Interspecies scaling and prediction of human clearance: comparison of small- and macro-molecule drugs

Model-Based Interspecies Scaling for Predicting Human Pharmacokinetics of CB 4332, a Complement Factor I Protein

Interspecies scaling of the pharmacokinetics (PK) of CB 4332, a 150 kDa recombinant complement factor I protein, was performed using traditional and model-based approaches to inform first-in-human dose selection. Plasma concentration versus time data from four preclinical PK studies of single intravenous and subcutaneous (SC) CB 4332 dosing in mice, rats and nonhuman primates (NHPs) were modeled simultaneously using naive pooling including allometric scaling. The human-equivalent dose was calculated using the preclinical no observed adverse effect level (NOAEL) as part of the dose-by-factor approach. Pharmacokinetic modeling of CB 4332 revealed species-specific differences in the elimination, which was accounted for by including an additional rat-specific clearance. Signs of anti-drug antibodies (ADA) formation in all rats and some NHPs were observed. Consequently, an additional ADA-induced clearance parameter was estimated including the time of onset. The traditional dose-by-factor approach calculated a maximum recommended starting SC dose of 0.9 mg/kg once weekly, which was predicted it to result in a trough steady-state concentration lower than the determined efficacy target range for CB 4332 in humans. Model simulations predicted the efficacy target range to be reached using 5 mg/kg once weekly SC dosing.

Ulgen K. Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling of Nanomaterials

Nanoparticles (NPs) have been widely used to improve the pharmacokinetic properties and tissue distribution of small molecules such as targeting to a specific tissue of interest, enhancing their systemic circulation, and enlarging their therapeutic properties. NPs have unique and complicated in vivo disposition properties compared to small molecule drugs due to their complex multifunctionality. Physiologically based pharmacokinetic (PBPK) modeling has been a powerful tool in the simulation of the absorption, distribution, metabolism, and elimination (ADME) characteristics of the materials, and it can be used in the characterization and prediction of the systemic disposition, toxicity, efficacy, and target exposure of various types of nanoparticles. In this review, recent advances in PBPK model applications related to the nanoparticles with unique properties, and dispositional features in the biological systems, ADME characteristics, the description of transport processes of nanoparticles in the PBPK model, and the challenges in PBPK model development of nanoparticles are delineated and juxtaposed with those encountered in small molecule models. Nanoparticle related, non-nanoparticle-related, and interspecies-scaling methods applied in PBPK modeling are reviewed. In vitro to in vivo extrapolation (IVIVE) methods being a promising computational tool to provide in vivo predictions from the results of in vitro and in silico studies are discussed. Finally, as a recent advancement ML/AI-based approaches and challenges in PBPK modeling in the estimation of ADME parameters and pharmacokinetic (PK) analysis results are introduced.

Translational modeling-based evidence for enhanced efficacy of standard-of-care drugs in combination with anti-microRNA-155 in non-small-cell lung cancer

BACKGROUND

Elevated microRNA-155 (miR-155) expression in non-small-cell lung cancer (NSCLC) promotes cisplatin resistance and negatively impacts treatment outcomes. However, miR-155 can also boost anti-tumor immunity by suppressing PD-L1 expression. Therapeutic targeting of miR-155 through its antagonist, anti-miR-155, has proven challenging due to its dual molecular effects.

METHODS

We developed a multiscale mechanistic model, calibrated with in vivo data and then extrapolated to humans, to investigate the therapeutic effects of nanoparticle-delivered anti-miR-155 in NSCLC, alone or in combination with standard-of-care drugs.

RESULTS

Model simulations and analyses of the clinical scenario revealed that monotherapy with anti-miR-155 at a dose of 2.5 mg/kg administered once every three weeks has substantial anti-cancer activity. It led to a median progression-free survival (PFS) of 6.7 months, which compared favorably to cisplatin and immune checkpoint inhibitors. Further, we explored the combinations of anti-miR-155 with standard-of-care drugs, and found strongly synergistic two- and three-drug combinations. A three-drug combination of anti-miR-155, cisplatin, and pembrolizumab resulted in a median PFS of 13.1 months, while a two-drug combination of anti-miR-155 and cisplatin resulted in a median PFS of 11.3 months, which emerged as a more practical option due to its simple design and cost-effectiveness. Our analyses also provided valuable insights into unfavorable dose ratios for drug combinations, highlighting the need for optimizing dose regimens to prevent antagonistic effects.

CONCLUSIONS

This work bridges the gap between preclinical development and clinical translation of anti-miR-155 and unravels the potential of anti-miR-155 combination therapies in NSCLC.

Pharmacokinetic models for first-in-human dose selection of immune-activating products in oncology

Pharmacokinetic (PK) models are increasingly submitted to the FDA to support first-in-human (FIH) dose selection of immune-oncology products. To examine whether a simple PK modeling (SPM) using clearance for scaling was acceptable for dose estimation, FIH(SPM) doses were computed and compared to doses that were safely administered to patients. We concluded that the SPM approach is acceptable in FIH dose estimation, but the variables should be carefully selected for CD3 constructs. For CD3 constructs, use of 60 kg BWh, a clearance exponent of 0.75, and a targeted plasma concentration based on relevant and/or sensitive activity assays was an acceptable approach for FIH dose selection; use of 0.85 as the scaling factor is questionable at this time as it resulted in a FIH dose that was too close to the AHD for one product (7%). Immune activating mAbs were not sensitive to changes in the clearance exponent (0.75-0.85) or body weight (60-70 kg). For PD-1/PD-L1 mAbs, using products' in vitro EC50 in the model resulted in suboptimal FIH doses and clinical data of closely related products informed FIH dose selection. PK models submitted by sponsors were diverse in methods, assumptions, and variables, and the resulting FIH doses were not always optimal.

Predictions of tissue concentrations of myclobutanil, oxyfluorfen, and pronamide in rat and human after oral exposures via GastroPlusTM physiologically based pharmacokinetic modelling

Heritage agrochemicals like myclobutanil, oxyfluorfen, and pronamide, are extensively used in agriculture, with well-established studies on their animal toxicity. Yet, human toxicity assessment relies on conventional human risk assessment approaches including the utilization of animal-based ADME (Absorption, Distribution, Metabolism, and Excretion) data. In recent years, Physiologically Based Pharmacokinetic (PBPK) modelling approaches have played an increasing role in human risk assessment of many chemicals including agrochemicals. This study addresses the absence of PBPK-type data for myclobutanil, oxyfluorfen, and pronamide by generating in vitro data for key input PBPK parameters (Caco-2 permeability, rat plasma binding, rat blood to plasma ratio, and rat liver microsomal half-life), followed by generation of PBPK models for these three chemicals via the GastroPlusTM software. Incorporating these experimental input parameters into PBPK models, the prediction accuracy of plasma AUC (area under curve) was significantly improved. Validation against rat oral administration data demonstrated substantial enhancement. Steady-state plasma concentrations (Css) of pronamide aligned well with published data using measured PBPK parameters. Following validation, parent-based tissue concentrations for these agrochemicals were predicted in humans and rats after single or 30-day repeat exposure of 10 mg/kg/day. These predicted concentrations contribute valuable information for future human toxicity risk assessments of these agrochemicals.

