporter proteins and drugs, with the objective of elucidating the mechanism by which SPC enhances renal targeting efficacy. The findings of this study offer new insights and methodologies for exploring the effects of Processing of Chinese Materia Medica (PCMM) on the meridian tropism of other traditional Chinese medicines (TCMs).

Organic cation transporters 2: Structure, regulation, functions, and clinical implications

The SLC22A2 gene encodes organic cation transporter 2 (OCT2), which is predominantly expressed in renal proximal tubule cells. OCT2 is critical for the active renal excretion of various cationic drugs and endogenous metabolites. OCT2 expression varies across species, with higher levels in mice and monkeys compared with humans and rats. The human OCT2 protein consists of 555 amino acids and contains 12 transmembrane domains. OCT2 functions as a uniporter, facilitating the bidirectional transport of organic cations into renal tubular cells, driven by the inside-negative membrane potential. Its expression is regulated by sex hormones, contributing to potential sex differences in Oct2 activity in rodents. OCT2 has been linked to tissue toxicity, such as cisplatin-induced nephrotoxicity. Factors such as genetic variants, age, disease states, and the coadministration of drugs, including tyrosine kinase inhibitors, contribute to interindividual variability in OCT2 activity. This, in turn, impacts the systemic exposure and elimination of drugs and endogenous substances. Regulatory agencies recommend evaluating the potential of a drug to inhibit OCT2 through in vitro and clinical drug-drug interaction (DDI) studies, often using metformin as a probe substrate. Emerging tools like transporter biomarkers and physiologically based pharmacokinetic modeling hold promise in predicting OCT2-mediated DDIs. While several OCT2 biomarkers, such as N1-methylnicotinamide, have been proposed, their reliability in predicting renal DDIs remains uncertain and requires further study. Ultimately, a better understanding of the factors influencing OCT2 activity is essential for achieving precision medicine and minimizing renal and systemic toxicity. SIGNIFICANCE STATEMENT: Organic cation transporter 2 (OCT2) is essential for the active tubular secretion of xenobiotics and endogenous cationic substances in the kidneys. This article offers a comprehensive overview of the tissue distribution, interspecies differences, and factors affecting its activity-critical for evaluating tissue toxicity and systemic exposure to cationic substances. Using OCT2 biomarkers and integrating OCT2 activity and expression data into physiologically based pharmacokinetic models are valuable tools for predicting OCT2 function and its clinical implications.

Protein-Based Degraders: From Chemical Biology Tools to Neo-Therapeutics

The nascent field of targeted protein degradation (TPD) could revolutionize biomedicine due to the ability of degrader molecules to selectively modulate disease-relevant proteins. A key limitation to the broad application of TPD is its dependence on small-molecule ligands to target proteins of interest. This leaves unstructured proteins or those lacking defined cavities for small-molecule binding out of the scope of many TPD technologies. The use of proteins, peptides, and nucleic acids (otherwise known as "biologics") as the protein-targeting moieties in degraders addresses this limitation. In the following sections, we provide a comprehensive and critical review of studies that have used proteins and peptides to mediate the degradation and hence the functional control of otherwise challenging disease-relevant protein targets. We describe existing platforms for protein/peptide-based ligand identification and the drug delivery systems that might be exploited for the delivery of biologic-based degraders. Throughout the Review, we underscore the successes, challenges, and opportunities of using protein-based degraders as chemical biology tools to spur discoveries, elucidate mechanisms, and act as a new therapeutic modality.

Is N1-Methylnicotinamide a Good Organic Cation Transporter 2 (OCT2) Biomarker?

Background/Objectives: The impact of potential precipitant drugs on plasma or urinary exposure of endogenous biomarkers is emerging as an alternative approach to evaluating drug-drug interaction (DDI) liability. N1-Methylnicotinamide (NMN) has been proposed as a potential biomarker for renal organic cation transporter 2 (OCT2). NMN is synthesized in the liver from nicotinamide by nicotinamide N-methyltransferase (NNMT) and is subsequently metabolized by aldehyde oxidase (AO). Multiple clinical studies have shown a reduction in NMN plasma concentration following the administration of OCT inhibitors such as cimetidine, trimethoprim, and pyrimethamine, which contrasts with their inhibition of NMN renal clearance by OCT2. We hypothesized that OCT1-mediated NMN release from hepatocytes is inhibited by the administration of OCT inhibitors. Methods: Re-analysis of the reported NMN pharmacokinetics with and without OCT inhibitor exposure was performed. We assessed the effect of cimetidine on NMN uptake in OCT1-HEK293 cells and evaluated the potential confounding effects of cimetidine on enzymes involved in NMN formation and metabolism. Results: A re-analysis of previous NMN pharmacokinetic DDI data suggests that NMN plasma systemic exposure decreased by 17-41% during the first 4 h following different OCT inhibitor administration except dolutegravir. Our findings indicate that NMN uptake was significantly higher (by 2.5-fold) in OCT1-HEK293 cells compared to mock cells, suggesting that NMN is a substrate of OCT1. Additionally, our results revealed that cimetidine does not inhibit NNMT and AO activity. Conclusions: Our findings emphasize the limitations of using NMN as an OCT2 biomarker and reveal potential mechanisms behind the reduction in NMN plasma levels associated with OCT inhibitors. Instead, our data suggest that NMN could be tested further as a potential biomarker for OCT1 activity.

Optimized chelator and nanoparticle strategies for high-activity 103Pd-loaded biodegradable brachytherapy seeds

BACKGROUND

Brachytherapy (BT) is routinely used in the treatment of various cancers. Current BT relies on the placement of large sources of radioactivity at the tumor site, requiring applicators that may cause local traumas and lesions. Further, they suffer from inflexibility in where they can be placed and some sources reside permanently in the body, causing potential long-term discomfort. These issues can be circumvented through injectable sources, prepared as biodegradable materials containing radionuclides that form solid seeds after administration. The level of radioactivity contained in such seeds must be sufficient to achieve substantial local irradiation. In this report, we investigate two different strategies for biodegradable BT seeds.

RESULTS

The first strategy entails injectable seeds based on 103Pd-labeled palladium-gold alloy nanoparticles ([103Pd]PdAuNPs). These were prepared by combining [103Pd]PdH2Cl4 and AuHCl4, followed by lipophilic surface coating and dispersed in lactose octaisobutyrate and ethanol (LOIB:EtOH), in overall radiochemical yield (RCY) of 83%. With the second strategy, [103Pd]Pd-SSIB was prepared by conjugating the [16]aneS4 chelator with lipophilic sucrose septaisobutyrate (SSIB) followed by complexation with [103Pd]PdH2Cl4 (RCY = 99%) and mixed with LOIB:EtOH. [103Pd]Pd-SSIB was likewise formulated as injectable liquid forming seeds by mixing with LOIB. Both formulations reached activities of 1.0-1.5 GBq/mL and negligible release of radioactivity after injection of 100 µL (100-150 MBq) into aqueous buffer or mouse serum of less than 1% over one month.

CONCLUSION

Both strategies for forming injectable BT seeds containing high 103Pd activity resulted in high radiolabeling yields, high activity per seed, and high activity retention. We consider both strategies suitable for BT, with the preferable strategy using a [16]aneS4 chelator due to its higher biodegradability.

