Utilising Endogenous Biomarkers in Drug Development to Streamline the Assessment of Drug-Drug Interactions Mediated by Renal Transporters: A Pharmaceutical Industry Perspective.

The renal secretion of many drugs is facilitated by membrane transporters, including organic cation transporter 2, multidrug and toxin extrusion protein 1/2-K and organic anion transporters 1 and 3. Inhibition of these transporters can reduce renal excretion of drugs and thereby pose a safety risk. Assessing the risk of inhibition of these membrane transporters by investigational drugs remains a key focus in the evaluation of drug-drug interactions (DDIs). Current methods to predict DDI risk are based on generating in vitro data followed by a clinical assessment using a recommended exogenous probe substrate for the individual drug transporter. More recently, monitoring plasma-based and urine-based endogenous biomarkers to predict transporter-mediated DDIs in early phase I studies represents a promising approach to facilitate, improve and potentially avoid conventional clinical DDI studies. This perspective reviews the evidence for use of these endogenous biomarkers in the assessment of renal transporter-mediated DDI, evaluates how endogenous biomarkers may help to expand the DDI assessment toolkit and offers some potential knowledge gaps. A conceptual framework for assessment that may complement the current paradigm of predicting the potential for renal transporter-mediated DDIs is outlined.

Application of the Finite Absorption Time (F.A.T.) Concept in the Assessment of Bioequivalence.

PURPOSE: Το formulate a methodology for the assessment of bioequivalence using metrics, which are based on the physiologically sound F.A.T. METHODS: The equations of the physiologically based finite time pharmacokinetic models for the one-and two-compartment model with one and two input stages of absorption were solved to derive metrics for the extent and rate of absorption. Simulated data were used to study the proper way for the estimation of metrics. A bioequivalence study was analyzed using these metrics. RESULTS: The rate of drug absorption was found to be equal to the slope of the amount absorbed versus time curve. The amount of drug absorbed at the end of the absorption process, corresponding to the blood concentration at F.A.T. is an indicator of the extent of absorption. The plot of the ratio test/reference of the simulated data for the amount absorbed as a function of time becomes constant beyond the end of drug absorption from the formulation exhibiting the longer absorption. The assessment of the bioequivalence study was based on the slope of the amount absorbed versus time curve for the rate of absorption, while the estimate for the constant ratio test/reference for the amount absorbed was used for the assessment of extent of absorption. CONCLUSIONS: The assessment of rate in bioequivalence studies can be based on the estimation of slope of the percent absorbed versus time curve while the constant ratio test/reference for the amount of drug absorbed is an indicator of the extent of absorption.

Application of Generative Artificial Intelligence in Predicting Membrane Partitioning of Drugs: Combining Denoising Diffusion Probabilistic Models and MD Simulations Reduces the Computational Cost to One-Third.

The optimal interaction of drugs with plasma membranes and membranes of subcellular organelles is a prerequisite for desirable pharmacology. Importantly, for drugs targeting the transmembrane lipid-facing sites of integral membrane proteins, the relative affinity of a drug to the bilayer lipids compared to the surrounding aqueous phase affects the partitioning, access, and binding of the drug to the target site. Molecular dynamics (MD) simulations, including enhanced sampling techniques such as steered MD, umbrella sampling (US), and metadynamics, offer valuable insights into the interactions of drugs with the membrane lipids and water in atomistic detail. However, these methods are computationally prohibitive for the high-throughput screening of drug candidates. This study shows that applying denoising diffusion probabilistic models (DDPMs), a generative AI method, to US simulation data reduces the computational cost significantly. Specifically, the models used only partial (one-third) data from the US simulations and reproduced the complete potential of mean force (PMF) profiles for three FDA-approved drugs (ß2-adrenergic agonists) and ∼20 biologically relevant chemicals with known experimentally characterized bilayer locations. Intriguingly, the model can predict the solvation-free energies for partitioning and crossing the bilayer, preferred bilayer locations (low-energy well), and orientations of the ligands with high accuracy. The results indicate that DDPMs can be used to characterize the complete membrane partitioning profile of drug molecules using fewer umbrella sampling simulations at select positions along the bilayer normal (z-axis), irrespective of their amphiphilic-lipophilic-cephalophilic characteristics.

Simulating Healthy Participant Pharmacokinetics for Renal and Hepatic Impairment Studies: Retrospective Assessment of the Approach.