Translational modeling-based evidence for enhanced efficacy of standard-of-care drugs in combination with anti-microRNA-155 in non-small-cell lung cancer

Elevated microRNA-155 (miR-155) expression in non-small-cell lung cancer (NSCLC) promotes cisplatin resistance and negatively impacts treatment outcomes. However, miR-155 can also boost anti-tumor immunity by suppressing PD-L1 expression. We developed a multiscale mechanistic model, calibrated with in vivo data and then extrapolated to humans, to investigate the therapeutic effects of nanoparticle-delivered anti-miR-155 in NSCLC, alone or in combination with standard-of-care drugs. Model simulations and analyses of the clinical scenario revealed that monotherapy with anti-miR-155 at a dose of 2.5 mg/kg administered once every three weeks has substantial anti-cancer activity. It led to a median progression-free survival (PFS) of 6.7 months, which compared favorably to cisplatin and immune checkpoint inhibitors. Further, we explored the combinations of anti-miR-155 with standard-of-care drugs, and found strongly synergistic two- and three-drug combinations. A three-drug combination of anti-miR-155, cisplatin, and pembrolizumab resulted in a median PFS of 13.1 months, while a two-drug combination of anti-miR-155 and cisplatin resulted in a median PFS of 11.3 months, which emerged as a more practical option due to its simple design and cost-effectiveness. Our analyses also provided valuable insights into unfavorable dose ratios for drug combinations, highlighting the need for optimizing dose regimen to prevent antagonistic effects. Thus, this work bridges the gap between preclinical development and clinical translation of anti-miR-155 and unravels the potential of anti-miR-155 combination therapies in NSCLC.

Combined translational pharmacometrics approach to support the design and conduct of the first-in-human study of DWP16001

AIMS

The objective of this study was to characterize the pharmacokinetics (PK)/pharmacodynamics (PD) of DWP16001, a novel sodium-glucose cotransporter 2 inhibitor, and predict efficacious doses for the first-in-human study using various translational approaches.

METHODS

A mechanistic PK/PD model was developed for DWP16001 using nonlinear mixed-effect modelling to describe animal PK/PD properties. Using allometry and in silico physiologically based equations, human PK parameters were predicted. Human PD parameters were scaled by applying interspecies difference and in vitro drug-specific factors. Human parameters were refined using early clinical data. Model-predicted PK and PD outcomes were compared to observations before and after parameter refinement.

RESULTS

The PK/PD model of DWP16001 was developed using a 2-compartment model with first-order absorption and indirect response. Efficacious doses of 0.3 and 2 mg of DWP16001 were predicted using human half-maximal inhibitory concentration values translated from Zucker Diabetic Fatty rats and normal rats, respectively. After parameter refinement, doses of 0.2 and 1 mg were predicted to be efficacious for each disease model, which improved the prediction results to within a 1.2-fold difference between the model prediction and observation.

CONCLUSIONS

This study predicted efficacious human doses of DWP16001 using population PK/PD modelling and a combined translational pharmacometrics approach. Early clinical data allowed the methods used to translate in vitro and in vivo findings to clinical PK/PD values for DWP16001 to be optimized. This study has shown that a refinement step can be readily applied to improve model prediction and further support the study design and conduct of a first-in-human study.

Plasma Pharmacokinetics of N-Acetylgalactosamine-Conjugated Small-Interfering Ribonucleic Acids (GalNAc-Conjugated siRNAs)

Small-interfering ribonucleic acids (siRNAs) with N-acetylgalactosamine (GalNAc) conjugation for improved liver uptake represent an emerging class of drugs that modulate liver-expressed therapeutic targets. The pharmacokinetics of GalNAc-siRNAs are characterized by a rapid distribution from plasma to tissue (hours) and a long terminal plasma half-life, analyzed in the form of the antisense strand, driven by redistribution from tissue (weeks). Understanding how clinical pharmacokinetics relate to the dose and type of siRNA chemical stabilizing method used is critical, e.g., to design studies, to investigate safety windows, and to predict the pharmacokinetics of new preclinical assets. To this end, we collected and analyzed pharmacokinetic data from the literature regarding nine GalNAc-siRNAs. Based on this analysis, we showed that the clinical plasma pharmacokinetics of GalNAc-siRNAs are approximately dose proportional and similar between chemical stabilizing methods. This holds for both the area under the concentration-time curve (AUC) and the maximum plasma concentration (Cmax). Corresponding rat and monkey pharmacokinetic data for a subset of the nine GalNAc-siRNAs show dose-proportional Cmax, supra-dose-proportional AUC, and similar pharmacokinetics between chemical stabilizing methods​. Together, the animal and human pharmacokinetic data indicate that plasma clearance divided by bioavailability follows allometric principles and scales between species with an exponent of 0.75. Finally, the clinical plasma concentration-time profiles can be empirically described by standard one-compartment kinetics with first-order absorption up to 24 h after subcutaneous dosing, and by three-compartment kinetics with first-order absorption in general. To describe the system more mechanistically, we report a corrected and unambiguously defined version of a previously published physiologically based pharmacokinetic model.

Comparison and summary of in silico prediction tools for CYP450-mediated drug metabolism

The cytochrome P450 (CYP450) enzyme system is responsible for the metabolism of more than two-thirds of xenobiotics. This review summarizes reports of a series of in silico tools for CYP450 enzyme-drug interaction predictions, including the prediction of sites of metabolism (SOM) of a drug and the identification of inhibitor/substrates for CYP subtypes. We also evaluated four prediction tools to identify CYP inhibitors utilizing 52 of the most frequently prescribed drugs. ADMET Predictor and CYPlebrity demonstrated the best performance. We hope that this review provides guidance for choosing appropriate enzyme prediction tools from a variety of in silico platforms to meet individual needs. Such predictions are useful for medicinal chemists to prioritize their designed compounds for further drug discovery.

Development of a Physiologically Based Pharmacokinetic Model for Nitrofurantoin in Rabbits, Rats, and Humans

Nitrofurantoin (NFT) is a commonly used antibiotic for the treatment of urinary tract infections that can cause liver toxicity. Despite reports of hepatic adverse events associated with NFT exposure, there is still limited understanding of the interplay between NFT exposure, its disposition, and the risk of developing liver toxicity. In this study, we aim to develop a physiologically based pharmacokinetic (PBPK) model for NFT in three different species (rabbits, rats, and humans) that can be used as a standard tool for predicting drug-induced liver injury (DILI). We created several versions of the PBPK model using previously published kinetics data from rabbits, and integrated enterohepatic recirculation (EHR) using rat data. Our model showed that active tubular secretion and reabsorption in the kidney are critical in explaining the non-linear renal clearance and urine kinetics of NFT. We subsequently extrapolated the PBPK model to humans. Adapting the physiology to humans led to predictions consistent with human kinetics data, considering a low amount of NFT to be excreted into bile. Model simulations predicted that the liver of individuals with a moderate-to-severe glomerular filtration rate (GFR) is exposed to two-to-three-fold higher concentrations of NFT than individuals with a normal GFR, which coincided with a substantial reduction in the NFT urinary concentration. In conclusion, people with renal insufficiency may be at a higher risk of developing DILI due to NFT exposure, while at the same time having a suboptimal therapeutic effect with a high risk of drug resistance. Our PBPK model can in the future be used to predict NFT kinetics in individual patients on the basis of characteristics like age and GFR.