Synergizing quantum techniques with machine learning for advancing drug discovery challenge

The Quantum Computing for Drug Discovery Challenge, held at the 42nd International Conference on Computer-Aided Design (ICCAD) in 2023, was a multi-month, research-intensive competition. Over 70 teams from more than 65 organizations from 12 different countries registered, focusing on the use of quantum computing for drug discovery. The challenge centered on designing algorithms to accurately estimate the ground state energy of molecules, specifically OH+, using quantum computing techniques. Participants utilized the IBM Qiskit platform within the constraints of the Noisy Intermediate Scale Quantum (NISQ) era, characterized by noise and limited quantum computing resources. The contest emphasized the importance of accurate estimation, efficient use of quantum resources, and the integration of machine learning techniques. This competition highlighted the potential of hybrid classical-quantum frameworks and machine learning in advancing quantum computing for practical applications, particularly in drug discovery.

Efficient proximal tubule-on-chip model from hiPSC-derived kidney organoids for functional analysis of renal transporters

Renal transporters play critical roles in predicting potential drug-drug interactions. However, current in vitro models often fail to adequately express these transporters, particularly solute carrier proteins, including organic anion transporters (OAT1/3), and organic cation transporter 2 (OCT2). Here, we developed a hiPSC-derived kidney organoids-based proximal tubule-on-chip (OPTC) model that emulates in vivo renal physiology to assess transporter function. Compared to chips based on immortalized cells, OPTC derived from the two most commonly used differentiation protocols exhibited significant improvement in expression level and polarity of OAT1/3 and OCT2. Hence, the OPTC demonstrates enhanced functionality in efflux and uptake assessments, and nephrotoxicity. Furthermore, these functionalities are diminished upon adding inhibitors during substrate-inhibitor interactions, which were closer to in vivo observations. Overall, these results support that OPTC can reliably assess the role of renal transporters in drug transport and nephrotoxicity, paving the way for personalized models to assess renal transport and disease modeling.

A multitier virtual screening study of phytoconstituents as Myeloid Cell Leukemias 1 inhibitors

Myeloid Cell Leukemia 1 (MCL1) is an anti-apoptotic protein that plays a critical role in regulating cell survival, particularly in cancer cells. It is a member of the BCL-2 family of proteins, which control the intrinsic pathway of apoptosis. MCL1 has emerged as a promising target for cancer therapy because it is overexpressed in a wide range of cancers, including breast, lung, prostate, and hematologic malignancies. Due to its remarkable role in cancer progression, it has been reflected as a promising drug target for cancer therapy. A few MCL1 inhibitors have been identified previously, but further research is needed to develop novel, effective and safe MCL1 inhibitors that can overcome resistance mechanisms and minimize toxicity in normal cells. In this study, we aim to search for compounds that target the critical binding site of MCL1 from phytoconstituent library from the IMPPAT database. To accomplish this, a multitier virtual screening approach involving molecular docking and molecular dynamics simulations (MDS) were used to evaluate their suitability for the receptor. Notably, certain screened phytoconstituents have appreciable docking scores and stable interactions toward the binding pocket of MCL1. The screened compounds underwent ADMET and bioactivity analysis to establish their anticancer properties. One phytoconstituent, Isopongaflavone, was identified that exhibiting higher docking and drug-likeness than the already reported MCL1 inhibitor, Tapotoclax. Isopongaflavone and and Tapotoclax, along with MCL1, were subjected to 100 nanoseconds (ns) MDS study to verify their stability inside the binding site of MCL1. The MDS findings demonstrated a strong binding affinity between Isopongaflavone and the MCL1 binding pocket, resulting in reduced conformational fluctuations. This investigation proposes Isopongaflavone as a promising candidate for the development of innovative anticancer therapeutics, pending the necessary validation procedures. Also, the findings provide valuable information for designing MCL1 inhibitors based on the protein's structure.Communicated by Ramaswamy H. Sarma.

Identification of Helicobacter pylori-carcinogenic TNF-alpha-inducing protein inhibitors via daidzein derivatives through computational approaches

Gastric cancer is considered a class 1 carcinogen that is closely linked to infection with Helicobacter pylori (H. pylori), which affects over 1 million people each year. However, the major challenge to fight against H. pylori and its associated gastric cancer due to drug resistance. This research gap had led our research team to investigate a potential drug candidate targeting the Helicobacter pylori-carcinogenic TNF-alpha-inducing protein. In this study, a total of 45 daidzein derivatives were investigated and the best 10 molecules were comprehensively investigated using in silico approaches for drug development, namely pass prediction, quantum calculations, molecular docking, molecular dynamics simulations, Lipinski rule evaluation, and prediction of pharmacokinetics. The molecular docking study was performed to evaluate the binding affinity between the target protein and the ligands. In addition, the stability of ligand-protein complexes was investigated by molecular dynamics simulations. Various parameters were analysed, including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA) and dynamic cross-correlation matrix (DCCM). The results has confirmed that the ligand-protein complex CID: 129661094 (07) and 129664277 (08) formed stable interactions with the target protein. It was also found that CID: 129661094 (07) has greater hydrogen bond occupancy and stability, while the ligand-protein complex CID 129664277 (08) has greater conformational flexibility. Principal component analysis revealed that the ligand-protein complex CID: 129661094 (07) is more compact and stable. Hydrogen bond analysis revealed favourable interactions with the reported amino acid residues. Overall, this study suggests that daidzein derivatives in particular show promise as potential inhibitors of H. pylori.

Acetylcholinesterase Inhibition in Rats and Humans Following Acute Fenitrothion Exposure Predicted by Physiologically Based Kinetic Modeling-Facilitated Quantitative In Vitro to In Vivo Extrapolation

Worldwide use of organophosphate pesticides as agricultural chemicals aims to maintain a stable food supply, while their toxicity remains a major public health concern. A common mechanism of acute neurotoxicity following organophosphate pesticide exposure is the inhibition of acetylcholinesterase (AChE). To support Next Generation Risk Assessment for public health upon acute neurotoxicity induced by organophosphate pesticides, physiologically based kinetic (PBK) modeling-facilitated quantitative in vitro to in vivo extrapolation (QIVIVE) approach was employed in this study, with fenitrothion (FNT) as an exemplary organophosphate pesticide. Rat and human PBK models were parametrized with data derived from in silico predictions and in vitro incubations. Then, PBK model-based QIVIVE was performed to convert species-specific concentration-dependent AChE inhibition obtained from in vitro blood assays to corresponding in vivo dose-response curves, from which points of departure (PODs) were derived. The obtained values for rats and humans were comparable with reported no-observed-adverse-effect levels (NOAELs). Humans were found to be more susceptible than rats toward erythrocyte AChE inhibition induced by acute FNT exposure due to interspecies differences in toxicokinetics and toxicodynamics. The described approach adequately predicts toxicokinetics and acute toxicity of FNT, providing a proof-of-principle for applying this approach in a 3R-based chemical risk assessment paradigm.

Renal Organic Anion Transporters 1 and 3 In Vitro: Gone but Not Forgotten

Organic anion transporters 1 and 3 (OAT1 and OAT3) play a crucial role in kidney function by regulating the secretion of multiple renally cleared small molecules and toxic metabolic by-products. Assessing the activity of these transporters is essential for drug development purposes as they can significantly impact drug disposition and safety. OAT1 and OAT3 are amongst the most abundant drug transporters expressed in human renal proximal tubules. However, their expression is lost when cells are isolated and cultured in vitro, which is a persistent issue across all human and animal renal proximal tubule cell models, including primary cells and cell lines. Although it is well known that the overall expression of drug transporters is affected in vitro, the underlying reasons for the loss of OAT1 and OAT3 are still not fully understood. Nonetheless, research into the regulatory mechanisms of these transporters has provided insights into the molecular pathways underlying their expression and activity. In this review, we explore the regulatory mechanisms that govern the expression and activity of OAT1 and OAT3 and investigate the physiological changes that proximal tubule cells undergo and that potentially result in the loss of these transporters. A better understanding of the regulation of these transporters could aid in the development of strategies, such as introducing microfluidic conditions or epigenetic modification inhibitors, to improve their expression and activity in vitro and to create more physiologically relevant models. Consequently, this will enable more accurate assessment for drug development and safety applications.