The recruitment of a parallel, healthy participants (HPs) arm in renal and hepatic impairment (RI and HI) studies is a common strategy to assess differences in pharmacokinetics. Limitations in this approach include the underpowered estimate of exposure differences and the use of the drug in a population for which there is no benefit. Recently, a method was published by Purohit et. al. (2023) that leveraged prior population pharmacokinetic (PopPK) modeling-based simulation to infer the distribution of exposure ratios between the RI/HI arms and HPs. The approach was successful, but it was a single example with a robust model having several iterations of development and fitting to extensive HP data. To test in more studies and models at different stages of development, our catalogue of RI/HI studies was searched, and those with suitable properties and from programs with available models were analyzed with the simulation approach. There were 9 studies included in the analysis. Most studies were associated with models that would have been available at the time (ATT) of the study, and all had a current, final model. For 3 studies, the HP PK was not predicted well by the ATT (2) or final (1) models. In comparison to conventional analysis of variance (ANOVA), the simulation approach provided similar point estimates and confidence intervals of exposure ratios. This PopPK based approach can be considered as a method of choice in situations where the simulation of HP data would not be an extrapolation, and when no other complicating factors are present.

First-in-Human Predictions of Hepatic Clearance for Drugs With the Well-Stirred Model: Comparative Assessment Between Models of Fraction Unbound Based Either on the Free Drug Hypothesis, Albumin-Facilitated Hepatic Uptake or Dynamic Binding Kinetics.

The well-stirred model (WSM) is commonly used to predict the hepatic clearance in vivo (CLH) of drugs. The necessary intrinsic clearance of the unbound drug (CLint-in vitro-unbound) is generated in the in vitro assays in the presence of microsomes or hepatocytes but in the absence of plasma proteins. The value of CLint-in vitro-unbound can be extrapolated with the fraction unbound determined in vitro in plasma (fup) only if the fraction unbound in vivo in liver is the same. However, this approach resulted to a systematic underprediction bias of CLH. With the goal of reducing this bias, two new models of fraction unbound were published in this journal. These models estimate the binding kinetics of the rates of association and dissociation of the drug-protein complex and propose that more dissociation in the liver compared to plasma will increase the fraction unbound available for the metabolism. Consequently, these two models generated higher values of fraction unbound, implying a lower underprediction bias of CLH with the WSM. The first model was developed by Poulin et al. and is referring to the value of fup that is adjusted (fu-adjusted) to quantify the effect of a full dissociation of the drug-protein complex at the hepatocyte membrane in accordance with the theory of the albumin-facilitated hepatic uptake. A second model was developed by Yan et al. who presented a dynamic fraction unbound (fu-dynamic) measuring the real dissociation kinetics of the drug-protein complex with a new in vitro assay in the presence and absence of a recombinant liver enzyme in plasma. Therefore, the objective of this study was to make the first comparative assessment between these two models. The results indicate that, in general, the WSM combined with the values of fu-adjusted was the most accurate approach for predicting CLH. The WSM combined with the values of fu-dynamic has underperformed particularly with the acidic and neutral drugs binding to the albumin and presenting a low metabolic turnover in vitro. Therefore, the new in vitro assay for fu-dynamic gave an underprediction bias of CLH for these drug properties. However, the values of fu-adjusted are significantly higher than those values of fu-dynamic, and, this resulted to no underprediction bias, which is reinforcing the theory of the ALB-facilitated hepatic uptake. For the other neutral and acidic drugs, the models of fu-dynamic and fu-adjusted are in closer agreement. Finally, for the basic drugs, the models of fu-adjusted and fu-dynamic as well as a third model only considering a pH gradient effect on fup are almost accurately equivalent.

Survey of Pharmaceutical Industry's Best Practices around In Vitro Transporter Assessment and Implications for Drug Development: Considerations from the International Consortium for Innovation and Quality for Pharmaceutical Development Transporter Working Group.