Tuning ultrasmall theranostic nanoparticles for MRI contrast and radiation dose amplification

Background: The introduction of magnetic resonance (MR)-guided radiation treatment planning has opened a new space for theranostic nanoparticles to reduce acute toxicity while improving local control. In this work, second-generation AGuIX® nanoparticles (AGuIX-Bi) are synthesized and validated. AGuIX-Bi are shown to maintain MR positive contrast while further amplifying the radiation dose by the replacement of some Gd3+ cations with higher Z Bi3+. These next-generation nanoparticles are based on the AGuIX® platform, which is currently being evaluated in multiple Phase II clinical trials in combination with radiotherapy. Methods: In this clinically scalable methodology, AGuIX® is used as an initial chelation platform to exchange Gd3+ for Bi3+. AGuIX-Bi nanoparticles are synthesized with three ratios of Gd/Bi, each maintaining MR contrast while further amplifying radiation dose relative to Bi3+. Safety, efficacy, and theranostic potential of the nanoparticles were evaluated in vitro and in vivo in a human non-small cell lung cancer model. Results: We demonstrated that increasing Bi3+ in the nanoparticles is associated with more DNA damage and improves in vivo efficacy with a statistically significant delay in tumor growth and 33% complete regression for the largest Bi/Gd ratio tested. The addition of Bi3+ by our synthetic method leads to nanoparticles that present slightly altered pharmacokinetics and lengthening of the period of high tumor accumulation with no observed evidence of toxicity. Conclusions: We confirmed the safety and enhanced efficacy of AGuIX-Bi with radiation therapy at the selected ratio of 30Gd/70Bi. These results provide crucial evidence towards patient translation.

Application of Allometric Scaling to Nanochelator Pharmacokinetics

Deferoxamine (DFO) is an effective FDA-approved iron chelator; however, its use is considerably limited by off-target toxicities and an extremely cumbersome dose regimen involving daily infusions. The recent development of a deferoxamine-based nanochelator (DFO-NP) with selective renal excretion has shown promise in ameliorating iron overload and associated physiological complications in rodent models with a substantially improved safety profile. While the dose- and administration route-dependent pharmacokinetics (PK) of DFO-NPs have been recently characterized, the optimized PK model was not validated, and the prior studies did not directly address the clinical translatability of DFO-NPs into humans. In the present work, these gaps were addressed by applying allometric scaling of DFO-NP PK in rats to predict those in mice and humans. First, this approach predicted serum concentration-time profiles of DFO-NPs, which were similar to those experimentally measured in mice, validating the nonlinear disposition and absorption models for DFO-NPs across the species. Subsequently, we explored the utility of allometric scaling by predicting the PK profile of DFO-NPs in humans under clinically relevant dosing schemes. These in silico efforts demonstrated that the novel nanochelator is expected to improve the PK of DFO when compared to standard infusion regimens of native DFO. Moreover, reasonable formulation strategies were identified and discussed for both early clinical development and more sophisticated formulation development.

Recent advances in measurement of metabolic clearance, metabolite profile and reaction phenotyping of low clearance compounds

INTRODUCTION

Low metabolic clearance is usually a highly desirable property of drug candidates in order to reduce dose and dosing frequency. However, measurement of low clearance can be challenging in drug discovery. A number of new tools have recently been developed to address the gaps in the measurement of intrinsic clearance, identification of metabolites, and reaction phenotyping of low clearance compounds.

AREAS COVERED

The new methodologies of low clearance measurements are discussed, including the hepatocyte relay, HepatoPac®, HμREL®, and spheroid systems. In addition, metabolite formation rate determination and in vivo allometric scaling approaches are covered as alternative methods for low clearance measurements. With these new methods, measurement of ~ 20-fold lower limit of intrinsic clearance can be achieved. The advantages and limitations of each approach are highlighted.

EXPERT OPINION

Although several novel methods have been developed in recent years to address the challenges of low clearance, these assays tend to be time and labor intensive and costly. Future innovations focusing on developing systems with high enzymatic activities, ultra-sensitive universal quantifiable detectors, and artificial intelligence will further enhance our ability to explore the low clearance space.

A PKPD Case Study: Achieving Clinically Relevant Exposures of AZD5991 in Oncology Mouse Models

Capturing human equivalent drug exposures preclinically is a key challenge in the translational process. Motivated by the need to recapitulate the pharmacokinetic (PK) profile of the clinical stage Mcl-1 inhibitor AZD5991 in mice, we describe the methodology used to develop a refined mathematical model relating clinically relevant concentration profiles to efficacy. Administration routes were explored to achieve target exposures matching the clinical exposure of AZD5991. Intravenous infusion using vascular access button (VAB) technology was found to best reproduce clinical target exposures of AZD5991 in mice. Exposure-efficacy relationships were evaluated, demonstrating that dissimilar PK profiles result in differences in target engagement and efficacy outcomes. Thus, these data underscore the importance of accurately ascribing key PK metrics in the translational process to enable clinically meaningful predictions of efficacy.

Novel technologies for applying immune checkpoint blockers

Cancer cells develop several ways to subdue the immune system among others via upregulation of inhibitory immune checkpoint (ICP) proteins. These ICPs paralyze immune effector cells and thereby enable unfettered tumor growth. Monoclonal antibodies (mAbs) that block ICPs can prevent immune exhaustion. Due to their outstanding effects, mAbs revolutionized the field of cancer immunotherapy. However, current ICP therapy regimens suffer from issues related to systemic administration of mAbs, including the onset of immune related adverse events, poor pharmacokinetics, limited tumor accessibility and immunogenicity. These drawbacks and new insights on spatiality prompted the exploration of novel administration routes for mAbs for instance peritumoral delivery. Moreover, novel ICP drug classes that are adept to novel delivery technologies were developed to circumvent the drawbacks of mAbs. We therefore review the state-of-the-art and novel delivery strategies of ICP drugs.

Scaling Pharmacodynamics from Rats to Humans to Support Erythropoietin and Romiplostim Combination Therapy to Treat Erythropoietin-Resistant Anemia

Recombinant human erythropoietin (rHuEPO) is one of the most effective drugs for the treatment of anemia in patients with chronic kidney disease. However, EPO-resistance is an important contributor to the increased risk of adverse effects. We previously showed that EPO treatment could induce precursor cell depletion, resulting in EPO-resistance. We further found that the combination of EPO with romiplostim, a thrombopoietin receptor agonist that can stimulate the expansion of hematopoietic stem cells, can treat EPO-resistance. In this study, we performed interspecies pharmacodynamic (PD) scaling of this combination therapy for human dose prediction. The pharmacokinetic parameters of both rHuEPO and romiplostim in humans were obtained from previous studies. The PD parameters obtained in rats were scaled to humans using allometric equations. The relationship between PD parameters of the megakaryocyte lineage from rats, monkeys, and humans was in agreement with those from the literature on allometric scaling. The PD response was translated to humans based on allometric scaling and agreed with the observed data. These parameters were used to simulate hemoglobin and platelet response in humans. RHuEPO 50 IU/kg thrice weekly and romiplostim 1 μg/kg once every 4 weeks from the second week is the recommended combination dosing regimen according to the model prediction. Our work successfully scaled the PD of rHuEPO and romiplostim monotherapy from rats to humans. The predicted dosing regimen of each drug in the combination therapy is less intensive than the approved starting dose of each drug, which supports additional evaluations of the combination therapy in humans.

Advanced harmonization techniques result in accurate establishment of in vitro-in vivo correlations for oxybenzone from four complex dermal formulations with reapplication

Due to high variability during clinical pharmacokinetic (PK) evaluation, the prediction of in vivo exposure from in vitro absorption testing of topical semisolid and liquid dermal products has historically proven difficult. Since absorption from unoccluded formulations can be influenced by environmental factors such as temperature and humidity, maximal effort must be placed on the harmonization of experimental parameters between in vitro and in vivo testing conditions to establish accurate in vitro/in vivo correlations (IVIVC). Using four different sunscreen formulations as a model, we performed in vitro permeation testing (IVPT) studies with excised human skin and maintained strict harmonization techniques to control application time, occlusion, temperature, and humidity during in vivo human serum PK evaluation. The goal was to investigate if increased control over experimental parameters would result in decreased inter-subject variability of common topical formulations leading to acceptable IVIVC establishment. Using a deconvolution-based approach, excellent point-to-point (Level A correlation) IVIVC for the entire 12-h study duration was achieved for all four sunscreen formulations with < 10% prediction error of both area under the curve (AUC) and peak concentration (C_max) estimation. The low variability of in vivo absorption data presents a proof-of-concept protocol design for testing of complex semisolid and liquid topical formulations applied over a large surface area with reapplication in a reliable manner. This work also presents the opportunity for expanded development of testing for the impact of altered temperature and humidity conditions on product absorption in vivo with a high degree of precision.

