Nonlinear pharmacokinetics of therapeutic proteins resulting from receptor mediated endocytosis

Integrated PK/PD Modeling Relates Smoothened Inhibitor Biomarkers to The Heterogeneous Intratumor Disposition of Cetuximab in Pancreatic Cancer Tumor Models

Therapeutic antibodies have shown little efficacy in the treatment of pancreatic ductal adenocarcinomas (PDAC). Tumor desmoplasia, hypovascularity, and poor perfusion result in insufficient tumor cell exposure, contributing to treatment failure. Smoothened inhibitors of hedgehog signaling (sHHi) increase PDAC tumor permeability, perfusion, and drug delivery, and provide a tool to develop a quantitative, mechanistic understanding as to how the temporal dynamics of tumor priming can impact intratumor distribution of monoclonal antibodies (mAb). A linked pharmacokinetic (PK)/pharmacodynamic (PD) model was developed to integrate the plasma and tumor PK of a sHHi priming agent with its effects upon downstream stromal biomarkers Gli1, hyaluronic acid, and interstitial fluid pressure in PDAC patient-derived xenograft (PDX) tumors. In parallel, in situ tumor concentrations of cetuximab (CTX: anti-epidermal growth factor receptor; EGFR) were quantified as a marker for tumor delivery of mAb or antibody-drug conjugates. A minimal, physiologically-based pharmacokinetic (mPBPK) model was constructed to link sHHi effects upon mechanistic effectors of tumor barrier compromise with the intratumor distribution of CTX, and CTX occupancy of EGFR in tumors. Integration of the mPBPK model of mAb deposition and intratumor distribution with the PK/PD model of tumor responses to priming not only identified physiological parameters that are critical for tumor antibody distribution, but also provides insight into dosing regimens that could achieve maximal tumor disposition of therapeutic antibodies under conditions of transient PDAC tumor permeability barrier compromise that mechanistically-diverse tumor priming strategies may achieve.

Preclinical InVivo Data Integrated in a Modeling Network Informs a Refined Clinical Strategy for a CD3 T-Cell Bispecific in Combination with Anti-PD-L1

TYRP1-TCB is a CD3 T-cell bispecific (CD3-TCB) antibody for the treatment of advanced melanoma. A tumor growth inhibition (TGI) model was developed using mouse xenograft data with TYRP1-TCB monotherapy or TYRP1-TCB plus anti-PD-L1 combination. The model was translated to humans to inform a refined clinical strategy. From xenograft mouse data, we estimated an EC₅₀ of 0.345 mg/L for TYRP1-TCB, close to what was observed in vitro using the same tumor cell line. The model showed that, though increasing the dose of TYRP1-TCB in monotherapy delays the time to tumor regrowth and promotes higher tumor cell killing, it also induces a faster rate of tumor regrowth. Combination with anti-PD-L1 extended the time to tumor regrowth by 25% while also decreasing the tumor regrowth rate by 69% compared to the same dose of TYRP1-TCB alone. The model translation to humans predicts that if patients' tumors were scanned every 6 weeks, only 46% of the monotherapy responders would be detected even at a TYRP1-TCB dose resulting in exposures above the EC₉₀. However, combination of TYRP1-TCB and anti-PD-L1 in the clinic is predicted to more than double the overall response rate (ORR), duration of response (DoR) and progression-free survival (PFS) compared to TYRP1-TCB monotherapy. As a result, it is highly recommended to consider development of CD3-TCBs as part of a combination therapy from the outset, without the need to escalate the CD3-TCB up to the Maximum Tolerated Dose (MTD) in monotherapy and without gating the combination only on RECIST-derived efficacy metrics.

An Extended Model Including Target Turnover, Ligand-Target Complex Kinetics, and Binding Properties to Describe Drug-Receptor Interactions

Since the beginning of this century, target-mediated drug disposition has become a central concept in modeling drug action in drug development. It combines a range of processes, such as turnover, protein binding, internalization, and non-specific elimination, and often serves as a nucleus of more complex pharmacokinetic models. It is simple enough to comprehend but complex enough to be able to describe a wide range of phenomena and data sets. However, the complexity comes at a price: many parameters. In this chapter, we present an overview of the temporal development of the compounds involved after different types of drug doses and offer convenient handles for dissecting data sets in a sophisticated manner in order to estimate the values of these parameters, such as rate constants and pertinent concentrations.

Non-human primates in the PKPD evaluation of biologics: Needs and options to reduce, refine, and replace. A BioSafe White Paper

Monoclonal antibodies (mAbs) deliver great benefits to patients with chronic and/or severe diseases thanks to their strong specificity to the therapeutic target. As a result of this specificity, non-human primates (NHP) are often the only preclinical species in which therapeutic antibodies cross-react with the target. Here, we highlight the value and limitations that NHP studies bring to the design of safe and efficient early clinical trials. Indeed, data generated in NHPs are integrated with in vitro information to predict the concentration/effect relationship in human, and therefore the doses to be tested in first-in-human trials. The similarities and differences in the systems defining the pharmacokinetics and pharmacodynamics (PKPD) of mAbs in NHP and human define the nature and the potential of the preclinical investigations performed in NHPs. Examples have been collated where the use of NHP was either pivotal to the design of the first-in-human trial or, inversely, led to the termination of a project prior to clinical development. The potential impact of immunogenicity on the results generated in NHPs is discussed. Strategies to optimize the use of NHPs for PKPD purposes include the addition of PD endpoints in safety assessment studies and the potential re-use of NHPs after non-terminal studies or cassette dosing several therapeutic agents of interest. Efforts are also made to reduce the use of NHPs in the industry through the use of in vitro systems, alternative in vivo models, and in silico approaches. In the case of prediction of ocular PK, the body of evidence gathered over the last two decades renders the use of NHPs obsolete. Expert perspectives, advantages, and pitfalls with these alternative approaches are shared in this review.