The International Consortium for Innovation and Quality in Pharmaceutical Development Transporter Working Group had a rare opportunity to analyze a crosspharma collation of in vitro data and assay methods for the evaluation of drug transporter substrate and inhibitor potential. Experiments were generally performed in accordance with regulatory guidelines. Discrepancies, such as not considering the impact of preincubation for inhibition and free or measured in vitro drug concentrations, may be due to the retrospective nature of the dataset and analysis. Lipophilicity was a frequent indicator of crosstransport inhibition (P-gp, BCRP, OATP1B, and OCT1), with high molecular weight (MW ≥500 Da) also common for OATP1B and BCRP inhibitors. A high level of overlap in in vitro inhibition across transporters was identified for BCRP, OATP1B1, and MATE1, suggesting that prediction of DDIs for these transporters will be common. In contrast, inhibition of OAT1 did not coincide with inhibition of any other transporter. Neutrals, bases, and compounds with intermediate-high lipophilicity tended to be P-gp and/or BCRP substrates, whereas compounds with MW <500 Da tended to be OAT3 substrates. Interestingly, the majority of in vitro inhibitors were not reported to be followed up with a clinical study by the submitting company, whereas those compounds identified as substrates generally were. Approaches to metabolite testing were generally found to be similar to parent testing, with metabolites generally being equally or less potent than parent compounds. However, examples where metabolites inhibited transporters in vitro were identified, supporting the regulatory requirement for in vitro testing of metabolites to enable integrated clinical DDI risk assessment. SIGNIFICANCE STATEMENT: A diverse dataset showed that transporter inhibition often correlated with lipophilicity and molecular weight (>500 Da). Overlapping transporter inhibition was identified, particularly that inhibition of BCRP, OATP1B1, and MATE1 was frequent if the compound inhibited other transporters. In contrast, inhibition of OAT1 did not correlate with the other drug transporters tested.

Drug-induced impairment of mitochondrial fatty acid oxidation and steatosis: assessment of causal relationship with 45 pharmaceuticals.

Drug-induced liver injury (DILI) represents a major issue for pharmaceutical companies, being a potential cause of black-box warnings on marketed pharmaceuticals, or drug withdrawal from the market. Lipid accumulation in the liver also referred to as steatosis, may be secondary to impaired mitochondrial fatty acid oxidation (mtFAO). However, an overall causal relationship between drug-induced mtFAO inhibition and the occurrence of steatosis in patients has not yet been established with a high number of pharmaceuticals. Hence, 32 steatogenic and 13 nonsteatogenic drugs were tested for their ability to inhibit mtFAO in isolated mouse liver mitochondria. To this end, mitochondrial respiration was measured with palmitoyl-l-carnitine, palmitoyl-CoA + l-carnitine, or octanoyl- l-carnitine. This mtFAO tri-parametric assay was able to predict the occurrence of steatosis in patients with a sensitivity and positive predictive value above 88%. To get further information regarding the mechanism of drug-induced mtFAO impairment, mitochondrial respiration was also measured with malate/glutamate or succinate. Drugs such as diclofenac, methotrexate, and troglitazone could inhibit mtFAO secondary to an impairment of the mitochondrial respiratory chain, whereas dexamethasone, olanzapine, and zidovudine appeared to impair mtFAO directly. Mitochondrial swelling, transmembrane potential, and production of reactive oxygen species were also assessed for all compounds. Only the steatogenic drugs amiodarone, ketoconazole, lovastatin, and toremifene altered all these 3 mitochondrial parameters. In conclusion, our tri-parametric mtFAO assay could be useful in predicting the occurrence of steatosis in patients. The combination of this assay with other mitochondrial parameters could also help to better understand the mechanism of drug-induced mtFAO inhibition.

Potential impact of underlying diseases influencing ADME in nonclinical safety assessment.

Nonclinical studies involve in vitro, in silico, and in vivo experiments to assess the toxicokinetics, toxicology, and safety pharmacology of drugs according to regulatory requirements by a national or international authority. In this review, we summarize the potential effects of various underlying diseases governing the absorption, distribution, metabolism, and excretion (ADME) of drugs to consider the use of animal models of diseases in nonclinical trials. Obesity models showed alterations in hepatic metabolizing enzymes, transporters, and renal pathophysiology, which increase the risk of drug-induced toxicity. Diabetes models displayed changes in hepatic metabolizing enzymes, transporters, and glomerular filtration rates (GFR), leading to variability in drug responses and susceptibility to toxicity. Animal models of advanced age exhibited impairment of drug metabolism and kidney function, thereby reducing the drug-metabolizing capacity and clearance. Along with changes in hepatic metabolic enzymes, animal models of metabolic syndrome-related hypertension showed renal dysfunction, resulting in a reduced GFR and urinary excretion of drugs. Taken together, underlying diseases can induce dysfunction of organs involved in the ADME of drugs, ultimately affecting toxicity. Therefore, the use of animal models of representative underlying diseases in nonclinical toxicity studies can be considered to improve the predictability of drug side effects before clinical trials.