Impacts of a Zwitterionic Peptide on its Fusion Protein

Therapeutic proteins frequently need to be modified with high-molecular-weight molecules to improve their pharmacokinetic properties. The genetic linkage of therapeutic proteins to a high-molecular-weight zwitterionic peptide, termed EKP, offers a promising approach. As with any protein modification, EKP could impact the structural behavior and receptor binding properties of the linked therapeutic protein, thereby altering its bioactivity. To evaluate the effects of EKP on therapeutic proteins, we study the receptor binding properties of high-molecular-weight EKP linked to the growth colony-stimulating factor (GCSF) using the genetically based yeast display platform. We find that yeast-displayed EKP-GCSF and GCSF exhibits similar binding to its receptor GCSF-R, suggesting that EKP does not hinder receptor binding. Furthermore, yeast-displayed EKP-GCSF demonstrates protection against thermal denaturation compared to GCSF. Similarly, to study the structural effects of EKP on GCSF, we employ in silico modeling using alphaFold2 in conjunction with molecular dynamics (MD) simulations. Likewise, in silico modeling reveals that EKP does not alter the structural behavior of GCSF. Finally, we demonstrate the functional benefits of EKP, by which the EKP-GCSF fusion protein produced in Escherichia coli exhibits improved pharmacokinetics and prolonged bioactivity in vivo.

Sialylation-dependent pharmacokinetics and differential complement pathway inhibition are hallmarks of CR1 activity in vivo

Human Complement Receptor 1 (HuCR1) is a potent membrane-bound regulator of complement both in vitro and in vivo, acting via interaction with its ligands C3b and C4b. Soluble versions of HuCR1 have been described such as TP10, the recombinant full-length extracellular domain, and more recently CSL040, a truncated version lacking the C-terminal long homologous repeat domain D (LHR-D). However, the role of N-linked glycosylation in determining its pharmacokinetic (PK) and pharmacodynamic (PD) properties is only partly understood. We demonstrated a relationship between the asialo-N-glycan levels of CSL040 and its PK/PD properties in rats and non-human primates (NHPs), using recombinant CSL040 preparations with varying asialo-N-glycan levels. The clearance mechanism likely involves the asialoglycoprotein receptor (ASGR), as clearance of CSL040 with a high proportion of asialo-N-glycans was attenuated in vivo by co-administration of rats with asialofetuin, which saturates the ASGR. Biodistribution studies also showed CSL040 localisation to the liver following systemic administration. Our studies uncovered differential PD effects by CSL040 on complement pathways, with extended inhibition in both rats and NHPs of the alternative pathway compared to the classical and lectin pathways that were not correlated with its PK profile. Further studies showed that this effect was dose dependent and observed with both CSL040 and the full-length extracellular domain of HuCR1. Taken together, our data suggests that sialylation optimization is an important consideration for developing HuCR1-based therapeutic candidates such as CSL040 with improved PK properties and shows that CSL040 has superior PK/PD responses compared to full-length soluble HuCR1.

Preclinical pharmacokinetics and safety of intravenous RTD-1

Severe illness caused by coronavirus disease 2019 (COVID-19) is characterized by an overexuberant inflammatory response resulting in acute respiratory distress syndrome (ARDS) and progressive respiratory failure (A. Gupta, M. V. Madhavan, K. Sehgal, N. Nair, et al., Nat Med 26:1017–1032, 2020, https://doi.org/10.1038/s41591-020-0968-3). Rhesus theta (θ) defensin-1 (RTD-1) is a macrocyclic host defense peptide exhibiting antimicrobial and immunomodulatory activities. RTD-1 treatment significantly improved survival in murine models of a severe acute respiratory syndrome (SARS-CoV-1) and endotoxin-induced acute lung injury (ALI) (C. L. Wohlford-Lenane, D. K. Meyerholz, S. Perlman, H. Zhou, et al., J Virol 83:11385–11390, 2009, https://doi.org/10.1128/JVI.01363-09; J. G. Jayne, T. J. Bensman, J. B. Schaal, A. Y. J. Park, et al., Am J Respir Cell Mol Biol 58:310–319, 2018, https://doi.org/10.1165/rcmb.2016-0428OC). This investigation aimed to characterize the preclinical pharmacokinetics (PK) and safety of intravenous (i.v.) RTD-1. Based on the lack of adverse findings, the no observed adverse effect level (NOAEL) was established at 10 mg/kg/day in rats and 15 mg/kg/day in monkeys. Analysis of single ascending dose studies in both species revealed greater-than-dose-proportional increases in the area under the curve extrapolated to infinity (AUC_0-∞) (e.g., 8-fold increase from 5 mg/kg to 20 mg/kg in rats) suggestive of nonlinear PK. The volume of distribution at steady state (V_ss) ranged between 550 and 1,461 mL/kg, indicating extensive tissue distribution, which was validated in a biodistribution study of [¹⁴C]RTD-1 in rats. Based on interspecies allometric scaling, the predicted human clearance and V_ss are 6.48 L/h and 28.0 L, respectively, for an adult (70 kg). To achieve plasma exposures associated with therapeutic efficacy established in a murine model of ALI, the estimated human equivalent dose (HED) is between 0.36 and 0.83 mg/kg/day. The excellent safety profile demonstrated in these studies and the efficacy observed in the murine models support the clinical investigation of RTD-1 for treatment of COVID-19 or other pulmonary inflammatory diseases.

Information-theoretic approach in allometric scaling relations of DNA and proteins

Allometric scaling relations can be observed in between molecular parameters. Hence, we looked for presence of such relation among sizes (i.e., lengths) of proteins and genes. Protein lengths exist in the literature as the number of amino acids. They can also be derived from the mRNA lengths. Here, we looked for allometric scaling relation by using such data and simultaneously, the data was compared with the sizes of genes and proteins that were obtained from our modified information-theoretic approach. Results implied presence of scaling relation in the calculated results. This was expected due to the implemented modification in the information-theoretic calculation. Relation in the literature-based data was lacking high goodness of fit value. It could be due to physical factors and selective pressures, which ended up in deviations of the literature-sourced values from those in the model. Genome size is correlated with cell size. Intracellular volume, which is related to the DNA size, would require certain number of proteins, the sizes of which can therefore be correlated with the protein sizes. Cell sizes, genome sizes, and average protein and gene sizes, along with the number of proteins, namely the expression levels of the genes, are the physical factors, and the molecular factors influence those physical factors. The selective pressures on those can act through the connection between those physical factors and limit the dynamic ranges. Biological measures could be prone to such forces and are likely to deviate from expected models, regardless of the validity of assumptions, unless those are also implemented in the models. Yet, present discrepancies could be pointing at the need for model improvement, data imperfection, invalid assumptions, etc. Still, current work highlights possible use of information-theoretic approach in allometric scaling relations' studies.