Estimating drug potency in the competitive target mediated drug disposition (TMDD) system when the endogenous ligand is included

Predictions for target engagement are often used to guide drug development. In particular, when selecting the recommended phase 2 dose of a drug that is very safe, and where good biomarkers for response may not exist (e.g. in immuno-oncology), a receptor occupancy prediction could even be the main determinant in justifying the approved dose, as was the case for atezolizumab. The underlying assumption in these models is that when the drug binds its target, it disrupts the interaction between the target and its endogenous ligand, thereby disrupting downstream signaling. However, the interaction between the target and its endogenous binding partner is almost never included in the model. In this work, we take a deeper look at the in vivo system where a drug binds to its target and disrupts the target's interaction with an endogenous ligand. We derive two simple steady state inhibition metrics (SSIMs) for the system, which provides intuition for when the competition between drug and endogenous ligand should be taken into account for guiding drug development.

Bioaccessibility and In Vitro Intestinal Permeability of a Recombinant Lectin from Tepary Bean (Phaseolus acutifolius) Using the Everted Intestine Assay

Tepary bean (Phaseolus acutifolius) lectins exhibit differential in vitro and in vivo biological effects, but their gastrointestinal interactions and digestion have not yet been assessed. This work aimed to evaluate the changes of a recombinant Tepary bean lectin (rTBL-1) through an in vitro and ex vivo gastrointestinal process. A polyclonal antibody was developed to selectively detect rTBL-1 by Western blot (WB) and immunohistochemical analysis. Everted gut sac viability was confirmed until 60 min, where protein bioaccessibility, apparent permeability coefficient, and efflux ratio showed rTBL-1 partial digestion and absorption. Immunoblot assays suggested rTBL-1 internalization, since the lectin was detected in the digestible fraction. The immunohistochemical assay detected rTBL-1 presence at the apical side of the small intestine, potentially due to the interaction with the intestinal cell membrane. The in silico interactions between rTBL-1 and some saccharides or derivatives showed high binding affinity to sialic acid (-6.70 kcal/mol) and N-acetylglucosamine (-6.10 kcal/mol). The ultra-high-performance liquid chromatography-electron spray ionization-quantitative time-of-flight coupled to mass spectrometry (UHPLC-ESI-QTOF/MS) analysis showed rTBL-1 presence in the gastric content and the non-digestible fraction after intestinal simulation conditions. The results indicated that rTBL-1 partially resisted the digestive conditions and interacted with the intestinal membrane, whereas its digestion allowed the absorption or internalization of the protein or the derivative peptides. Further purification of digestion samples should be conducted to identify intact rTBL-1 protein and digested peptides to assess their physiological effects.

Prediction of Human Pharmacokinetics and Clinical Effective Dose of SI-B001, an EGFR/HER3 Bi-specific Monoclonal Antibody

SI-B001 is a new EGFR/HER3 bi-specific antibody showing encouraging anti-tumor efficacy in the preclinical studies and was ready for further clinical research. To help with the dose design, human pharmacokinetics (PK) and clinical effective doses of SI-B001 were predicted by PK and PK/PD modeling and simulation. A Michaels-Menten (M-M) PK model was first used to describe the PK of SI-B001 in cynomolgus monkeys, whose parameters were allometrically scaled to humans for the simulation of human PK profiles. Besides, the anti-tumor efficacy of SI-B001 on different xenografts in tumor-bearing mice was quantitatively described by PK/PD models. The clinical effective doses were predicted by comparing the effective exposure (AUCs) in mice with simulated human AUCs. The clinical effective doses of SI-B001 were predicted to be over 16 mg/kg, 5-7 mg/kg or 5-6 mg/kg per week for colon cancer, head and neck cancer or esophageal cancer, respectively, which may help with the optimization of dose escalation schemes and the selection of indications for SI-B001.

Understanding Inter-Individual Variability in Monoclonal Antibody Disposition

Monoclonal antibodies (mAbs) are currently the largest and most dominant class of therapeutic proteins. Inter-individual variability has been observed for several mAbs; however, an understanding of the underlying mechanisms and factors contributing to inter-subject differences in mAb disposition is still lacking. In this review, we analyze the mechanisms of antibody disposition and the putative mechanistic determinants of inter-individual variability. Results from in vitro, preclinical, and clinical studies were reviewed evaluate the role of the neonatal Fc receptor and Fc gamma receptors (expression and polymorphism), target properties (expression, shedding, turnover, internalization, heterogeneity, polymorphism), and the influence of anti-drug antibodies. Particular attention is given to the influence of co-administered drugs and disease, and to the physiological relevance of covariates identified by population pharmacokinetic modeling, as determinants of variability in mAb pharmacokinetics.

A systems pharmacokinetic/pharmacodynamic model for concizumab to explore the potential of anti-TFPI recycling antibodies

Concizumab is a humanized monoclonal antibody in clinical investigation directed against membrane-bound and soluble tissue factor pathway inhibitor (mTFPI and sTFPI) for treatment of hemophilia. Concizumab displays a non-linear pharmacokinetic (PK) profile due to mTFPI-mediated endocytosis and necessitates a high dose and frequent dosing to suppress the abundant sTFPI, a negative regulator of coagulation. Recycling antibodies that can dissociate bound mTFPI/sTFPI in endosomes for degradation and rescue antibody from degradation have a potential in reducing the dose by extending antibody systemic persistence and sTFPI suppression. We developed a systems PK/pharmacodynamics (PD) model with nested endosome compartments to simulate the effect of decreased antibody binding to mTFPI/sTFPI in endosomes on antibody clearance and sTFPI suppression for exploring the potential of anti-TFPI recycling antibodies in reducing the dose. A dynamic model-building strategy was taken. A reduced PK/PD model without the endosome compartments was developed to optimize unknown target turnover parameters using concizumab PK data. The optimized parameters were then employed in the systems PK/PD model for simulations. The obtained systems PK/PD model adequately described the PK of concizumab in rabbits, monkeys, and humans and the PD in humans. The systems PK/PD model predicted that an anti-TFPI recycling antibody with a 100-fold higher mTFPI/sTFPI dissociation constant in endosomes than concizumab can extend sTFPI suppression from 12 days to 1 month. Thus, the systems PK/PD model provides a quantitative platform for guiding the engineering and translational development of anti-TFPI recycling antibodies.