Predicting the Drug Clearance Pathway with Structural Descriptors

BACKGROUND AND OBJECTIVE

The clearance, by renal elimination or hepatic metabolism, is one of the most important pharmacokinetic parameters of a drug. It allows the half-life, bioavailability, and drug-drug interactions to be predicted, and it can also affect the dose regimen of a drug. Predicting the clearance pathways of new chemical candidates during drug development is vital in order to minimize the risks of possible side effects and drug interactions. Many in vivo methods have been established to predict drug clearance in humans, and these mainly rely on data from in vivo studies in preclinical species-mainly rats, dogs, and monkeys. They are also time consuming and expensive. The aim of this study was to find the relationship between structural parameters of drugs and their clearance pathways.

METHODS

The clearance pathway of each drug was obtained from the literature. Various structural descriptors [Abraham solvation parameters, topological polar surface area, numbers of hydrogen-bond donors and acceptors, number of rotatable bonds, molecular weight, logarithm of the partition coefficient (logP), and logarithm of the distribution coefficient at pH 7.4 (logD_7.4)] were applied to develop a mechanistic model for predicting clearance pathways.

RESULTS

The results of this study indicate that compounds with logD_7.4 > 1 or with zero or one hydrogen-bond donor undergo hepatic metabolism, whereas the clearance pathway for chemicals with logD_7.4 < - 2 is renal elimination. Furthermore, models established using logistic regression based on five structural parameters for compounds with - 2 < logD_7.4 < 1 could be used in a clearance pathway prediction tool. The overall prediction accuracies of the first and second models were 84.8% and 84.4%, respectively.

CONCLUSION

The developed model can be used to find the clearance pathways of new drug candidates with acceptable accuracy. The main descriptors that are used to evaluate this parameter are the hydrophobicity and the number of hydrogen-bonding functional groups of the compound.

Engineering non-antibody human proteins as efficient scaffolds for selective, receptor-targeted drug delivery

Self-assembling non-immunoglobulin scaffold proteins are a promising class of nanoscale carriers for drug delivery and interesting alternatives to antibody-based carriers that are not sufficiently efficient in systemic administration. To exploit their potentialities in clinics, protein scaffolds need to be further tailored to confer appropriate targeting and to overcome their potential immunogenicity, short half-life in plasma and proteolytic degradation. We have here engineered three human scaffold proteins as drug carrier nanoparticles to target the cytokine receptor CXCR4, a tumoral cell surface marker of high clinical relevance. The capability of these scaffolds for the selective delivery of Monomethyl auristatin E has been comparatively evaluated in a disseminated mouse model of human, CXCR4⁺ acute myeloid leukemia. Monomethyl auristatin E is an ultra-potent anti-mitotic drug used against a range of hematological neoplasias, which because of its high toxicity is not currently administered as a free drug but as payload in antibody-drug conjugates. The protein nanoconjugates generated here offer a collective strength of simple manufacturing process, high proteolytic and structural stability and multivalent ligand receptor interactions that result in a highly efficient and selective delivery of the payload drug and in a potent anticancer effect. The approach shown here stresses this class of human scaffold proteins as promising alternatives to antibodies for targeted drug delivery in the rapidly evolving drug development landscape.

Oxadiazepinone HBV capsid assembly modulators

The HBV core protein serves multiple essential functions in the viral life cycle that enable chronic HBV infection to persist, and as such, represents a promising drug target. Modulation of the HBV capsid assembly has shown efficacy in early clinical trials through use of small molecule capsid assembly modulators (CAMs). Herein is described the evolution and SAR of a novel pyrazolo piperidine lead series into advanced oxadiazepinone HBV CAMs.

Nano versus Molecular: Optical Imaging Approaches to Detect and Monitor Tumor Hypoxia

Hypoxia is a ubiquitous feature of solid tumors, which plays a key role in tumor angiogenesis and resistance development. Conventional hypoxia detection methods lack continuous functional detection and are generally less suitable for dynamic hypoxia measurement. Optical sensors hereby provide a unique opportunity to noninvasively image hypoxia with high spatiotemporal resolution and enable real-time detection. Therefore, these approaches can provide a valuable tool for personalized treatment planning against this hallmark of aggressive cancers. Many small optical molecular probes can enable analyte triggered response and their photophysical properties can also be fine-tuned through structural modification. On the other hand, optical nanoprobes can acquire unique intrinsic optical properties through nanoconfinement as well as enable simultaneous multimodal imaging and drug delivery. Furthermore, nanoprobes provide biological advantages such as improving bioavailability and systemic delivery of the sensor to enhance bioavailability. This review provides a comprehensive overview of the physical, chemical, and biological analytes for cancer hypoxia detection and focuses on discussing the latest nano- and molecular developments in various optical imaging approaches (fluorescence, phosphorescence, and photoacoustic) in vivo. Finally, this review concludes with a perspective toward the potentials of these optical imaging approaches in hypoxia detection and the challenges with molecular and nanotechnology design strategies.

Design and engineering of tumor-targeted, dual-acting cytotoxic nanoparticles

The possibility to conjugate tumor-targeted cytotoxic nanoparticles and conventional antitumoral drugs in single pharmacological entities would open a wide spectrum of opportunities in nanomedical oncology. This principle has been explored here by using CXCR4-targeted self-assembling protein nanoparticles based on two potent microbial toxins, the exotoxin A from Pseudomonas aeruginosa and the diphtheria toxin from Corynebacterium diphtheriae, to which oligo-floxuridine and monomethyl auristatin E respectively have been chemically coupled. The resulting multifunctional hybrid nanoconjugates, with a hydrodynamic size of around 50 nm, are stable and internalize target cells with a biological impact. Although the chemical conjugation minimizes the cytotoxic activity of the protein partner in the complexes, the concept of drug combination proposed here is fully feasible and highly promising when considering multiple drug treatments aimed to higher effectiveness or when facing the therapy of cancers with acquired resistance to classical drugs.

Is the human model RPTEC/TERT1 a relevant model for assessing renal drug efflux?

Active tubular secretion plays a major role in renal excretion of drugs thanks to the presence of many membrane transporters such as ABC transporters. These proteins facilitate drug transfer into the urine and could be a source of pharmacokinetic variabilities. Up to now, several human in vitro models of proximal tubule have been proposed but few of them have been characterized for predicting drugs renal efflux. The aim of this study was to determine whether the human model RPTEC/TERT1 meets all the criteria expected of a good model to assess renal drug transport. First, in vitro barrier properties were investigated. Then, the expression of several ABC transporters was assessed by immunofluorescence and relative quantification by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) in comparison to the MDCK model. Finally, bidirectional transport studies were performed to evaluate the functionality of transporters and the abilities of model to discriminate several drugs. The RPTEC/TERT1 model formed a tight structure (192 Ω.cm² ) that was confirmed by paracellular permeability assays. Proteomic analysis and immunofluorescence staining showed the expression of several ABC transporters. Then, only the functionality of P-gp was confirmed by the active efflux of apixaban in this study. In addition, the RPTEC/TERT1 model presents the key criteria of a renal barrier and expresses several ABC transporters. Nevertheless, the BCRP and MRP's functionality was not confirmed and further investigations are required to valid this model as in vitro model for assessing renal drug efflux.