The role of DMPK science in improving pharmaceutical research and development efficiency

The successful regulatory authority approval rate of drug candidates in the drug development pipeline is crucial for determining pharmaceutical research and development (R&D) efficiency. Regulatory authorities include the US Food and Drug Administration (FDA), European Medicines Agency (EMA), and Pharmaceutical and Food Safety Bureau Japan (PFSB), among others. Optimal drug metabolism and pharmacokinetics (DMPK) properties influence the progression of a drug candidate from the preclinical to the clinical phase. In this review, we provide a comprehensive assessment of essential concepts, methods, improvements, and challenges in DMPK science and its significance in drug development. This information provides insights into the association of DMPK science with pharmaceutical R&D efficiency.

Experimental Data and PBPK Modeling Quantify Antibody Interference in PEGylated Drug Carrier Delivery

Physiologically-based pharmacokinetic (PBPK) modeling is a popular drug development tool that integrates physiology, drug physicochemical properties, preclinical data, and clinical information to predict drug systemic disposition. Since PBPK models seek to capture complex physiology, parameter uncertainty and variability is a prevailing challenge: there are often more compartments (e.g., organs, each with drug flux and retention mechanisms, and associated model parameters) than can be simultaneously measured. To improve the fidelity of PBPK modeling, one approach is to search and optimize within the high-dimensional model parameter space, based on experimental time-series measurements of drug distributions. Here, we employ Latin Hypercube Sampling (LHS) on a PBPK model of PEG-liposomes (PL) that tracks biodistribution in an 8-compartment mouse circulatory system, in the presence (APA+) or absence (naïve) of anti-PEG antibodies (APA). Near-continuous experimental measurements of PL concentration during the first hour post-injection from the liver, spleen, kidney, muscle, lung, and blood plasma, based on PET/CT imaging in live mice, are used as truth sets with LHS to infer optimal parameter ranges for the full PBPK model. The data and model quantify that PL retention in the liver is the primary differentiator of biodistribution patterns in naïve versus APA+ mice, and spleen the secondary differentiator. Retention of PEGylated nanomedicines is substantially amplified in APA+ mice, likely due to PL-bound APA engaging specific receptors in the liver and spleen that bind antibody Fc domains. Our work illustrates how applying LHS to PBPK models can further mechanistic understanding of the biodistribution and antibody-mediated clearance of specific drugs.

Bioequivalence assessment of high-capacity polymeric micelle nanoformulation of paclitaxel and Abraxane® in rodent and non-human primate models using a stable isotope tracer assay

The in vivo fate of nanoformulated drugs is governed by the physicochemical properties of the drug and the functionality of nanocarriers. Nanoformulations such as polymeric micelles, which physically encapsulate poorly soluble drugs, release their payload into the bloodstream during systemic circulation. This results in three distinct fractions of the drug-nanomedicine: encapsulated, protein-bound, and free drug. Having a thorough understanding of the pharmacokinetic (PK) profiles of each fraction is essential to elucidate mechanisms of nanomedicine-driven changes in drug exposure and PK/PD relationships pharmacodynamic activity. Here, we present a comprehensive preclinical assessment of the poly (2-oxazoline)-based polymeric micelle of paclitaxel (PTX) (POXOL hl-PM), including bioequivalence comparison to the clinically approved paclitaxel nanomedicine, Abraxane®. Physicochemical characterization and toxicity analysis of POXOL hl-PM was conducted using standardized protocols by the Nanotechnology Characterization Laboratory (NCL). The bioequivalence of POXOL hl-PM to Abraxane® was evaluated in rats and rhesus macaques using the NCL's established stable isotope tracer ultrafiltration assay (SITUA) to delineate the plasma PK of each PTX fraction. The SITUA study revealed that POXOL hl-PM and Abraxane® had comparable PK profiles not only for total PTX but also for the distinct drug fractions, suggesting bioequivalence in given animal models. The comprehensive preclinical evaluation of POXOL hl-PM in this study showcases a series of widely applicable standardized studies by NCL for assessing nanoformulations prior to clinical investigation.

Single-nanometer iron oxide nanoparticles as tissue-permeable MRI contrast agents

Magnetic nanoparticles are robust contrast agents for MRI and often produce particularly strong signal changes per particle. Leveraging these effects to probe cellular- and molecular-level phenomena in tissue can, however, be hindered by the large sizes of typical nanoparticle contrast agents. To address this limitation, we introduce single-nanometer iron oxide (SNIO) particles that exhibit superparamagnetic properties in conjunction with hydrodynamic diameters comparable to small, highly diffusible imaging agents. These particles efficiently brighten the signal in T ₁-weighted MRI, producing per-molecule longitudinal relaxation enhancements over 10 times greater than conventional gadolinium-based contrast agents. We show that SNIOs permeate biological tissue effectively following injection into brain parenchyma or cerebrospinal fluid. We also demonstrate that SNIOs readily enter the brain following ultrasound-induced blood-brain barrier disruption, emulating the performance of a gadolinium agent and providing a basis for future biomedical applications. These results thus demonstrate a platform for MRI probe development that combines advantages of small-molecule imaging agents with the potency of nanoscale materials.

Toxicokinetics of U-47700, tramadol, and their main metabolites in pigs following intravenous administration: is a multiple species allometric scaling approach useful for the extrapolation of toxicokinetic parameters to humans?

New synthetic opioids (NSOs) pose a public health concern since their emergence on the illicit drug market and are gaining increasing importance in forensic toxicology. Like many other new psychoactive substances, NSOs are consumed without any preclinical safety data or any knowledge on toxicokinetic (TK) data. Due to ethical reasons, controlled human TK studies cannot be performed for the assessment of these relevant data. As an alternative animal experimental approach, six pigs per drug received a single intravenous dose of 100 µg/kg body weight (BW) of U-47700 or 1000 µg/kg BW of tramadol to evaluate whether this species is suitable to assess the TK of NSOs. The drugs were determined in serum and whole blood using a fully validated method based on solid-phase extraction and LC–MS/MS. The concentration–time profiles and a population (pop) TK analysis revealed that a three-compartment model best described the TK data of both opioids. Central volumes of distribution were 0.94 L/kg for U-47700 and 1.25 L/kg for tramadol and central (metabolic) clearances were estimated at 1.57 L/h/kg and 1.85 L/h/kg for U-47700 and tramadol, respectively. The final popTK model parameters for pigs were upscaled via allometric scaling techniques. In comparison to published human data, concentration–time profiles for tramadol could successfully be predicted with single species allometric scaling. Furthermore, possible profiles for U-47700 in humans were simulated. The findings of this study indicate that unlike a multiple species scaling approach, pigs in conjunction with TK modeling are a suitable tool for the assessment of TK data of NSOs and the prediction of human TK data.

Peptide-Based Inhibitors for SARS-CoV-2 and SARS-CoV

The COVID-19 (coronavirus disease) global pandemic, caused by the spread of the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus, currently has limited treatment options which include vaccines, anti-virals, and repurposed therapeutics. With their high specificity, tunability, and biocompatibility, small molecules like peptides are positioned to act as key players in combating SARS-CoV-2, and can be readily modified to match viral mutation rate. A recent expansion of the understanding of the viral structure and entry mechanisms has led to the proliferation of therapeutic viral entry inhibitors. In this comprehensive review, inhibitors of SARS and SARS-CoV-2 are investigated and discussed based on therapeutic design, inhibitory mechanistic approaches, and common targets. Peptide therapeutics are highlighted, which have demonstrated in vitro or in vivo efficacy, discuss advantages of peptide therapeutics, and common strategies in identifying targets for viral inhibition.