Guiding dose selection of monoclonal antibodies using a new parameter (AFTIR) for characterizing ligand binding systems

Guiding the dose selection for monoclonal antibody oncology drugs is often done using methods for predicting the receptor occupancy of the drug in the tumor. In this manuscript, previous work on characterizing target inhibition at steady state using the AFIR metric (Stein and Ramakrishna in CPT Pharmacomet Syst Pharmacol 6(4):258-266, 2017) is extended to include a "target-tissue" compartment and the shedding of membrane-bound targets. A new potency metric average free tissue target to initial target ratio (AFTIR) at steady state is derived, and it depends on only four key quantities: the equilibrium binding constant, the fold-change in target expression at steady state after binding to drug, the biodistribution of target from circulation to target tissue, and the average drug concentration in circulation. The AFTIR metric is useful for guiding dose selection, for efficiently performing sensitivity analyses, and for building intuition for more complex target mediated drug disposition models. In particular, reducing the complex, physiological model to four key parameters needed to predict target inhibition helps to highlight specific parameters that are the most important to estimate in future experiments to guide drug development.

Improved oral bioavailability and therapeutic efficacy of erlotinib through molecular complexation with phospholipid

The current study was aimed to prepare a molecular complex of erlotinib (ERL) with phospholipid (PC) for enhancement of solubility and thus bioavailability, therapeutic efficacy and reducing the toxicity of erlotinib. Phospholipid complex of drug was prepared by solvent evaporation method and characterized by differential scanning calorimetry (DSC), Fourier transform infra-red spectroscopy (FT-IR), proton and phosphorus nuclear magnetic resonance spectroscopy (1H NMR and 31P NMR), powder X-ray diffraction (P-XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM), which all explained the interactions of two components, validating the complexation phenomenon. In silico study also supported the phase change and molecular interactions for the establishment of ERL-PC. Spherical shaped nanostructures with 183.37±28.61nm size, -19.52±6.94mV potential and 28.59±2.66% loading efficiency were formed following dispersion of ERL-PC in aqueous media. In vitro release study revealed the higher release of ERL-PC due to amorphization and solubilization of drug. Caco-2 cell uptake resulted in ∼2 fold higher uptake of ERL-PC than free drug. In vitro cell culture studies were performed using human pancreatic adenocarcinoma cell lines, which demonstrated the higher cytotoxicity and apoptosis in case of ERL-PC. In vivo pharmacokinetics also supported the in vitro observations and showed ∼1.7 fold higher bioavailability with ERL-PC than ERL. Finally, in vivo efficacy and toxicity studies explained the superiority of ERL-PC over the free drug. Based on the results, phospholipid complex appears to be a promising tool to enhance bioavailability, efficacy, cytotoxicity and safety of erlotinib.

Mathematical description of drug-target interactions: application to biologics that bind to targets with two binding sites

The emerging discipline of mathematical pharmacology occupies the space between advanced pharmacometrics and systems biology. A characteristic feature of the approach is application of advance mathematical methods to study the behavior of biological systems as described by mathematical (most often differential) equations. One of the early application of mathematical pharmacology (that was not called this name at the time) was formulation and investigation of the target-mediated drug disposition (TMDD) model and its approximations. The model was shown to be remarkably successful, not only in describing the observed data for drug-target interactions, but also in advancing the qualitative and quantitative understanding of those interactions and their role in pharmacokinetic and pharmacodynamic properties of biologics. The TMDD model in its original formulation describes the interaction of the drug that has one binding site with the target that also has only one binding site. Following the framework developed earlier for drugs with one-to-one binding, this work aims to describe a rigorous approach for working with similar systems and to apply it to drugs that bind to targets with two binding sites. The quasi-steady-state, quasi-equilibrium, irreversible binding, and Michaelis-Menten approximations of the model are also derived. These equations can be used, in particular, to predict concentrations of the partially bound target (RC). This could be clinically important if RC remains active and has slow internalization rate. In this case, introduction of the drug aimed to suppress target activity may lead to the opposite effect due to RC accumulation.

Impact of mathematical pharmacology on practice and theory: four case studies

Drug-discovery has become a complex discipline in which the amount of knowledge about human biology, physiology, and biochemistry have increased. In order to harness this complex body of knowledge mathematics can play a critical role, and has actually already been doing so. We demonstrate through four case studies, taken from previously published data and analyses, what we can gain from mathematical/analytical techniques when nonlinear concentration-time courses have to be transformed into their equilibrium concentration-response (target or complex) relationships and new structures of drug potency have to be deciphered; when pattern recognition needs to be carried out for an unconventional response-time dataset; when what-if? predictions beyond the observational concentration-time range need to be made; or when the behaviour of a semi-mechanistic model needs to be elucidated or challenged. These four examples are typical situations when standard approaches known to the general community of pharmacokineticists prove to be inadequate.