Dissecting molecular network structures using a network subgraph approach

Biological processes are based on molecular networks, which exhibit biological functions through interactions of genetic elements or proteins. This study presents a graph-based method to characterize molecular networks by decomposing the networks into directed multigraphs: network subgraphs. Spectral graph theory, reciprocity and complexity measures were used to quantify the network subgraphs. Graph energy, reciprocity and cyclomatic complexity can optimally specify network subgraphs with some degree of degeneracy. Seventy-one molecular networks were analyzed from three network types: cancer networks, signal transduction networks, and cellular processes. Molecular networks are built from a finite number of subgraph patterns and subgraphs with large graph energies are not present, which implies a graph energy cutoff. In addition, certain subgraph patterns are absent from the three network types. Thus, the Shannon entropy of the subgraph frequency distribution is not maximal. Furthermore, frequently-observed subgraphs are irreducible graphs. These novel findings warrant further investigation and may lead to important applications. Finally, we observed that cancer-related cellular processes are enriched with subgraph-associated driver genes. Our study provides a systematic approach for dissecting biological networks and supports the conclusion that there are organizational principles underlying molecular networks.

In Vivo-to-In Vitro Extrapolation of Transporter-Mediated Renal Clearance: Relative Expression Factor Versus Relative Activity Factor Approach

About 30% of approved drugs are cleared predominantly by renal clearance (CLr). Of these, many are secreted by transporters. For these drugs, in vitro-to-in vivo extrapolation of transporter-mediated renal secretory clearance (CLsec,plasma) is important to prospectively predict their renal clearance and to assess the impact of drug-drug interactions and pharmacogenetics on their pharmacokinetics. Here we compared the ability of the relative expression factor (REF) and the relative activity factor (RAF) approaches to quantitatively predict the in vivo CLsec,plasma of 26 organic anion transporter (OAT) substrates assuming that OAT-mediated uptake is the rate-determining step in the CLsec,plasma of the drugs. The REF approach requires protein quantification of each transporter in the tissue (e.g., kidney) and transporter-expressing cells, whereas the RAF approach requires the use of a transporter-selective probe substrate (both in vitro and in vivo) for each transporter of interest. For the REF approach, 50% and 69% of the CLsec,plasma predictions were within 2- and 3-fold of the observed values, respectively; the corresponding values for the RAF approach were 65% and 81%. We found no significant difference between the two approaches in their predictive capability (as measured by accuracy and bias) of the CLsec,plasma or CLr of OAT drugs. We recommend that the REF and RAF approaches can be used interchangeably to predict OAT-mediated CLsec,plasma Further research is warranted to evaluate the ability of the REF or RAF approach to predict CLsec,plasma of drugs when uptake is not the rate-determining step. SIGNIFICANCE STATEMENT: This is the first direct comparison of the relative expression factor (REF) and relative activity factor (RAF) approaches to predict transporter-mediated renal clearance (CLr). The RAF, but not REF, approach requires transporter-selective probes and that the basolateral uptake is the rate-determining step in the CLr of drugs. Given that there is no difference in predictive capability of the REF and RAF approach for organic anion transporter-mediated CLr, the REF approach should be explored further to assess its ability to predict CLr when basolateral uptake is not the sole rate-determining step.

In Silico Prediction of Human Renal Clearance of Compounds Using Quantitative Structure-Pharmacokinetic Relationship Models

Renal clearance (CLr) plays an essential role in the elimination of drugs. In this study, 636 compounds were obtained from various sources to develop in silico models for the prediction of CLr. Stepwise multiple linear regression and random forest regression methods were employed to build global models and local models according to ionization state or net elimination pathways. The local models toward compounds undergoing different net elimination pathways showed good predictive power: the geometric mean fold error was close to 2, indicating the clearance of most compounds could be predicted within a 2-fold error range. Six classification methods were used to construct classification models. However, the performance of these classification models was less than satisfactory, and the mean accuracy of the top five models in test sets was 0.65. Moreover, qualitative analysis of physicochemical profiles between compounds undergoing different net elimination pathways revealed that compounds with higher lipophilicity tended to be reabsorbed more easily and showed lower CLr, while compounds with higher values of polar descriptors tended to secrete more easily and showed higher CLr.

Development of an in silico prediction system of human renal excretion and clearance from chemical structure information incorporating fraction unbound in plasma as a descriptor

Prediction of pharmacokinetic profiles of new chemical entities is essential in drug development to minimize the risks of potential withdrawals. The excretion of unchanged compounds by the kidney constitutes a major route in drug elimination and plays an important role in pharmacokinetics. Herein, we created in silico prediction models of the fraction of drug excreted unchanged in the urine (f_e) and renal clearance (CL_r), with datasets of 411 and 401 compounds using freely available software; notably, all models require chemical structure information alone. The binary classification model for f_e demonstrated a balanced accuracy of 0.74. The two-step prediction system for CL_r was generated using a combination of the classification model to predict excretion-type compounds and regression models to predict the CL_r value for each excretion type. The accuracies of the regression models increased upon adding a descriptor, which was the observed and predicted fraction unbound in plasma (f_u,p); 78.6% of the samples in the higher range of renal clearance fell within 2-fold error with predicted f_u,p value. Our prediction system for renal excretion is freely available to the public and can be used as a practical tool for prioritization and optimization of compound synthesis in the early stage of drug discovery.

Improvement of Aglycone π-Stacking Yields Nanomolar to Sub-nanomolar FimH Antagonists

Antimicrobial resistance has become a serious concern for the treatment of urinary tract infections. In this context, an anti-adhesive approach targeting FimH, a bacterial lectin enabling the attachment of E. coli to host cells, has attracted considerable interest. FimH can adopt a low/medium-affinity state in the absence and a high-affinity state in the presence of shear forces. Until recently, mostly the high-affinity state has been investigated, despite the fact that a therapeutic antagonist should bind predominantly to the low-affinity state. In this communication, we demonstrate that fluorination of biphenyl α-d-mannosides leads to compounds with perfect π-π stacking interactions with the tyrosine gate of FimH, yielding low nanomolar to sub-nanomolar K_D values for the low- and high-affinity states, respectively. The face-to-face alignment of the perfluorinated biphenyl group of FimH ligands and Tyr48 was confirmed by crystal structures as well as ¹ H,¹⁵ N-HSQC NMR analysis. Finally, fluorination improves pharmacokinetic parameters predictive for oral availability.