Prospective prediction of plasma pharmacokinetics of a novel immune-modulating agent in cancer patients after intra-tumoral administration: translation from non-clinical species to humans

Intra-tumoral (I-TUMOUR) delivery is being widely explored for novel anti-cancer agents. This route is anticipated to result in high tumour concentrations leading to better efficacy and safety. Prediction of human systemic pharmacokinetics (PK) from non-clinical species facilitates understanding of pharmacokinetic-pharmacodynamic relationships, efficient dose selection, and risk assessment of novel drugs. However, there is limited knowledge on the predictability of human pharmacokinetics following I-TUMOUR delivery.In this publication, we present a case study wherein human systemic PK of a novel agent administered intra-tumourally was prospectively predicted and compared with observed human PK.Simple allometry was used to project the human clearance (10.5 mL/min/kg) and steady-state volume of distribution (1.4 L/kg) after intravenous (IV) dosing. Using these IV PK parameters and assuming rapid absorption and complete I-TUMOUR bioavailability, human plasma PK profile was simulated. The projected 30 min concentrations and AUC_(0-6h) were within 1.9 to 2.5-fold and 1 to 1.4-fold of the observed PK indicating a reasonable concordance between predicted and observed PK.To our knowledge, this is the first article that prospectively projected human pharmacokinetics after I-TUMOUR dosing. The results from this study indicate that similar approaches can be used to project the human PK of other I-TUMOUR agents.

Examination of Urinary Excretion of Unchanged Drug in Humans and Preclinical Animal Models: Increasing the Predictability of Poor Metabolism in Humans

PURPOSE

A dataset of fraction excreted unchanged in the urine (fe) values was developed and used to evaluate the ability of preclinical animal species to predict high urinary excretion, and corresponding poor metabolism, in humans.

METHODS

A literature review of fe values in rats, dogs, and monkeys was conducted for all Biopharmaceutics Drug Disposition Classification System (BDDCS) Class 3 and 4 drugs (n=352) and a set of Class 1 and 2 drugs (n=80). The final dataset consisted of 202 total fe values for 135 unique drugs. Human and animal data were compared through correlations, two-fold analysis, and binary classifications of high (fe ≥30%) versus low (<30%) urinary excretion in humans. Receiver Operating Characteristic curves were plotted to optimize animal fe thresholds.

RESULTS

Significant correlations were found between fe values for each animal species and human fe (p<0.05). Sixty-five percent of all fe values were within two-fold of human fe with animals more likely to underpredict human urinary excretion as opposed to overpredict. Dogs were the most reliable predictors of human fe of the three animal species examined with 72% of fe values within two-fold of human fe and the greatest accuracy in predicting human fe ≥30%. ROC determined thresholds of ≥25% in rats, ≥19% in dogs, and ≥10% in monkeys had improved accuracies in predicting human fe of ≥30%.

CONCLUSIONS

Drugs with high urinary excretion in animals are likely to have high urinary excretion in humans. Animal models tend to underpredict the urinary excretion of unchanged drug in humans.

Interspecies Scaling of Human Clearance and Plasma Trough Exposure for Antisense Oligonucleotides: A Retrospective Analysis of GalNAc3-Conjugated and Unconjugated-Antisense Oligonucleotides

It is well documented and generally accepted that human clearance (CL) of unconjugated single-strand antisense oligonucleotides (ASOs) can be directly predicted from monkeys by body weight (BW) on a mg/kg dose basis. However, the scaling for triantennary N-acetyl galactosamine (GalNAc₃)-conjugated ASOs has not been fully established. In this study, we retrospectively analyzed pharmacokinetic data from 9 GalNAc₃-conjugated and 12 unconjugated single-stranded ASOs (ten 2'-methoxyethyl and two 2', 4'-constrained ethyl ASOs) to identify an appropriate allometric scaling factor between the two species. In addition, we compared the trough plasma concentrations (C_trough, a surrogate for tissue exposure) between monkeys and humans at comparable dose levels, aiming at predicting tissue distribution in humans from monkeys. Overall, the median plasma CL ratios (monkey CL/human CL) were 1.05 and 0.94 when CL was normalized by BW, as compared with 0.33 and 0.29 when CL was normalized by body surface area (BSA) for the 12 unconjugated and 9 GalNAc₃-conjugated ASOs, respectively. Similarly, the median C_trough ratios (C_trough in monkeys/C_trough in humans) were 0.96 and 1.71, respectively, when C_trough was normalized by mg/kg dose as compared with 3.10 and 5.50 when C_trough was normalized by mg/m² dose for the same unconjugated and conjugated ASOs, respectively. Equivalent CL and dose-normalized plasma C_trough between monkeys and humans suggest similar pharmacokinetic profiles and tissue distribution between the two species on a per kilogram BW basis. In conclusion, human CL and plasma C_trough (a surrogate of tissue distribution) can be directly predicted (1:1 or within twofold) from monkeys by BW on a mg/kg dose basis but these parameters can be under- or over-predicted by BSA on a mg/m² dose basis. These results provide evidence for single species scaling from monkeys to humans directly and, thus, they can facilitate early human dose prediction in ASO drug development.

Development of New Tuberculosis Drugs: Translation to Regimen Composition for Drug-Sensitive and Multidrug-Resistant Tuberculosis

Tuberculosis (TB) kills more people than any other infectious disease. Challenges for developing better treatments include the complex pathology due to within-host immune dynamics, interpatient variability in disease severity and drug pharmacokinetics-pharmacodynamics (PK-PD), and the growing emergence of resistance. Model-informed drug development using quantitative and translational pharmacology has become increasingly recognized as a method capable of drug prioritization and regimen optimization to efficiently progress compounds through TB drug development phases. In this review, we examine translational models and tools, including plasma PK scaling, site-of-disease lesion PK, host-immune and bacteria interplay, combination PK-PD models of multidrug regimens, resistance formation, and integration of data across nonclinical and clinical phases.We propose a workflow that integrates these tools with computational platforms to identify drug combinations that have the potential to accelerate sterilization, reduce relapse rates, and limit the emergence of resistance.

Allometric scaling of therapeutic monoclonal antibodies in preclinical and clinical settings

Constant technological advancement enabled the production of therapeutic monoclonal antibodies (mAbs) and will continue to contribute to their rapid expansion. Compared to small-molecule drugs, mAbs have favorable characteristics, but also more complex pharmacokinetics (PK), e.g., target-mediated nonlinear elimination and recycling by neonatal Fc-receptor. This review briefly discusses mAb biology, similarities and differences in PK processes across species and within human, and provides a detailed overview of allometric scaling approaches for translating mAb PK from preclinical species to human and extrapolating from adults to children. The approaches described here will remain vital in mAb drug development, although more data are needed, for example, from very young patients and mAbs with nonlinear PK, to allow for more confident conclusions and contribute to further growth of this field. Improving mAb PK predictions will facilitate better planning of (pediatric) clinical studies and enable progression toward the ultimate goal of expediting drug development.