Capacity limits of asialoglycoprotein receptor-mediated liver targeting

The abundant cell surface asialoglycoprotein receptor (ASGPR) is a highly selective receptor found on hepatocytes that potentially can be exploited as a selective shuttle for delivery. Various nucleic acid therapeutics that bind ASGPR are already in clinical development, but this receptor-mediated delivery mechanism can be saturated, which will likely result in reduced selectivity for the liver and therefore increase the likelihood for systemic adverse effects. Therefore, when aiming to utilize this mechanism, it is important to optimize both the administration protocol and the molecular properties. We here present a study using a novel ASGPR-targeted antibody to estimate ASGPR expression, turnover and internalization rates in vivo in mice. Using pharmacokinetic data (intravenous and subcutaneous dosing) and an in-silico target-mediated drug disposition (TMDD) model, we estimate an ASGPR expression level of 1.8 million molecules per hepatocyte. The half-life of the degradation of the receptor was found to be equal to 15 hours and the formed ligand-receptor complex is internalized with a half-life of 5 days. A biodistribution study was performed and confirmed the accuracy of the TMDD model predictions. The kinetics of the ASGPR shows that saturation of the shuttle at therapeutic concentrations is possible; however, simulation allows the dosing schedule to be optimized. The developed TMDD model can be used to support the development of therapies that use the ASGPR as a shuttle into hepatocytes.

Exposure-Response Analysis of Necitumumab Efficacy in Squamous Non-Small Cell Lung Cancer Patients

We sought to describe the exposure-response relationship of necitumumab efficacy in squamous non-small cell lung cancer patients and evaluate intrinsic and extrinsic patient descriptors that may guide dosing. SQUIRE was a phase III study comparing necitumumab in combination with gemcitabine and cisplatin vs. gemcitabine and cisplatin alone in 1,014 patients. An integrated model for tumor size dynamics and overall survival was developed, where reduction in tumor size results in a decrease in survival hazard. The change in tumor size was characterized using linear growth and first-order shrinkage. Overall survival was described using a combination of a Weibull function and Gompertz function for the hazard, with dynamic tumor size being a predictor for the hazard. Although body weight resulted in higher clearance and lower exposure, simulations showed that an 800 mg flat dose provided optimal response regardless of body weight.

Impact of altered endogenous IgG on unspecific mAb clearance

Immunodeficient mice are crucial models to evaluate the efficacy of monoclonal antibodies (mAbs). When studying mAb pharmacokinetics (PK), protection from elimination by binding to the neonatal Fc receptor (FcRn) is known to be a major process influencing the unspecific clearance of endogenous and therapeutic IgG. The concentration of endogenous IgG in immunodeficient mice, however is reduced, and this effect on the FcRn protection mechanism and subsequently on unspecific mAb clearance is unknown, yet of great importance for the interpretation of mAb PK data. We used a PBPK modelling approach to elucidate the influence of altered endogenous IgG concentrations on unspecific mAb clearance. To this end, we used PK data in immunodeficient mice, i.e. nude and severe combined immunodeficiency mice. To avoid impact of target-mediated clearance processes, we focussed on mAbs without affinity to a target antigen in these mice. In addition, intravenous immunoglobulin (IVIG) data of immunocompetent mice was used to study the impact of increased total IgG concentrations on unspecific therapeutic antibody clearance. The unspecific clearance is linear, whenever therapeutic IgG concentrations, i.e. mAb and IVIG concentrations are lower than FcRn; it can be non-linear if therapeutic IgG concentrations are larger than FcRn and endogenous IgG concentrations (e.g., under IVIG therapy). Unspecific mAb clearance of immunodeficient mice is effectively linear (under mAb doses as typically used in human). Studying the impact of reduced endogenous IgG concentrations on unspecific mAb clearance is of great relevance for the extrapolation to clinical species, e.g., when predicting mAb PK in immunosuppressed cancer patients.

Target-mediated drug disposition with drug-drug interaction, Part I: single drug case in alternative formulations

Target-mediated drug disposition (TMDD) describes drug binding with high affinity to a target such as a receptor. In application TMDD models are often over-parameterized and quasi-equilibrium (QE) or quasi-steady state (QSS) approximations are essential to reduce the number of parameters. However, implementation of such approximations becomes difficult for TMDD models with drug-drug interaction (DDI) mechanisms. Hence, alternative but equivalent formulations are necessary for QE or QSS approximations. To introduce and develop such formulations, the single drug case is reanalyzed. This work opens the route for straightforward implementation of QE or QSS approximations of DDI TMDD models. The manuscript is the first part to introduce DDI TMDD models with QE or QSS approximations.

Diffusion and Uptake of Tobacco Mosaic Virus as Therapeutic Carrier in Tumor Tissue: Effect of Nanoparticle Aspect Ratio

Nanoparticle-based technologies, including platforms derived from plant viruses, hold great promise for targeting and delivering cancer therapeutics to solid tumors by overcoming dose-limiting toxicities associated with chemotherapies. A growing body of data indicates advantageous margination and penetration properties of high aspect-ratio nanoparticles, which enhance payload delivery, resulting in increased efficacy. Our lab has demonstrated that elongated rod-shaped and filamentous macromolecular nucleoprotein assemblies from plant viruses have higher tissue diffusion rates than spherical particles. In this study, we developed a mathematical model to quantify diffusion and uptake of tobacco mosaic virus (TMV) in a spheroid system approximating a capillary-free segment of a solid tumor. Model simulations predict TMV concentration distribution with time in a tumor spheroid for different sizes and cell densities. From simulations of TMV concentration distribution, we can quantify the effect of TMV aspect ratio (e.g., nanorod length-to-width) with and without cellular uptake by modulated surface chemistry. This theoretical analysis can be applied to other viral or nonviral delivery systems to complement the experimental development of the next generation of nanotherapeutics.