Towards Greener and More Cost-efficient Biosynthesis of Pharmaceuticals and Fragrance Molecules.

Enzymes are natural catalysts which are gaining momentum in chemical synthesis due to their exquisiteselectivity and their biodegradability. However, the cost-efficiency and the sustainability of the overall biocatalytic process must be enhanced to unlock completely the potential of enzymes for industrial applications. To reach this goal, enzyme immobilization and the integration into continuous flow reactors have been the cornerstone of our research. We showed key examples of the advantages of those tools for the biosynthesis of antivirals, anticancer drugs, and valuable fragrance molecules. By combining new strategies to immobilize biocatalysts, innovative bioengineering approaches, and process development, the performance of the reactions could be boosted up to 100-fold.

Encapsulation and assessment of therapeutic cargo in engineered exosomes: a systematic review.

Exosomes are nanoscale extracellular vesicles secreted by cells and enclosed by a lipid bilayer membrane containing various biologically active cargoes such as proteins, lipids, and nucleic acids. Engineered exosomes generated through genetic modification of parent cells show promise as drug delivery vehicles, and they have been demonstrated to have great therapeutic potential for treating cancer, cardiovascular, neurological, and immune diseases, but systematic knowledge is lacking regarding optimization of drug loading and assessment of delivery efficacy. This review summarizes current approaches for engineering exosomes and evaluating their drug delivery effects, and current techniques for assessing exosome drug loading and release kinetics, cell targeting, biodistribution, pharmacokinetics, and therapeutic outcomes are critically examined. Additionally, this review synthesizes the latest applications of exosome engineering and drug delivery in clinical translation. The knowledge compiled in this review provides a framework for the rational design and rigorous assessment of exosomes as therapeutics. Continued advancement of robust characterization methods and reporting standards will accelerate the development of exosome engineering technologies and pave the way for clinical studies.

Use of Traditional and Proteomic Methods in the Assessment of a Preclinical Model of Preeclampsia.

Recent studies have demonstrated downregulation of breast cancer resistance protein (BCRP/ABCG2) in placenta obtained from women with preeclampsia (PE). BCRP is highly expressed in placenta and plays an important role in preventing xenobiotics from entering the fetal compartment. Although PE is often therapeutically managed with drugs that are substrates of BCRP, there are limited studies on the impact of PE on fetal drug exposure. Due to ethical concerns, use of preclinical models is an important approach. Thus, by using proteomic and traditional methods, we characterized transporter changes in an immunologic rat model of PE to determine its utility and predictive value for future drug disposition studies. PE was induced by daily administration of low-dose endotoxin (0.01-0.04 mg/kg) to rats on gestational days (GD) 13-16, urine was collected, and rats were sacrificed on GD17 or GD18. PE rats shared similar phenotype to PE patients, including proteinuria, and increased levels of tumor necrosis factor α and interleukin 6. Transcript and protein levels of Bcrp were significantly downregulated in placenta of PE rats on GD18. multidrug resistance 1a, multidrug resistance 1b, and organic anion transporting polypeptide 2B1 mRNA were also decreased in PE. Proteomics revealed activation of various hallmarks of PE including immune activation, oxidative stress, endoplasmic reticulum stress and apoptosis. Overall, our results demonstrated that the immunologic PE rat model exhibits numerous similarities to human PE along with dysregulation of placental transporters. Therefore, this model may be useful in examining the impact of PE on the maternal and fetal disposition of BCRP substrates. SIGNIFICANCE STATEMENT: Fully characterizing preclinical models of disease is necessary to determine their validity to human conditions. Combining traditional and proteomic methods of model characterization, we identified numerous phenotypic similarities between our model of preeclampsia and human disease. The alignment with human pathophysiological changes allows for more confident use of this preclinical model.

Industry Perspective on Therapeutic Peptide Drug-Drug Interaction Assessments During Drug Development: A European Federation of Pharmaceutical Industries and Associations White Paper.