Human pharmacokinetics of ginkgo terpene lactones and impact of carboxylation in blood on their platelet-activating factor antagonistic activity

Terpene lactones are a class of bioactive constituents of standardized preparations of Ginkgo biloba leaf extract, extensively used as add-on therapies in patients with ischemic cardiovascular and cerebrovascular diseases. This investigation evaluated human pharmacokinetics of ginkgo terpene lactones and impact of their carboxylation in blood. Human subjects received oral YinXing-TongZhi tablet or intravenous ShuXueNing, two standardized ginkgo preparations. Their plasma protein-binding and platelet-activating factor antagonistic activity were assessed in vitro. Their carboxylation was assessed in phosphate-buffered saline (pH 7.4) and in human plasma. After dosing YinXing-TongZhi tablet, ginkgolides A and B and bilobalide exhibited significantly higher systemic exposure levels than ginkgolides C and J; after dosing ShuXueNing, ginkgolides A, B, C, and J exhibited high exposure levels. The compounds' unbound fractions in plasma were 45-92%. Apparent oral bioavailability of ginkgolides A and B was mostly >100%, while that of ginkgolides C and J was 6-15%. Bilobalide's bioavailability was probably high but lower than that of ginkgolides A/B. Terminal half-lives of ginkgolides A, B, and C (4-7 h) after dosing ShuXueNing were shorter than their respective values (6-13 h) after dosing YinXing-TongZhi tablet. Half-life of bilobalide after dosing the tablet was around 5 h. Terpene lactones were roughly evenly distributed in various body fluids and tissues; glomerular-filtration-based renal excretion was the predominant elimination route for the ginkgolides and a major route for bilobalide. Terpene lactones circulated as trilactones and monocarboxylates. Carboxylation reduced platelet-activating factor antagonistic activity of ginkgolides A, B, and C. Ginkgolide J, bilobalide, and ginkgo flavonoids exhibited no such bioactivity. Collectively, differences in terpene lactones' exposure between the two preparations and influence of their carboxylation in blood should be considered in investigating the relative contributions of terpene lactones to ginkgo preparations' therapeutic effects. The results here will inform rational clinical use of ginkgo preparations.

Emerging Kidney Models to Investigate Metabolism, Transport, and Toxicity of Drugs and Xenobiotics

The kidney is a major clearance organ of the body and is responsible for the elimination of many xenobiotics and prescription drugs. With its multitude of uptake and efflux transporters and metabolizing enzymes, the proximal tubule cell (PTC) in the nephron plays a key role in the disposition of xenobiotics and is also a primary site for toxicity. In this minireview, we first provide an overview of the major transporters and metabolizing enzymes in the PTCs responsible for biotransformation and disposition of drugs. Next, we discuss different cell sources that have been used to model PTCs in vitro, their pros and cons, and their characterization. As current technology is inadequate to evaluate reliably drug disposition and toxicity in the kidney, we then discuss recent advancements in kidney microphysiological systems (MPS) and the need to develop robust in vitro platforms that could be routinely used by pharmaceutical companies to screen compounds. Finally, we discuss the new and exciting field of stem cell-derived kidney models as potential cell sources for future kidney MPS. Given the push from both regulatory agencies and pharmaceutical companies to use more predictive "human-like" in vitro systems in the early stages of drug development to reduce attrition, these emerging models have the potential to be a game changer and may revolutionize how renal disposition and kidney toxicity in drug discovery are evaluated in the future.

Simultaneous Assessment of Transporter-Mediated Drug-Drug Interactions Using a Probe Drug Cocktail in Cynomolgus Monkey

We aim to establish an in vivo preclinical model to enable simultaneous assessment of inhibition potential of an investigational drug on clinically relevant drug transporters, organic anion-transporting polypeptide (OATP)1B, breast cancer resistance protein (BCRP), P-glycoprotein (P-gp), and organic anion transporter (OAT)3. Pharmacokinetics of substrate cocktail consisting of pitavastatin (OATP1B substrate), rosuvastatin (OATP1B/BCRP/OAT3), sulfasalazine (BCRP), and talinolol (P-gp) were obtained in cynomolgus monkey-alone or in combination with transporter inhibitors. Single-dose rifampicin (30 mg/kg) significantly (P < 0.01) increased the plasma exposure of all four drugs, with a marked effect on pitavastatin and rosuvastatin [area under the plasma concentration-time curve (AUC) ratio ∼21-39]. Elacridar, BCRP/P-gp inhibitor, increased the AUC of sulfasalazine, talinolol, as well as rosuvastatin and pitavastatin. An OAT1/3 inhibitor (probenecid) significantly (P < 0.05) impacted the renal clearance of rosuvastatin (∼8-fold). In vitro, rifampicin (10 µM) inhibited uptake of pitavastatin, rosuvastatin, and sulfasalazine by monkey and human primary hepatocytes. Transport studies using membrane vesicles suggested that all probe substrates, except talinolol, are transported by cynoBCRP, whereas talinolol is a cynoP-gp substrate. Elacridar and rifampicin inhibited both cynoBCRP and cynoP-gp in vitro, indicating potential for in vivo intestinal efflux inhibition. In conclusion, a probe substrate cocktail was validated to simultaneously evaluate perpetrator impact on multiple clinically relevant transporters using the cynomolgus monkey. The results support the use of the cynomolgus monkey as a model that could enable drug-drug interaction risk assessment, before advancing a new molecular entity into clinical development, as well as providing mechanistic insights on transporter-mediated interactions.

Navigating Transporter Sciences in Pharmacokinetics Characterization Using the Extended Clearance Classification System

Membrane transporters play an important role in the absorption, distribution, clearance, and elimination of drugs. Supported by the pharmacokinetics data in human, several transporters including organic anion transporting polypeptide (OATP)1B1, OATP1B3, organic anion transporter (OAT)1, OAT3, organic cation transporter (OCT)2, multidrug and toxin extrusion (MATE) proteins, P-glycoprotein and breast cancer resistance protein are suggested to be of clinical relevance. An early understanding of the transporter role in drug disposition and clearance allows reliable prediction/evaluation of pharmacokinetics and changes due to drug-drug interactions (DDIs) or genetic polymorphisms. We recently proposed an extended clearance classification system (ECCS) based on simple drug properties (i.e., ionization, permeability, and molecular weight) to predict the predominant clearance mechanism. According to this framework, systemic clearance of class 1B and 3B drugs is likely determined by the OATP-mediated hepatic uptake. Class 3A and 4 drugs, and certain class 3B drugs, are predominantly cleared by renal, wherein, OAT1, OAT3, OCT2, and MATE proteins could contribute to their active renal secretion. Intestinal efflux and uptake transporters largely influence the oral pharmacokinetics of class 3A, 3B, and 4 drugs. We discuss the paradigm of applying the ECCS framework in mapping the role of clinically relevant drug transporters in early discovery and development; thereby implementing the right strategy to allow optimization of drug exposure and evaluation of clinical risk due to DDIs and pharmacogenomics.

Renal Transporter-Mediated Drug-Drug Interactions: Are They Clinically Relevant?

The kidney, through the distinct processes of passive glomerular filtration and active tubular secretion, plays an important role in the elimination of numerous endobiotics (eg, hormones, metabolites), toxins, nutrients, and drugs. Renal transport pathways mediating active tubular secretion and reabsorption in the proximal tubule are complex, involving apical and basolateral transporters acting in concert. Detailed studies of the molecular mechanisms of net active tubular secretion have established the involvement of multiple transporters with overlapping substrate specificity mediating competing secretion and reabsorption pathways. Although drug interactions arising from inhibition of renal transporters are rare relative to other mechanisms, they can involve commonly administered drugs (eg, cimetidine, metformin), may be underappreciated due to muted effects on plasma pharmacokinetics relative to tissue levels, can affect narrow-therapeutic-index medications (eg, antiarrhythmic, oncology medications), and may disproportionately affect sensitive populations where polypharmacy is common (eg, the elderly, diabetics). In particular, there is the potential for larger-magnitude interactions in subjects with reduced glomerular filtration rates due to the increased relative contribution of tubular secretion. The assessment of additional endpoints in drug-drug interaction studies including pharmacodynamics, positron emission tomography imaging, and metabolomics promises to expand our understanding of the clinical relevance of renal drug interactions.