Pharmacokinetics and pharmacokinetic-pharmacodynamic relationships of monoclonal antibodies in children

Monoclonal antibodies (mAbs) constitute a therapeutically and economically important drug class with increasing use in both adult and paediatric patients. The rather complex pharmacokinetic and pharmacodynamic properties of mAbs have been extensively reviewed in adults. In children, however, limited information is currently available. This paper aims to comprehensively review published pharmacokinetic and pharmacokinetic-pharmacodynamic studies of mAbs in children. The current status of mAbs in the USA and in Europe is outlined, including a critical discussion of the dosing strategies of approved mAbs. The pharmacokinetic properties of mAbs in children are exhaustively summarised along with comparisons to reports in adults: for each pharmacokinetic process, we discuss the general principles and mechanisms of the pharmacokinetic/pharmacodynamic characteristics of mAbs, as well as key growth and maturational processes in children that might impact these characteristics. Throughout this review, considerable knowledge gaps are identified, especially regarding children-specific properties that influence pharmacokinetics, pharmacodynamics and immunogenicity. Furthermore, the large heterogeneity in the presentation of pharmacokinetic/pharmacodynamic data limited clinical inferences in many aspects of paediatric mAb therapy. Overall, further studies are needed to fully understand the impact of body size and maturational changes on drug exposure and response. To maximise future knowledge gain, we propose a 'Guideline for Best Practice' on how to report pharmacokinetic and pharmacokinetic-pharmacodynamic results from mAb studies in children which also facilitates comparisons. Finally, we advocate the use of more sophisticated modelling strategies (population analysis, physiology-based approaches) to appropriately characterise pharmacokinetic-pharmacodynamic relationships of mAbs and, thus, allow for a more rational use of mAb in the paediatric population.

A Role for Low Density Lipoprotein Receptor-Related Protein 1 in the Cellular Uptake of Tissue Plasminogen Activator in the Lungs

PURPOSE

To gain knowledge of lung clearance mechanisms of inhaled tissue plasminogen activator (tPA).

METHODS

Using an in vivo mouse model and ex vivo murine whole organ cell suspensions, we examined the capability of the lungs to utilize LRP1 receptor-mediated endocytosis (RME) for the uptake of exogenous tPA with and without an LRP1 inhibitor, receptor associated protein (RAP), and quantitatively compared it to the liver. We also used a novel imaging technique to assess the amount LRP1 in sections of mouse liver and lung.

RESULTS

Following intratracheal administration, tPA concentrations in the bronchoalveolar lavage fluid (BALF) declined over time following two-compartment pharmacokinetics suggestive of a RME clearance mechanism. Ex vivo studies showed that lung and liver cells are similarly capable of tPA uptake via LRP1 RME which was reduced by ~50% by RAP. The comparable lung and liver uptake of tPA is likely due to equivalent amounts of LRP1 of which there was an abundance in the alveolar epithelium.

CONCLUSIONS

Our findings indicate that LRP1 RME is a candidate clearance mechanism for inhaled tPA which has implications for the development of safe and effective dosing regimens of inhaled tPA for the treatment of plastic bronchitis and other fibrin-inflammatory airway diseases in which inhaled tPA may have utility.

A Tutorial on Target-Mediated Drug Disposition (TMDD) Models

Target-mediated drug disposition (TMDD) is the phenomenon in which a drug binds with high affinity to its pharmacological target site (such as a receptor) to such an extent that this affects its pharmacokinetic characteristics.1 The aim of this Tutorial is to provide an introductory guide to the mathematical aspects of TMDD models for pharmaceutical researchers. Examples of Berkeley Madonna2 code for some models discussed in this Tutorial are provided in the Supplementary Materials.

Quantitative measurement of the target-mediated internalization kinetics of biopharmaceuticals

PURPOSE

Measurement of internalization of biopharmaceuticals targeting cell surface proteins can greatly facilitate drug development. The objective of this study was to develop a reliable method for determination of internalization rate constant (kint) and to demonstrate its utility.

METHODS

This method utilized confocal imaging to record the internalization kinetics of fluorescence-tagged biopharmaceuticals in live-cells and a quantitative image-analysis algorithm for kint determination. Kint was incorporated into a pharmacokinetic-pharmacodynamic (PK-PD) model for simulation of the drug PK profiles, target occupancy and the displacement of endogenous ligand.

RESULTS

The method was highly sensitive, allowing kint determination in cells expressing as low as 5,000 receptors/cell, and was amenable to adherent and suspension cells. Its feasibility in a mixed cell population, such as whole blood, was also demonstrated. Accurate assessment of the kint was largely attributed to continuous monitoring of internalization in live cells, rapid confocal image acquisition and quantitative image-analysis algorithm. Translational PK-PD simulations demonstrated that kint is a major determinant of the drug PK profiles, target occupancy, and the displacement of endogenous ligand.

CONCLUSIONS

The developed method is robust for broad cell types. Reliable kint assessment can greatly expedite biopharmaceutical development by facilitating target evaluation, drug affinity goal setting, and clinical dose projection.

A review of mixed-effects models of tumor growth and effects of anticancer drug treatment used in population analysis

Population modeling of tumor size dynamics has recently emerged as an important tool in pharmacometric research. A series of new mixed-effects models have been reported recently, and we present herein a synthetic view of models with published mathematical equations aimed at describing the dynamics of tumor size in cancer patients following anticancer drug treatment. This selection of models will constitute the basis for the Drug Disease Model Resources (DDMoRe) repository for models on oncology.

Monoclonal antibody disposition: a simplified PBPK model and its implications for the derivation and interpretation of classical compartment models

The structure, interpretation and parameterization of classical compartment models as well as physiologically-based pharmacokinetic (PBPK) models for monoclonal antibody (mAb) disposition are very diverse, with no apparent consensus. In addition, there is a remarkable discrepancy between the simplicity of experimental plasma and tissue profiles and the complexity of published PBPK models. We present a simplified PBPK model based on an extravasation rate-limited tissue model with elimination potentially occurring from various tissues and plasma. Based on model reduction (lumping), we derive several classical compartment model structures that are consistent with the simplified PBPK model and experimental data. We show that a common interpretation of classical two-compartment models for mAb disposition-identifying the central compartment with the total plasma volume and the peripheral compartment with the interstitial space (or part of it)-is not consistent with current knowledge. Results are illustrated for the monoclonal antibodies 7E3 and T84.66 in mice.