Drug-drug interaction (DDI) assessments are well defined in health authority guidelines for small molecule drugs, and US Food and Drug Administration (FDA) draft guidance is now available for therapeutic proteins. However, there are currently no regulatory guidelines outlining DDI assessments for therapeutic peptides, which poses significant uncertainty and challenges during drug development for this heterogenous class of molecules. A cross-industry peptide DDI working group consisting of experts from 10 leading companies was formed under the sponsorship of the European Federation of Pharmaceutical Industries and Associations. We aimed to capture the range of DDI studies undertaken for peptide drugs by (i) anonymously surveying relevant companies involved in peptide drug development to better understand DDI study type/timing currently performed and (ii) compiling a database containing in vitro / clinical DDI data from submission packages for recently approved peptide drugs. Our analyses highlight significant gaps and uncertainty in the field. For example, the reported timing of in vitro peptide DDI studies, if performed, vary substantially across responding companies from early research to phase III. Nearly all in vitro cytochrome P450 / transporter inhibition studies reported in the survey were negative. For the few positive hits reported, no clinical follow-up studies were performed, questioning the clinical relevance of these findings. Furthermore, available submission packages reveal DDI likelihood is low for peptides >2 kDa, making it reasonable to adopt a risk-based approach during drug development for larger peptides. By benchmarking the landscape of peptide DDI activities across the industry, we set the stage for future discussions with health authorities on harmonizing peptide DDI approaches.

Single-particle assessment of six different drug-loading strategies for incorporating doxorubicin into small extracellular vesicles.

Extracellular vesicles (EVs) have emerged as an attractive drug delivery system owing to their natural roles in intercellular communication. On account of the large intrinsic heterogeneity of EVs, it is highly desirable to evaluate not only the encapsulation efficiency but also the alteration of biological functionality after the drug-loading process at the single-particle level. However, the nanoscale size of EVs poses a great challenge. Taking advantage of nano-flow cytometry (nFCM) in the multiparameter analysis of single EVs as small as 40 nm, six commonly used drug-loading strategies (coincubation, electroporation, extrusion, freeze-thawing, sonication, and surfactant treatment) were exploited by employing doxorubicin (Dox) as the model drug. Encapsulation ratio, EV concentration, drug content, and membrane proteins of Dox-loaded EVs were measured at the single-particle level. Our data indicated that coincubation and electroporation outperformed other methods with an encapsulation ratio of approximately 45% and a higher Dox content in single EVs. Interestingly, the labeling ratios of membrane proteins indicated that varying degrees of damage to the surface proteins of EVs occurred upon extrusion, freeze-thawing, sonication, and surfactant treatment. Confocal fluorescence microscopy and flow cytometry analysis revealed that Dox-loaded EVs prepared by electroporation induced the strongest apoptosis followed by coincubation. These results correlated well with their cellular uptake rate and fundamentally with the Dox encapsulation efficiency of single EVs. nFCM provides a rapid and sensitive platform for single-particle assessment of drug-loading strategies for incorporating drugs into EVs.

Euryale ferox, a prominent superfood: Nutritional, pharmaceutical, and its economical importance.

Euryale ferox (also known as foxnut), belongs to the family Nymphaeaceae. It is mainly grown in India, China, Japan, and Korea. It is a highly nutritious food, abundant in nutritional and bioactive compounds such as carbohydrates, protein, fiber, vitamins, minerals, and polyphenols. It is considered a functional food owing to its various health benefits such as antidiabetic, antihyperlipidemic, antifatigue, hepatoprotective, cardioprotective, antimelanogenic, etc. E. ferox has immense potential in both food and non-food industries. Regardless of being recognized as a superfood packed with nutritional as well as medicinal properties, it is still neglected, and there has not been much attention given to its cultivation. Therefore, in this review, the potential of E. ferox as a superfood has been explored to enhance its utilization in the development of different foods and make it available outside its growing area. PRACTICAL APPLICATIONS: Euryale ferox is abundant in several macronutrients and micronutrients; and considered as a superfood in terms of various health benefits. E. ferox has the ability to be used in the development of different health, functional, and nutraceutical foods, which will open a new door for the food industry to combat with numerous diseases.

Factors Affecting the Binding of Diltiazem to Rainbow Trout Plasma: Implications for the Risk Assessment of Pharmaceuticals in Aquatic Systems.