Evaluation and Quantitative Prediction of Renal Transporter-Mediated Drug-Drug Interactions

With numerous drugs cleared renally, inhibition of uptake transporters localized on the basolateral membrane of renal proximal tubule cells, eg, organic anion transporters (OATs) and organic cation transporters (OCTs), may lead to clinically meaningful drug-drug interactions (DDIs). Additionally, clinical evidence for the possible involvement of efflux transporters, such as P-glycoprotein (P-gp) and multidrug and toxin extrusion protein 1/2-K (MATE1/2-K), in the renal DDIs is emerging. Herein, we review recent progress regarding mechanistic understanding of transporter-mediated renal DDIs as well as the quantitative predictability of renal DDIs using static and physiologically based pharmacokinetic (PBPK) models. Generally, clinical DDI data suggest that the magnitude of plasma exposure changes attributable to renal DDIs is less than 2-fold, unlike the DDIs associated with inhibition of cytochrome P-450s and/or hepatic uptake transporters. It is concluded that although there is a need for risk assessment early in drug development, current available data imply that safety concerns related to the renal DDIs are generally low. Nevertheless, consideration must be given to the therapeutic index of the victim drug and potential risk in a specific patient population (eg, renal impairment). Finally, in vitro transporter data and clinical pharmacokinetic parameters obtained from the first-in-human studies have proven useful in support of quantitative prediction of DDIs associated with inhibition of renal secretory transporters, OATs or OCTs.

Renal Drug Transporters and Drug Interactions

Transporters in proximal renal tubules contribute to the disposition of numerous drugs. Furthermore, the molecular mechanisms of tubular secretion have been progressively elucidated during the past decades. Organic anions tend to be secreted by the transport proteins OAT1, OAT3 and OATP4C1 on the basolateral side of tubular cells, and multidrug resistance protein (MRP) 2, MRP4, OATP1A2 and breast cancer resistance protein (BCRP) on the apical side. Organic cations are secreted by organic cation transporter (OCT) 2 on the basolateral side, and multidrug and toxic compound extrusion (MATE) proteins MATE1, MATE2/2-K, P-glycoprotein, organic cation and carnitine transporter (OCTN) 1 and OCTN2 on the apical side. Significant drug-drug interactions (DDIs) may affect any of these transporters, altering the clearance and, consequently, the efficacy and/or toxicity of substrate drugs. Interactions at the level of basolateral transporters typically decrease the clearance of the victim drug, causing higher systemic exposure. Interactions at the apical level can also lower drug clearance, but may be associated with higher renal toxicity, due to intracellular accumulation. Whereas the importance of glomerular filtration in drug disposition is largely appreciated among clinicians, DDIs involving renal transporters are less well recognized. This review summarizes current knowledge on the roles, quantitative importance and clinical relevance of these transporters in drug therapy. It proposes an approach based on substrate-inhibitor associations for predicting potential tubular-based DDIs and preventing their adverse consequences. We provide a comprehensive list of known drug interactions with renally-expressed transporters. While many of these interactions have limited clinical consequences, some involving high-risk drugs (e.g. methotrexate) definitely deserve the attention of prescribers.

Molecular properties associated with transporter-mediated drug disposition

Membrane transporters play a key role in the absorption, distribution, clearance, elimination, and transport of drugs. Understanding the drug properties and structure activity relationships (SAR) for affinity to membrane transporters is critical to optimize clearance and pharmacokinetics during drug design. To facilitate the early identification of clearance mechanism, a framework named the extended clearance classification system (ECCS) was recently introduced. Using in vitro and physicochemical properties that are readily available in early drug discovery, ECCS has been successfully applied to identify major clearance mechanism and to implicate the role of membrane transporters in determining pharmacokinetics. While the crystal structures for most of the drug transporters are currently not available, ligand-based modeling approaches that use information obtained from the structure and molecular properties of the ligands have been applied to associate the drug-related properties and transporter-mediated disposition. The approach allows prospective prediction of transporter both substrate and/or inhibitor affinity and build quantitative structure-activity relationship (QSAR) to enable early optimization of pharmacokinetics, tissue distribution and drug-drug interaction risk. Drug design applications can be further improved through uncovering transporter protein crystal structure and generation of quality data to refine and develop viable predictive models.

Assembly of Macrocycle Dye Derivatives into Particles for Fluorescence and Photoacoustic Applications

Optical imaging is a rapidly progressing medical technique that can benefit from the development of new and improved optical imaging agents suitable for use in vivo. However, the molecular rules detailing what optical agents can be processed and encapsulated into in vivo presentable forms are not known. We here present the screening of series of highly hydrophobic porphyrin, phthalocyanine, and naphthalocyanine dye macrocycles through a self-assembling Flash NanoPrecipitation process to form a series of water dispersible dye nanoparticles (NPs). Ten out of 19 tested dyes could be formed into poly(ethylene glycol) coated nanoparticles 60-150 nm in size, and these results shed insight on dye structural criteria that are required to permit dye assembly into NPs. Dye NPs display a diverse range of absorbance profiles with absorbance maxima within the NIR region, and have absorbance that can be tuned by varying dye choice or by doping bulking materials in the NP core. Particle properties such as dye core load and the compositions of co-core dopants were varied, and subsequent effects on photoacoustic and fluorescence signal intensities were measured. These results provide guidelines for designing NPs optimized for photoacoustic imaging and NPs optimized for fluorescence imaging. This work provides important details for dye NP engineering, and expands the optical imaging tools available for use.

Quantitative Prediction of Human Renal Clearance and Drug-Drug Interactions of Organic Anion Transporter Substrates Using In Vitro Transport Data: A Relative Activity Factor Approach

Organic anion transporters (OATs) are important in the renal secretion, and thus, the clearance, of many drugs; and their functional change can result in pharmacokinetic variability. In this study, we applied transport rates measured in vitro using OAT-transfected human embryonic kidney cells to predict human renal secretory and total renal clearance of 31 diverse drugs. Selective substrates to OAT1 (tenofovir), OAT2 (acyclovir and ganciclovir), and OAT3 (benzylpenicillin, oseltamivir acid) were used to obtain relative activity factors (RAFs) for these individual transporters by relating in vitro transport clearance (after physiologic scaling) to in vivo secretory clearance. Using the estimated RAFs (0.64, 7.3, and 4.1, respectively, for OAT1, OAT2, and OAT3, respectively) and the in vitro active clearances, renal secretory clearance and total renal clearance were predicted with average fold errors (AFEs) of 1.89 and 1.40, respectively. The results show that OAT3-mediated transport play a predominant role in renal secretion for 22 of the 31 drugs evaluated. This mechanistic static approach was further applied to quantitatively predict renal drug-drug interactions (AFE ∼1.6) of the substrate drugs with probenecid, a clinical probe OAT inhibitor. In conclusion, the proposed in vitro-in vivo extrapolation approach is the first comprehensive attempt toward mechanistic modeling of renal secretory clearance based on routinely employed in vitro cell models.