Model-Informed Drug Development for Antimicrobials: Translational PK and PK/PD Modeling to Predict an Efficacious Human Dose for Apramycin

Apramycin represents a subclass of aminoglycoside antibiotics that has been shown to evade almost all mechanisms of clinically relevant aminoglycoside resistance. Model-informed drug development may facilitate its transition from preclinical to clinical phase. This study explored the potential of pharmacokinetic/pharmacodynamic (PK/PD) modeling to maximize the use of in vitro time-kill and in vivo preclinical data for prediction of a human efficacious dose (HED) for apramycin. PK model parameters of apramycin from four different species (mouse, rat, guinea pig, and dog) were allometrically scaled to humans. A semimechanistic PK/PD model was developed from the rich in vitro data on four Escherichia coli strains and subsequently the sparse in vivo efficacy data on the same strains were integrated. An efficacious human dose was predicted from the PK/PD model and compared with the classical PK/PD index methodology and the aminoglycoside dose similarity. One-compartment models described the PK data and human values for clearance and volume of distribution were predicted to 7.07 L/hour and 26.8 L, respectively. The required fAUC/MIC (area under the unbound drug concentration-time curve over MIC ratio) targets for stasis and 1-log kill in the thigh model were 34.5 and 76.2, respectively. The developed PK/PD model predicted the efficacy data well with strain-specific differences in susceptibility, maximum bacterial load, and resistance development. All three dose prediction approaches supported an apramycin daily dose of 30 mg/kg for a typical adult patient. The results indicate that the mechanistic PK/PD modeling approach can be suitable for HED prediction and serves to efficiently integrate all available efficacy data with potential to improve predictive capacity.

Improving the Pharmacodynamics and In Vivo Activity of ENPP1-Fc Through Protein and Glycosylation Engineering

Enzyme replacement with ectonucleotide pyrophosphatase phospodiesterase‐1 (ENPP1) eliminates mortality in a murine model of the lethal calcification disorder generalized arterial calcification of infancy. We used protein engineering, glycan optimization, and a novel biomanufacturing platform to enhance potency by using a three‐prong strategy. First, we added new N‐glycans to ENPP1; second, we optimized pH‐dependent cellular recycling by protein engineering of the Fc neonatal receptor; finally, we used a two‐step process to improve sialylation by first producing ENPP1‐Fc in cells stably transfected with human α‐2,6‐sialyltransferase (ST6) and further enhanced terminal sialylation by supplementing production with 1,3,4‐O‐Bu₃ManNAc. These steps sequentially increased the half‐life of the parent compound in rodents from 37 hours to ~ 67 hours with an added N‐glycan, to ~ 96 hours with optimized pH‐dependent Fc recycling, to ~ 204 hours when the therapeutic was produced in ST6‐overexpressing cells with 1,3,4‐O‐Bu₃ManNAc supplementation. The alterations were demonstrated to increase drug potency by maintaining efficacious levels of plasma phosphoanhydride pyrophosphate in ENPP1‐deficient mice when the optimized biologic was administered at a 10‐fold lower mass dose less frequently than the parent compound—once every 10 days vs. 3 times a week. We believe these improvements represent a general strategy to rationally optimize protein therapeutics.

Application of Pharmacokinetic-Pharmacodynamic Modeling in Drug Delivery: Development and Challenges

With the advancement of technology, drug delivery systems and molecules with more complex architecture are developed. As a result, the drug absorption and disposition processes after administration of these drug delivery systems and engineered molecules become exceedingly complex. As the pharmacokinetic and pharmacodynamic (PK-PD) modeling allows for the separation of the drug-, carrier- and pharmacological system-specific parameters, it has been widely used to improve understanding of the in vivo behavior of these complex delivery systems and help their development. In this review, we summarized the basic PK-PD modeling theory in drug delivery and demonstrated how it had been applied to help the development of new delivery systems and modified large molecules. The linkage between PK and PD was highlighted. In particular, we exemplified the application of PK-PD modeling in the development of extended-release formulations, liposomal drugs, modified proteins, and antibody-drug conjugates. Furthermore, the model-based simulation using primary PD models for direct and indirect PD responses was conducted to explain the assertion of hypothetical minimal effective concentration or threshold in the exposure-response relationship of many drugs and its misconception. The limitations and challenges of the mechanism-based PK-PD model were also discussed.

Pharmacokinetic/Pharmacodynamic Determination and Preclinical Pharmacokinetics of the β-Lactamase Inhibitor ETX1317 and Its Orally Available Prodrug ETX0282

Increasingly resistant Enterobacteriaceae have emerged as a health threat in both hospital and community settings. Infections of the urinary tract, once often treated with oral agents in the community, are requiring increased hospitalization and use of intravenously administered agents for effective treatment. These isolates often carry extended spectrum β-lactamases (ESBLs) and carbapenemases that necessitate the need for an inhibitor to cover a broad range of β-lactamases. ETX1317 is a novel diazabicyclooctane class serine β-lactamase inhibitor that restores the antibacterial activity of several classes of β-lactams, including third-generation cephalosporins such as cefpodoxime. ETX1317 is currently being developed as an orally available prodrug, ETX0282, to be administered with cefpodoxime proxetil (CPDP). The combination has demonstrated oral efficacy in murine models of infection. Pharmacokinetics established in preclinical species and pharmacokinetic/pharmacodynamic attributes suggest the orally administered combination ETX0282 + CPDP could serve as an effective treatment option against contemporary ESBL and carbapenemase-producing Enterobacteriaceae.

Comparison of In Vitro and In Vivo Percutaneous Absorption Across Human Skin Using BAY1003803 Formulated as Ointment and Cream

Direct comparisons between skin absorption data and clinical pharmacokinetic data are rare. Here we use the lipophilic nonsteroidal selective glucocorticoid receptor agonist BAY1003803 to make such a comparison. The objective is to find the extent to which measurements of skin permeation in vitro can be used to predict the corresponding permeation in vivo for human pharmacokinetics of topically applied substances. BAY1003803 was prepared in various formulations: ointment, hydrophilic cream, lipophilic cream, and milk. Its ability to permeate healthy human skin was measured in vitro in static diffusion cells, and percutaneous absorption as well as dermal delivery was measured thereafter, for 2 selected formulations, in vivo in healthy volunteers. Absorption in vivo comparing ointment and lipophilic cream was correlated with expectation based on the dermal delivery obtained in vitro. A 2.17-fold higher systemic exposure to BAY1003803 was achieved by the ointment formulation. This is well in line with the predicted exposure difference of 2.74 based on the in vitro data. In conclusion, in vitro skin absorption studies using human skin are suitable for the prediction of systemic exposure and formulation effects in vivo; they can therefore be applied to guide the design of clinical investigations of dermatological preparations.

Quantitative Prediction of Human Pharmacokinetics and Pharmacodynamics of CKD519, a Potent Inhibitor of Cholesteryl Ester Transfer Protein (CETP)

CKD519, a selective inhibitor of cholesteryl ester transfer protein(CETP), is undergoing development as an oral agent for the treatment of primary hypercholesterolemia and mixed hyperlipidemia. The aim of this study was to predict the appropriate efficacious dose of CKD519 for humans in terms of the inhibition of CETP activity by developing a CKD519 pharmacokinetic/pharmacodynamic (PK/PD) model based on data from preclinical studies. CKD519 was intravenously and orally administered to hamsters, rats, and monkeys for PK assessment. Animal PK models of all dose levels in each species were developed using mixed effect modeling analysis for exploration, and an interspecies model where allometric scaling was applied was developed based on the integrated animal PK data to predict the human PK profile. PD parameters and profile were predicted using in vitro potency and same-in-class drug information. The two-compartment first-order elimination model with Weibull-type absorption and bioavailability following the sigmoid E_max model was selected as the final PK model. The PK/PD model was developed by linking the interspecies PK model with the E_max model of the same-in-class drug. The predicted PK/PD profile and parameters were used to simulate the human PK/PD profiles for different dose levels, and based on the simulation result, the appropriate efficacious dose was estimated as 25 mg in a 60 kg human. However, there were some discrepancies between the predicted and observed human PK/PD profiles compared to the phase I clinical data. The huge difference between the observed and predicted bioavailability suggests that there is a hurdle in predicting the absorption parameter only from animal PK data.