Assessing the transport of receptor-mediated drug-delivery devices across cellular monolayers

Receptor-mediated endocytosis (RME) has been extensively studied as a method for augmenting the transport of therapeutic devices across monolayers. These devices range from simple ligand-therapeutic conjugates to complex ligand-nanocarrier systems. However, characterizing the uptake of these carriers typically relies on their comparisons to the native therapeutic, which provides no understanding of the ligand or cellular performance. To better understand the potential of the RME pathway, a model for monolayer transport was designed based on the endocytosis cycle of transferrin, a ligand often used in RME drug-delivery devices. This model established the correlation between apical receptor concentration and transport capability. Experimental studies confirmed this relationship, demonstrating an upper transport limit independent of the applied dose. This contrasts with the dose-proportional pathways that native therapeutics rely on for transport. Thus, the direct comparison of these two transport mechanisms can produce misleading results that change with arbitrarily chosen doses. Furthermore, transport potential was hindered by repeated use of the RME cycle. Future studies should base the success of this technology not on the performance of the therapeutic itself, but on the capabilities of the cell. Using receptor-binding studies, we were able to demonstrate how these capabilities can be predicted and potentially adopted for high-throughput screening methods.

Hyaluronic acid (HA) presentation as a tool to modulate and control the receptor-mediated uptake of HA-coated nanoparticles

The natural turnover of free hyaluronic acid (HA) is predominantly based on its CD44-mediated internalisation in leukocytes. In a phagocytic cell model (RAW 264.7 murine macrophages) we here provide conclusive evidence that this receptor-mediated mechanism endocytosis is responsible also of the uptake of materials where HA is used as a coating agent, in this case chitosan/triphosphate nanoparticles on whose surface HA is electrostatically adsorbed. Alginate-coated nanoparticles were used as a control and they appeared to undergo a qualitatively similar endocytic process, which was mediated by a different scavenging receptor yet to be identified. In this general picture, an important, modulating role appears to be played by how receptors can cluster around individual nanoparticles. The CD44 slow representation (24-48 h) enforces a limit in the amount of available HA internalisation receptors; therefore a higher affinity, and hence a higher degree of clustering, would yield a lower number of internalised nanoparticles. HA presentation can be varied by acting on nanoparticle structure/morphology, and our data suggest that a better presentation may be linked to both higher affinity and lower capacity/uptake rate. Paradoxically, this result would suggest that particles with a lower affinity for CD44 may allow a more efficient HA-mediated delivery of payloads.

Dynamics of target-mediated drug disposition: characteristic profiles and parameter identification

In this paper we present a mathematical analysis of the basic model for target mediated drug disposition (TMDD). Assuming high affinity of ligand to target, we give a qualitative characterisation of ligand versus time graphs for different dosing regimes and derive accurate analytic approximations of different phases in the temporal behaviour of the system. These approximations are used to estimate model parameters, give analytical approximations of such quantities as area under the ligand curve and clearance. We formulate conditions under which a suitably chosen Michaelis-Menten model provides a good approximation of the full TMDD-model over a specified time interval.

A guide to rational dosing of monoclonal antibodies

BACKGROUND AND OBJECTIVE

Dosing of therapeutic monoclonal antibodies (mAbs) is often based on body size, with the perception that body size-based dosing would reduce inter-subject variability in drug exposure. However, most mAbs are target specific with a relatively large therapeutic window and generally a small contribution of body size to pharmacokinetic variability. Therefore, the dosing paradigm for mAbs should be assessed in the context of these unique characteristics. The objective of this study was to review the current dosing strategy and to provide a scientific rationale for dosing of mAbs using a modelling and simulation approach.

METHODS

In this analysis, the body weight-based or body weight-independent (fixed) dosing regimens for mAbs were systematically evaluated. A generic two-compartment first-order elimination model was developed. Individual or population pharmacokinetic profiles were simulated as a function of the body weight effects on clearance (θ(BW_CL)) and on the central volume of distribution (θ(BW_V1)). The variability in exposure (the area under the serum concentration-time curve [AUC], trough serum concentration [C(min)] and peak serum concentration [C(max)]) was compared between body weight-based dosing and fixed dosing in the entire population. The deviation of exposure for light and heavy subjects from median body weight subjects was also measured. The simulation results were then evaluated with clinical pharmacokinetic characteristics of various mAbs that were given either by body weight-based dosing or by fixed dosing in the case study.

RESULTS

Results from this analysis demonstrated that exposure variability was dependent on the magnitude of the body weight effect on pharmacokinetics. In contrast to the conventional assumption, body weight-based dosing does not always offer advantages over fixed dosing in reducing exposure variability. In general, when the exponential functions of θ(BW_CL) and θ(BW_V1) in the population pharmacokinetic model are <0.5, fixed dosing results in less variability and less deviation than body weight-based dosing; when both θ(BW_CL) and θ(BW_V1) are >0.5, body weight-based dosing results in less variability and less deviation than fixed dosing. In the scenarios when either θ(BW_CL) or θ(BW_V1) is >0.5, the impact on exposure variability is different for each exposure measure. The case study demonstrated that most mAbs had little effect or a moderate body weight effect (θ(BW_CL) and θ(BW_V1) <0.5 or ∼0.5). The difference of variability in exposure between body weight-based and fixed dosing is generally less than 20% and the percentages of deviation for light and heavy subpopulations are less than 40%.