Abundance of Drug Transporters in the Human Kidney Cortex as Quantified by Quantitative Targeted Proteomics

Protein expression of renal uptake and efflux transporters was quantified by quantitative targeted proteomics using the surrogate peptide approach. Renal uptake transporters assessed in this study included organic anion transporters (OAT1-OAT4), organic cation transporter 2 (OCT2), organic/carnitine cation transporters (OCTN1 and OCTN2), and sodium-glucose transporter 2 (SGLT2); efflux transporters included P-glycoprotein, breast cancer resistance protein, multidrug resistance proteins (MRP2 and MRP4), and multidrug and toxin extrusion proteins (MATE1 and MATE2-K). Total membrane was isolated from the cortex of human kidneys (N = 41). The isolated membranes were digested by trypsin and the digest was subjected to liquid chromatography-tandem mass spectrometry analysis. The mean expression of surrogate peptides was as follows (given with the standard deviation, in picomoles per milligram of total membrane protein): OAT1 (5.3 ± 1.9), OAT2 (0.9 ± 0.3), OAT3 (3.5 ± 1.6), OAT4 (0.5 ± 0.2), OCT2 (7.4 ± 2.8), OCTN1 (1.3 ± 0.6), OCTN2 (0.6 ± 0.2), P-glycoprotein (2.1 ± 0.8), MRP2 (1.4 ± 0.6), MRP4 (0.9 ± 0.6), MATE1 (5.1 ± 2.3), and SGLT2 (3.7 ± 1.8). Breast cancer resistance protein (BCRP) and MATE2-K proteins were detectable but were below the lower limit of quantification. Interestingly, the protein expression of OAT1 and OAT3 was significantly correlated (r > 0.8). A significant correlation was also observed between expression of multiple other drug transporters, such as OATs/OCT2 or OCTN1/OCTN2, and SGLT2/OCTNs, OCT, OATs, and MRP2. These renal transporter data should be useful in deriving in vitro to in vivo scaling factors to accurately predict renal clearance and kidney epithelial cell exposure to drugs or their metabolites.

Prodruggability of carbohydrates — oral FimH antagonists

The bacterial lectin FimH is a promising therapeutic target for the nonantibiotic prevention and treatment of urinary tract infections. In this communication, an ester prodrug approach is described to achieve oral bioavailability for FimH antagonists. By introducing short-chain acyl promoieties at the C-6 position of a biphenyl α-d-mannopyranoside, prodrugs with an excellent absorption potential were obtained. The human carboxylesterase 2 was identified as a main enzyme mediating rapid bioconversion to the active principle. Despite their propensity to hydrolysis within the enterocytes during absorption, these ester prodrugs present a considerable progress in the development of orally available FimH antagonists.

Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine

Personalized medicine strives to deliver the 'right drug at the right dose' by considering inter-person variability, one of the causes for therapeutic failure in specialized populations of patients. Physiologically-based pharmacokinetic (PBPK) modeling is a key tool in the advancement of personalized medicine to evaluate complex clinical scenarios, making use of physiological information as well as physicochemical data to simulate various physiological states to predict the distribution of pharmacokinetic responses. The increased dependency on PBPK models to address regulatory questions is aligned with the ability of PBPK models to minimize ethical and technical difficulties associated with pharmacokinetic and toxicology experiments for special patient populations. Subpopulation modeling can be achieved through an iterative and integrative approach using an adopt, adapt, develop, assess, amend, and deliver methodology. PBPK modeling has two valuable applications in personalized medicine: (1) determining the importance of certain subpopulations within a distribution of pharmacokinetic responses for a given drug formulation and (2) establishing the formulation design space needed to attain a targeted drug plasma concentration profile. This review article focuses on model development for physiological differences associated with sex (male vs. female), age (pediatric vs. young adults vs. elderly), disease state (healthy vs. unhealthy), and temporal variation (influence of biological rhythms), connecting them to drug product formulation development within the quality by design framework. Although PBPK modeling has come a long way, there is still a lengthy road before it can be fully accepted by pharmacologists, clinicians, and the broader industry.

Projecting ADME Behavior and Drug-Drug Interactions in Early Discovery and Development: Application of the Extended Clearance Classification System

PURPOSE

To assess the utility of Extended Clearance Classification System (ECCS) in understanding absorption, distribution, metabolism, and elimination (ADME) attributes and enabling victim drug-drug interaction (DDI) predictions.

METHODS

A database of 368 drugs with relevant ADME parameters, main metabolizing enzymes, uptake transporters, efflux transporters, and highest change in exposure (%AUC) in presence of inhibitors was developed using published literature. Drugs were characterized according to ECCS using ionization, molecular weight and estimated permeability.

RESULTS

Analyses suggested that ECCS class 1A drugs are well absorbed and systemic clearance is determined by metabolism mediated by CYP2C, esterases, and UGTs. For class 1B drugs, oral absorption is high and the predominant clearance mechanism is hepatic uptake mediated by OATP transporters. High permeability neutral/basic drugs (class 2) showed high oral absorption, with metabolism mediated generally by CYP3A, CYP2D6 and UGTs as the predominant clearance mechanism. Class 3A/4 drugs showed moderate absorption with dominant renal clearance involving OAT/OCT2 transporters. Class 3B drugs showed low to moderate absorption with hepatic uptake (OATPs) and/or renal clearance as primary clearance mechanisms. The highest DDI risk is typically seen with class 2/1B/3B compounds manifested by inhibition of either CYP metabolism or active hepatic uptake. Class 2 showed a wider range in AUC change likely due to a variety of enzymes involved. DDI risk for class 3A/4 is small and associated with inhibition of renal transporters.

CONCLUSIONS

ECCS provides a framework to project ADME profiles and further enables prediction of victim DDI liabilities in drug discovery and development.

Cancer Theranostic Nanoparticles Self-Assembled from Amphiphilic Small Molecules with Equilibrium Shift-Induced Renal Clearance

Nano drug delivery systems have emerged as promising candidates for cancer therapy, whereas their uncertainly complete elimination from the body within specific timescales restricts their clinical translation. Compared with hepatic clearance of nanoparticles, renal excretion of small molecules is preferred to minimize the agent-induced toxicity. Herein, we construct in vivo renal-clearable nanoparticles, which are self-assembled from amphiphilic small molecules holding the capabilities of magnetic resonance imaging (MRI) and chemotherapy. The assembled nanoparticles can accumulate in tumor tissues for their nano-characteristics, while the small molecules dismantled from the nanoparticles can be efficiently cleared by kidneys. The renal-clearable nanoparticles exhibit excellent tumor-inhibition performance as well as low side effects and negligible chronic toxicity. These results demonstrate a potential strategy for small molecular nano drug delivery systems with obvious anticancer effect and low-toxic metabolism pathway for clinical applications.

New IVIVE method for the prediction of total human clearance and relative elimination pathway contributions from in vitro hepatocyte and microsome data

Total human clearance is a key determinant for the pharmacokinetic behavior of drug candidates. Our group recently introduced the Extended Clearance Model (ECM) as an accurate in vitro-in vivo extrapolation (IVIVE) method for the prediction of hepatic clearance. Yet, knowledge about relative elimination pathway contributions is needed in order to predict the total human clearance of drug candidates. In the present work, a training set of 18 drug compounds was used to describe the affiliations between in vitro sinusoidal uptake clearance and the fractional contributions of hepatic (metabolic and biliary) or renal clearance to overall in vivo elimination. By means of these quantitative relationships and using a validation set of 10 diverse drug molecules covering different (sub)classes of the Extended Clearance Concept Classification System (ECCCS), the relative contributions of elimination pathways were calculated and demonstrated to well correlate with human reference data. Likewise, ECM- and pathway-based predictions of total clearances from both data sets demonstrated a strong correlation with the observed clinical values with 26 out of 28 compounds within a three-fold deviation. Hence, total human clearance and relative contributions of elimination pathways were successfully predicted by the presented method using solely hepatocyte and microsome in vitro data.