Research tools for extrapolating the disposition and pharmacokinetics of nanomaterials from preclinical animals to humans

A critical step in the translational science of nanomaterials from preclinical animal studies to humans is the comprehensive investigation of their disposition (or ADME) and pharmacokinetic behaviours. Disposition and pharmacokinetic data are ideally collected in different animal species (rodent and nonrodent), at different dose levels, and following multiple administrations. These data are used to assess the systemic exposure and effect to nanomaterials, primary determinants of their potential toxicity and therapeutic efficacy. At toxic doses in animal models, pharmacokinetic (termed toxicokinetic) data are related to toxicologic findings that inform the design of nonclinical toxicity studies and contribute to the determination of the maximum recommended starting dose in clinical phase 1 trials. Nanomaterials present a unique challenge for disposition and pharmacokinetic investigations owing to their prolonged circulation times, nonlinear pharmacokinetic profiles, and their extensive distribution into tissues. Predictive relationships between nanomaterial physicochemical properties and behaviours in vivo are lacking and are confounded by anatomical, physiological, and immunological differences amongst preclinical animal models and humans. These challenges are poorly understood and frequently overlooked by investigators, leading to inaccurate assumptions of disposition, pharmacokinetic, and toxicokinetics profiles across species that can have profoundly detrimental impacts for nonclinical toxicity studies and clinical phase 1 trials. Herein are highlighted two research tools for analysing and interpreting disposition and pharmacokinetic data from multiple species and for extrapolating this data accurately in humans. Empirical methodologies and mechanistic mathematical modelling approaches are discussed with emphasis placed on important considerations and caveats for representing nanomaterials, such as the importance of integrating physiological variables associated with the mononuclear phagocyte system (MPS) into extrapolation methods for nanomaterials. The application of these tools will be examined in recent examples of investigational and clinically approved nanomaterials. Finally, strategies for applying these extrapolation tools in a complementary manner to perform dose predictions and in silico toxicity assessments in humans will be explained. A greater familiarity with the available tools and prior experiences of extrapolating nanomaterial disposition and pharmacokinetics from preclinical animal models to humans will hopefully result in a more straightforward roadmap for the clinical translation of promising nanomaterials.

In Silico Prediction of the Absorption and Disposition of Cefadroxil in Humans using an Intestinal Permeability Method Scaled from Humanized PepT1 Mice

It is difficult to predict the pharmacokinetics and plasma concentration-time profiles of new chemical entities in humans based on animal data. Some pharmacokinetic parameters, such as clearance and volume of distribution, can be scaled allometrically from rodents, mammals, and nonhuman primates with good success. However, it is far more challenging to predict the oral pharmacokinetics of experimental drug candidates. In the present study, we used in situ estimates of intestinal permeability, obtained in silico and from rat, wild-type (WT), and humanized PepT1 (huPepT1) mice, to predict the systemic exposure of cefadroxil, an orally administered model compound, under a variety of conditions. Using the GastroPlus simulation software program (Simulations Plus, Lancaster, CA), we found that the C max and area under the plasma concentration-time curve from time zero to the last measurable concentration of cefadroxil were better predicted using intestinal permeability estimates (both segmental and jejunal) from huPepT1 than from WT mice, and that intestinal permeabilities based on in silico and rat estimates gave worse predictions. We also observed that accurate predictions were possible for cefadroxil during oral dose escalation (i.e., 5, 15, and 30 mg/kg cefadroxil), a drug-drug interaction study (i.e., 5 mg/kg oral cefadroxil plus 45 mg/kg oral cephalexin), and an oral multiple dose study [i.e., 500 mg (6.7 mg/kg) cefadroxil every 6 hours]. Finally, the greatest amount of cefadroxil was absorbed in duodenal and jejunal segments of the small intestine after a 5 mg/kg oral dose. Thus, by combining a humanized mouse model and in silico software, the present study offers a novel strategy for better translating preclinical pharmacokinetic data to oral drug exposure during first-in-human studies.

In Vitro-In Vivo Extrapolation and Hepatic Clearance-Dependent Underprediction

Accurately predicting the hepatic clearance of compounds using in vitro to in vivo extrapolation (IVIVE) is crucial within the pharmaceutical industry. However, several groups have recently highlighted the serious error in the process. Although empirical or regression-based scaling factors may be used to mitigate the common underprediction, they provide unsatisfying solutions because the reasoning behind the underlying error has yet to be determined. One previously noted trend was intrinsic clearance-dependent underprediction, highlighting the limitations of current in vitro systems. When applying these generated in vitro intrinsic clearance values during drug development and making first-in-human dose predictions for new chemical entities though, hepatic clearance is the parameter that must be estimated using a model of hepatic disposition, such as the well-stirred model. Here, we examine error across hepatic clearance ranges and find a similar hepatic clearance-dependent trend, with high clearance compounds not predicted to be so, demonstrating another gap in the field.

Design and Conduct Considerations for First-in-Human Trials

A milestone step in translational science to transform basic scientific discoveries into therapeutic applications is the advancement of a drug candidate from preclinical studies to initial human testing. First-in-human (FIH) trials serve as the link to advance new promising drug candidates and are conducted primarily to determine the safe dose range for further clinical development. Cross-functional collaboration is essential to ensure efficient and successful FIH trials. The aim of this publication is to serve as a tutorial for conducting FIH trials for both small molecule and biological drug candidates with topics covering regulatory requirements, preclinical safety testing, study design considerations, safety monitoring, biomarker assessment, and global considerations. An emphasis is placed on FIH trial design considerations, including starting dose selection, study size and population, dose escalation scheme, and implementation of adaptive designs. In light of the recent revision of the European Medicines Agency (EMA) guideline on FIH trials to promote safety and mitigate risk, we also discuss new measures introduced in the guideline that impact FIH trial design.

Nanodelivery systems and stabilized solid-drug nanoparticles for orally administered medicine: current landscape

The use of nanoparticles as a means of targeted delivery of therapeutics and imaging agents could greatly enhance the transport of biologically active contents to specific target tissues, while avoiding or reducing potentially undesired side effects. Generally speaking, the oral route of administration is associated with good patient compliance, as it is convenient, economical, noninvasive, and does not require special training. Here, we review the progress of the utilization of nanodelivery-system carriers or stabilized solid-drug nanoparticles following oral administration, with particular attention on toxicological data. Mechanisms of cytotoxicity are discussed and the problem of extrapolating knowledge to human scenarios highlighted. Additionally, issues associated with administration of drugs via the oral route are underlined, while strategies utilized to overcome these are highlighted. This review aims to offer a balanced overview of strategies currently being used in the application of nanosize constructs for oral medical applications.

Development of a Dynamic Physiologically Based Mechanistic Kidney Model to Predict Renal Clearance

Renal clearance is usually predicted via empirical approaches including quantitative structure activity relationship and allometric scaling. Recently, mechanistic prediction approaches using in silico kidney models have been proposed. However, empirical scaling factors are typically used to adjust for either passive diffusion or active secretion, to acceptably predict renal clearances. The goal of this study was to establish a renal clearance simulation tool that allows prediction of renal clearance (filtration and pH-dependent passive reabsorption) from in vitro permeability data. A 35-compartment physiologically based mechanistic kidney model was developed based on human physiology. The model was verified using 46 test compounds, including neutrals, acids, bases, and zwitterions. The feasibility of incorporating active secretion and pH-dependent bidirectional passive diffusion into the model was demonstrated using para-aminohippuric acid (PAH), cimetidine, memantine, and salicylic acid. The developed model enables simulation of renal clearance from in vitro permeability data, with predicted renal clearance within twofold of observed for 87% of the test drugs.