CONCLUSIONS

The analysis provided insights into the conditions under which either fixed or body weight-based dosing would be superior in reducing pharmacokinetic variability and exposure differences between light and heavy subjects across the population. The pharmacokinetic variability introduced by either dosing regimen is moderate relative to the variability generally observed in pharmacodynamics, efficacy and safety. Therefore, mAb dosing can be flexible. Given many practical advantages, fixed dosing is recommended to be the first option in first-in-human studies with mAbs. The dosing strategy in later stages of clinical development could then be determined based on combined knowledge of the body weight effect on pharmacokinetics, safety and efficacy from the early clinical trials.

Predicting the F(ab)-mediated effect of monoclonal antibodies in vivo by combining cell-level kinetic and pharmacokinetic modelling

Cell-level kinetic models for therapeutically relevant processes increasingly benefit the early stages of drug development. Later stages of the drug development processes, however, rely on pharmacokinetic compartment models while cell-level dynamics are typically neglected. We here present a systematic approach to integrate cell-level kinetic models and pharmacokinetic compartment models. Incorporating target dynamics into pharmacokinetic models is especially useful for the development of therapeutic antibodies because their effect and pharmacokinetics are inherently interdependent. The approach is illustrated by analysing the F(ab)-mediated inhibitory effect of therapeutic antibodies targeting the epidermal growth factor receptor. We build a multi-level model for anti-EGFR antibodies by combining a systems biology model with in vitro determined parameters and a pharmacokinetic model based on in vivo pharmacokinetic data. Using this model, we investigated in silico the impact of biochemical properties of anti-EGFR antibodies on their F(ab)-mediated inhibitory effect. The multi-level model suggests that the F(ab)-mediated inhibitory effect saturates with increasing drug-receptor affinity, thereby limiting the impact of increasing antibody affinity on improving the effect. This indicates that observed differences in the therapeutic effects of high affinity antibodies in the market and in clinical development may result mainly from Fc-mediated indirect mechanisms such as antibody-dependent cell cytotoxicity.

Pharmacokinetics of recombinant bifunctional fusion proteins

INTRODUCTION

The development of biotechnology has enabled the creation of various recombinant fusion proteins as a new class of biotherapeutics. The uniqueness of fusion proteins lies in their ability to fuse two or more protein domains, providing vast opportunities to generate novel combinations of functions. Pharmacokinetic (PK) studies, which are critical components in preclinical and clinical drug development, have not been fully explored for fusion proteins. The lack of general PK models and study guidelines has become a bottleneck for translation of fusion proteins from basic research to the clinic.

AREAS COVERED

This article reviews the current status of PK studies for fusion proteins, covering the processes that affect PK. According to their PK properties, a classification of fusion proteins is suggested along with examples from the clinic or under development. Current limitations and future perspectives for PK of fusion proteins are also discussed.

EXPERT OPINION

A PK model for bifunctional fusion proteins is presented to highlight the importance of mechanistic studies for a thorough understanding of the PK properties of fusion proteins. The model suggests investigating the receptor binding and subsequent intracellular disposition of individual domains, which can have dramatic impact on the PK of fusion proteins.

Population pharmacokinetic meta-analysis of denosumab in healthy subjects and postmenopausal women with osteopenia or osteoporosis

BACKGROUND AND OBJECTIVE

Inhibition of the receptor activator of nuclear factor κ-B ligand (RANKL) is a therapeutic target for treatment of bone disorders associated with increased bone resorption, such as osteoporosis. The objective of this analysis was to characterize the population pharmacokinetics of denosumab (AMG 162; Prolia®), a fully human IgG2 monoclonal antibody that binds to RANKL, in healthy subjects and postmenopausal women with osteopenia or osteoporosis.

METHODS

A total of 22944 serum free denosumab concentrations from 495 healthy subjects and 1069 postmenopausal women with osteopenia or osteoporosis were pooled. Denosumab was administered as either a single intravenous dose (n = 36), a single subcutaneous dose (n = 469) or multiple subcutaneous doses (n = 1059), ranging from 0.01 to 3 mg/kg (or 6-210 mg as fixed mass dosages), every 3 or 6 months for up to 48 months. An open, two-compartment pharmacokinetic model with a quasi-steady-state approximation of the target-mediated drug disposition model was used to describe denosumab pharmacokinetics, using NONMEM Version 7.1.0 software. Subcutaneous absorption was characterized by the first-order absorption rate constant (k(a)), with constant absolute bioavailability over the range of doses that were evaluated. Clearance and volume of distribution parameters were scaled by body weight, using a power model. Model evaluation was performed through visual predictive checks.

RESULTS

The subcutaneous bioavailability of denosumab was 64%, and the k(a) was 0.00883 h-1. The central volume of distribution and linear clearance were 2.49 L/66 kg and 3.06 mL/h/66 kg, respectively. The baseline RANKL level, quasi-steady-state constant and RANKL degradation rate were 614 ng/mL, 138 ng/mL and 0.00148 h-1, respectively. Between-subject variability in model parameters was moderate. A fixed dose of 60 mg provided RANKL inhibition similar to that achieved by equivalent body weight-based dosing. The effects of age and race on the area under the serum concentration-time curve of denosumab were less than 15% over the range of covariate values that were evaluated.

CONCLUSIONS

The non-linearity in denosumab pharmacokinetics is probably due to RANKL binding, and denosumab dose adjustment based on the patient demographics is not warranted.

Population pharmacokinetic meta-analysis of denosumab in healthy subjects and postmenopausal women with osteopenia or osteoporosis

BACKGROUND AND OBJECTIVE

Inhibition of the receptor activator of nuclear factor κ-B ligand (RANKL) is a therapeutic target for treatment of bone disorders associated with increased bone resorption, such as osteoporosis. The objective of this analysis was to characterize the population pharmacokinetics of denosumab (AMG 162; Prolia®), a fully human IgG2 monoclonal antibody that binds to RANKL, in healthy subjects and postmenopausal women with osteopenia or osteoporosis.