The accumulation of organic toxicants in fish plasma, and how they partition between the bound and unbound fraction once absorbed, are important metrics in models that seek to predict the risk of such contaminants in aquatic settings. Rapid equilibrium dialysis of diltiazem, an ionizable weak base and important human pharmaceutical contaminant of freshwaters, was conducted with rainbow trout (Oncorhynchus mykiss) plasma. The effect of fed state, fish sex, fish strain/size, and dialysis buffer pH on the binding of radiolabeled diltiazem (9 ng ml-1 ) was assessed. In fed fish, 24.6%-29.5% of diltiazem was free, unbound to plasma proteins. Although starvation of fish resulted in a decrease in plasma protein, the bound fraction of diltiazem remained relatively constant. Consequently, the protein-bound concentration of diltiazem increased with length of starvation. In general, rainbow trout strain was a significant factor affecting plasma binding, although the two strains tested also differed markedly in size. Dialysis buffer pH significantly influenced plasma binding, with a higher unbound diltiazem fraction at pH 6.8 than pH 8.0. These data indicate that empirical measures of plasma binding in fish are important for accurate risk assessment and that the physiological status of a fish is likely to impact its sensitivity to toxicants such as diltiazem. Environ Toxicol Chem 2022;41:3125-3133. © 2022 SETAC.

Chromosomal-level genome of velvet bean (Mucuna pruriens) provides resources for L-DOPA synthetic research and development.

Mucuna pruriens, commonly called velvet bean, is the main natural source of levodopa (L-DOPA), which has been marketed as a psychoactive drug for the clinical management of Parkinson's disease and dopamine-responsive dystonia. Although velvet bean is a very important plant species for food and pharmaceutical manufacturing, the lack of genetic and genomic information about this species severely hinders further molecular research thereon and biotechnological development. Here, we reported the first velvet bean genome, with a size of 500.49 Mb and 11 chromosomes encoding 28,010 proteins. Genomic comparison among legume species indicated that velvet bean speciated ∼29 Ma from soybean clade, without specific genome duplication. Importantly, we identified 21 polyphenol oxidase coding genes that catalyse l-tyrosine to L-DOPA in velvet bean, and two subfamilies showing tandem expansion on Chr3 and Chr7 after speciation. Interestingly, disease-resistant and anti-pathogen gene families were found contracted in velvet bean, which might be related to the expansion of polyphenol oxidase. Our study generated a high-quality genomic reference for velvet bean, an economically important agricultural and medicinal plant, and the newly reported L-DOPA biosynthetic genes could provide indispensable information for the biotechnological and sustainable development of an environment-friendly L-DOPA biosynthesis processing method.

Prioritization based on risk assessment to study the bioconcentration and biotransformation of pharmaceuticals in glass eels (Anguilla anguilla) from the Adour estuary (Basque Country, France).

The presence of contaminants of emerging concern in the aquatic environment directly impacts water-living organisms and can alter their living functions. These compounds are often metabolized and excreted, but they can also be accumulated and spread through the food chain. The metabolized contaminants can also lead to the formation of new compounds with unknown toxicity and bioaccumulation potential. In this work, we have studied the occurrence, bioconcentration, and biotransformation of CECs in glass eels (Anguilla anguilla) using UHPLC-HRMS. To select the target CECs, we first carried out an environmental risk assessment of the WWTP effluent that releases directly into the Adour estuary (Bayonne, Basque Country, France). The risk quotients of every detected contaminant were calculated and three ecotoxicologically relevant contaminants were chosen to perform the exposure experiment: propranolol, diazepam, and irbesartan. An experiment of 14 days consisting of 7 days of exposure and 7 days of depuration was carried out to measure the bioconcentration of the chosen compounds. The quantitative results of the concentrations in glass eel showed that diazepam and irbesartan reached BCF ≈10 on day 7, but both compounds were eliminated after 7 days of depuration. On the other hand, propranolol's concentration remains constant all along with the experiment, and its presence can be detected even in the non-exposed control group, which might suggest environmental contamination. Two additional suspect screening strategies were used to identify metabolization products of the target compounds and other xenobiotics already present in wild glass eels. Only one metabolite was identified, nordiazepam, a well-known diazepam metabolite, probably due to the low metabolic rate of glass eels at this stage. The xenobiotic screening confirmed the presence of more xenobiotics in wild glass eels, prominent among them, the pharmaceuticals exemestane, primidone, iloprost, and norethandrolone.

Absorption, Distribution, Metabolism, and Excretion of Therapeutic Proteins: Current Industry Practices and Future Perspectives.