Pre-Plated Cell Lines for ADMETox Applications in the Pharmaceutical Industry

Membrane transporters significantly modulate membrane permeability of endobiotics and xenobiotics, such as bile acids and drugs, respectively. Various in vitro methods have been established for both ATP-binding cassette (ABC) transporters to examine cellular efflux and uptake, and for solute carriers (SLC) to examine cellular uptake of substrates. Cell-based systems are the models of choice to test drug-transporter interactions as well as drug-drug interactions for research and regulatory purposes, albeit, for low passive permeability substrates of ABC transporters, vesicular uptake assays are also recommended. Commercially available pre-plated cells (e.g., immortalized or transfected) offer a useful alternative to in-house cell culture. Three main methods are known to manufacture pre-plated cultures: regular culture medium with vacuum seal, cryopreserved delivery, and the solid shipping media technology. The regular culture medium and the solid shipping media technologies provide ready-to-use models for end users. Models expressing a broad selection of transporters are available in pre-plated formats for absorption, distribution, metabolism, excretion, and toxicity (ADMETox) studies. Conversely, the application and utility of pre-plated cultures coupled with personal experiences have not been extensively covered in published research papers or reviews, despite availability and significant use of pre-plated products in the pharmaceutical industry. In this overview, we will briefly describe: 1) in vitro tools commonly used for ADMETox testing; 2) methods employed in manufacturing, shipment and preparation of pre-plated cell lines; 3) cell-membrane barrier models currently available in pre-plated format to reproduce passage restriction of physiological barriers to certain compounds; and 4) recommended pre-plated cell lines overexpressing uptake transporters for ADMETox applications.

In vitro methods in drug transporter interaction assessment

Drug transporter proteins recruit to pharmacological barrier tissues and profoundly affect the ADME properties of a large number of drugs. In vitro assays optimized for drug transporters have grown into routine tools in the determination of molecular level interactions as well as prediction of barrier penetration and system level pharmacokinetics. Regulatory position mandates increasing interest in the application of these assays during drug development.

FimH antagonists: bioisosteres to improve the in vitro and in vivo PK/PD profile

Urinary tract infections (UTIs), predominantly caused by uropathogenic Escherichia coli (UPEC), belong to the most prevalent infectious diseases worldwide. The attachment of UPEC to host cells is mediated by FimH, a mannose-binding adhesin at the tip of bacterial type 1 pili. To date, UTIs are mainly treated with antibiotics, leading to the ubiquitous problem of increasing resistance against most of the currently available antimicrobials. Therefore, new treatment strategies are urgently needed. Here, we describe the development of an orally available FimH antagonist. Starting from the carboxylate substituted biphenyl α-d-mannoside 9, affinity and the relevant pharmacokinetic parameters (solubility, permeability, renal excretion) were substantially improved by a bioisosteric approach. With 3'-chloro-4'-(α-d-mannopyranosyloxy)biphenyl-4-carbonitrile (10j) a FimH antagonist with an optimal in vitro PK/PD profile was identified. Orally applied, 10j was effective in a mouse model of UTI by reducing the bacterial load in the bladder by about 1000-fold.

Renal Safety Pharmacology in Drug Discovery and Development

The kidney is a complex excretory organ playing a crucial role in various physiological processes such as fluid and electrolyte balance, control of blood pressure, removal of waste products, and drug disposition. Drug-induced kidney injury (DIKI) remains a significant cause of candidate drug attrition during drug development. However, the incidence of renal toxicities in preclinical studies is low, and the mechanisms by which drugs induce kidney injury are still poorly understood. Although some in vitro investigational tools have been developed, the in vivo assessment of renal function remains the most widely used methodology to identify DIKI. Stand-alone safety pharmacology studies usually include assessment of glomerular and hemodynamic function, coupled with urine and plasma analyses. However, as renal function is not part of the ICH S7A core battery, such studies are not routinely conducted by pharmaceutical companies. The most common approach consists in integrating renal/urinary measurements in repeat-dose toxicity studies. In addition to the standard analyses and histopathological examination of kidneys, novel promising urinary biomarkers have emerged over the last decade, offering greater sensitivity and specificity than traditional renal parameters. Seven of these biomarkers have been qualified by regulatory agencies for use in rat toxicity studies.

Quantitative structure-pharmacokinetic relationships for the prediction of renal clearance in humans

Renal clearance (CLR), a major route of elimination for many drugs and drug metabolites, represents the net result of glomerular filtration, active secretion and reabsorption, and passive reabsorption. The aim of this study was to develop quantitative structure-pharmacokinetic relationships (QSPKR) to predict CLR of drugs or drug-like compounds in humans. Human CLR data for 382 compounds were obtained from the literature. Step-wise multiple linear regression was used to construct QSPKR models for training sets and their predictive performance was evaluated using internal validation (leave-one-out method). All qualified models were validated externally using test sets. QSPKR models were also constructed for compounds in accordance with their 1) net elimination pathways (net secretion, extensive net secretion, net reabsorption, and extensive net reabsorption), 2) net elimination clearances (net secretion clearance, CLSEC; or net reabsorption clearance, CLREAB), 3) ion status, and 4) substrate/inhibitor specificity for renal transporters. We were able to predict 1) CLREAB (Q(2) = 0.77) of all compounds undergoing net reabsorption; 2) CLREAB (Q(2) = 0.81) of all compounds undergoing extensive net reabsorption; and 3) CLR for substrates and/or inhibitors of OAT1/3 (Q(2) = 0.81), OCT2 (Q(2) = 0.85), MRP2/4 (Q(2) = 0.78), P-gp (Q(2) = 0.71), and MATE1/2K (Q(2) = 0.81). Moreover, compounds undergoing net reabsorption/extensive net reabsorption predominantly belonged to Biopharmaceutics Drug Disposition Classification System classes 1 and 2. In conclusion, constructed parsimonious QSPKR models can be used to predict CLR of compounds that 1) undergo net reabsorption/extensive net reabsorption and 2) are substrates and/or inhibitors of human renal transporters.

In vivo architectonic stability of fully de novo designed protein-only nanoparticles

The fully de novo design of protein building blocks for self-assembling as functional nanoparticles is a challenging task in emerging nanomedicines, which urgently demand novel, versatile, and biologically safe vehicles for imaging, drug delivery, and gene therapy. While the use of viruses and virus-like particles is limited by severe constraints, the generation of protein-only nanocarriers is progressively reachable by the engineering of protein-protein interactions, resulting in self-assembling functional building blocks. In particular, end-terminal cationic peptides drive the organization of structurally diverse protein species as regular nanosized oligomers, offering promise in the rational engineering of protein self-assembling. However, the in vivo stability of these constructs, being a critical issue for their medical applicability, needs to be assessed. We have explored here if the cross-molecular contacts between protein monomers, generated by end-terminal cationic peptides and oligohistidine tags, are stable enough for the resulting nanoparticles to overcome biological barriers in assembled form. The analyses of renal clearance and biodistribution of several tagged modular proteins reveal long-term architectonic stability, allowing systemic circulation and tissue targeting in form of nanoparticulate material. This observation fully supports the value of the engineered of protein building blocks addressed to the biofabrication of smart, robust, and multifunctional nanoparticles with medical applicability that mimic structure and functional capabilities of viral capsids.