Therapeutic proteins (TPs) comprise a variety of modalities, including antibody-based drugs, coagulation factors, recombinant cytokines, enzymes, growth factors, and hormones. TPs usually cannot traverse cellular barriers and exert their pharmacological activity by interacting with targets on the exterior membrane of cells or with soluble ligands in the tissue interstitial fluid/blood. Due to their large size, lack of cellular permeability, variation in metabolic fate, and distinct physicochemical characteristics, TPs are subject to different absorption, distribution, metabolism, and excretion (ADME) processes as compared with small molecules. Limited regulatory guidance makes it challenging to determine the most relevant ADME data required for regulatory submissions. The TP ADME working group was sponsored by the Translational and ADME Sciences Leadership Group within the Innovation and Quality (IQ) consortium with objectives to: (1) better understand the current practices of ADME data generated for TPs across IQ member companies, (2) learn about their regulatory strategies and interaction experiences, and (3) provide recommendations on best practices for conducting ADME studies for TPs. To understand current ADME practices and regulatory strategies, an industry-wide survey was conducted within IQ member companies. In addition, ADME data submitted to the U.S. Food and Drug Administration was also collated by reviewing regulatory submission packages of TPs approved between 2011 and 2020. This article summarizes the key learnings from the survey and an overview of ADME data presented in biologics license applications along with future perspectives and recommendations for conducting ADME studies for internal decision-making as well as regulatory submissions for TPs. SIGNIFICANCE STATEMENT: This article provides comprehensive assessment of the current practices of absorption, distribution, metabolism, and excretion (ADME) data generated for therapeutic proteins (TPs) across the Innovation and Quality participating companies and the utility of the data in discovery, development, and regulatory submissions. The TP ADME working group also recommends the best practices for condu-cting ADME studies for internal decision-making and regulatory submissions.

Perspectives on the evaluation and adoption of complex in vitro models in drug development: Workshop with the FDA and the pharmaceutical industry (IQ MPS Affiliate).

Complex in vitro models (CIVM) offer the potential to improve pharmaceutical clinical drug attrition due to safety and/ or efficacy concerns. For this technology to have an impact, the establishment of robust characterization and qualifi­cation plans constructed around specific contexts of use (COU) is required. This article covers the output from a workshop between the Food and Drug Administration (FDA) and Innovation and Quality Microphysiological Systems (IQ MPS) Affiliate. The intent of the workshop was to understand how CIVM technologies are currently being applied by pharma­ceutical companies during drug development and are being tested at the FDA through various case studies in order to identify hurdles (real or perceived) to the adoption of microphysiological systems (MPS) technologies, and to address evaluation/qualification pathways for these technologies. Output from the workshop includes the alignment on a working definition of MPS, a detailed description of the eleven CIVM case studies presented at the workshop, in-depth analysis, and key take aways from breakout sessions on ADME (absorption, distribution, metabolism, and excretion), pharmacology, and safety that covered topics such as qualification and performance criteria, species differences and concordance, and how industry can overcome barriers to regulatory submission of CIVM data. In conclusion, IQ MPS Affiliate and FDA scientists were able to build a general consensus on the need for animal CIVMs for preclinical species to better determine species concordance. Furthermore, there was acceptance that CIVM technologies for use in ADME, pharmacology and safety assessment will require qualification, which will vary depending on the specific COU.

Combining Electrospray Mass Spectrometry (ESI-MS) and Computational Techniques in the Assessment of G-Quadruplex Ligands: A Hybrid Approach to Optimize Hit Discovery.

Guanine-rich sequences forming G-quadruplexes (GQs) are present in several genomes, ranging from viral to human. Given their peculiar localization, the induction of GQ formation or GQ stabilization with small molecules represents a strategy for interfering with crucial biological functions. Investigating the recognition event at the molecular level, with the aim of fully understanding the triggered pharmacological effects, is challenging. Native electrospray ionization mass spectrometry (ESI-MS) is being optimized to study these noncovalent assemblies. Quantitative parameters retrieved from ESI-MS studies, such as binding affinity, the equilibrium binding constant, and sequence selectivity, will be overviewed. Computational experiments supporting the ESI-MS investigation and boosting its efficiency in the search for GQ ligands will also be discussed with practical examples. The combination of ESI-MS and in silico techniques in a hybrid high-throughput-screening workflow represents a valuable tool for the medicinal chemist, providing data on the quantitative and structural aspects of ligand-GQ interactions.