METHODS

A total of 22944 serum free denosumab concentrations from 495 healthy subjects and 1069 postmenopausal women with osteopenia or osteoporosis were pooled. Denosumab was administered as either a single intravenous dose (n = 36), a single subcutaneous dose (n = 469) or multiple subcutaneous doses (n = 1059), ranging from 0.01 to 3 mg/kg (or 6-210 mg as fixed mass dosages), every 3 or 6 months for up to 48 months. An open, two-compartment pharmacokinetic model with a quasi-steady-state approximation of the target-mediated drug disposition model was used to describe denosumab pharmacokinetics, using NONMEM Version 7.1.0 software. Subcutaneous absorption was characterized by the first-order absorption rate constant (k(a)), with constant absolute bioavailability over the range of doses that were evaluated. Clearance and volume of distribution parameters were scaled by body weight, using a power model. Model evaluation was performed through visual predictive checks.

RESULTS

The subcutaneous bioavailability of denosumab was 64%, and the k(a) was 0.00883 h-1. The central volume of distribution and linear clearance were 2.49 L/66 kg and 3.06 mL/h/66 kg, respectively. The baseline RANKL level, quasi-steady-state constant and RANKL degradation rate were 614 ng/mL, 138 ng/mL and 0.00148 h-1, respectively. Between-subject variability in model parameters was moderate. A fixed dose of 60 mg provided RANKL inhibition similar to that achieved by equivalent body weight-based dosing. The effects of age and race on the area under the serum concentration-time curve of denosumab were less than 15% over the range of covariate values that were evaluated.

CONCLUSIONS

The non-linearity in denosumab pharmacokinetics is probably due to RANKL binding, and denosumab dose adjustment based on the patient demographics is not warranted.

Mathematical analysis of the pharmacokinetic-pharmacodynamic (PKPD) behaviour of monoclonal antibodies: predicting in vivo potency

We consider the relationship between the target affinity of a monoclonal antibody and its in vivo potency. The dynamics of the system is described mathematically by a target-mediated drug disposition model. As a measure of potency, we consider the minimum level of the free receptor following a single bolus injection of the ligand into the plasma compartment. From the differential equations, we derive two expressions for this minimum level in terms of the parameters of the problem, one of which is valid over the full range of values of the equilibrium dissociation constant K(D) and the other which is valid only for a large drug dose or for a small value of K(D). Both of these formulae show that the potency achieved by increasing the association constant k(on) can be very different from the potency achieved by decreasing the dissociation constant k(off). In particular, there is a saturation effect when decreasing k(off) where the increase in potency that can be achieved is limited, whereas there is no such effect when increasing k(on). Thus, for certain monoclonal antibodies, an increase in potency may be better achieved by increasing k(on) than by decreasing k(off).

Target-mediated drug disposition model for drugs that bind to more than one target

Until recently, most therapeutic monoclonal antibodies (mAb) were designed to bind only one target. However, several existing mAbs bind to soluble and membrane forms of the same receptor. Moreover, design of bi-specific and multi-specific proteins that bind to more than one target is a promising direction of drug design. The pharmacokinetics and pharmacodynamics of these drugs may be described by the target-mediated drug disposition (TMDD). This work extended the TMDD model to drugs that bind more than one target. The quasi-steady-state (QSS) and Michaelis-Menten (MM) approximations of the model were also derived. Identifiability of model parameters was studied by simulations. The drug and target parameters used in simulations were chosen to imitate a monoclonal antibody that binds to the soluble (S) and membrane-bound (M) targets. The data were simulated for 224 subjects using the full TMDD model and dosing that mimicked typical Phase I and Phase II designs with rich sampling. Four population pharmacokinetic models were fitted to the free (unbound) drug and total (unbound and bound to the drug) S-target data: a one-target QSS model that simultaneously described the free drug and the total S-target (M1), a model with parallel linear and MM elimination that described the free drug combined with a separate S-target model that utilized the free drug concentrations but did not influence them (M2), a two-target QSS model where the S-target was described by the QSS approximation while the contribution of the M-target was described by the MM elimination term (M3), and a two-target full TMDD model (M4). The influence of relative contributions of the S and M-targets to target-mediated elimination on identifiability of the model parameters was investigated. The influence of assay sensitivity and availability of the total rather than free drug concentration measurements were also investigated. The results indicated that for the dosing regimens and system parameters investigated in this work the pharmacokinetic data alone did not allow to distinguish influences of the two targets. When the drug and S-target data were available, the model M1 described the data with the deficiencies of the fit visible only at the lowest dose level. However, the parameter estimates were strongly biased. The model M2 improved the fit and provided the precise estimates of the S-target parameters. However, no information concerning the M-target could be obtained from this model. The model M3 provided an excellent description of the data and the unbiased estimates of all the parameters. It also provided the unbiased estimates of change from baseline of the unobservable M-target concentrations. The models M1-M3 were robust while M4 was unstable despite the prohibitively long run time. The results were similar when the total rather than free drug was measured. The M-target parameters were estimated only when M-target elimination was at least comparable to S-target elimination. Improvement of the assay sensitivity has not resulted in marked improvement of the parameter estimates. In summary, for the cases investigated in this work the QSS approximation of the two-target TMDD model provided the unbiased and robust estimates of all the relevant TMDD parameters.

The minimum anticipated biological effect level (MABEL) for selection of first human dose in clinical trials with monoclonal antibodies

Dose selection for first-in-human (FIH) clinical trials with monoclonal antibodies (mAbs) is based on specifically designed preclinical pharmacology and toxicology studies, mechanistic ex vivo/in vitro investigations with human and animal cells and pharmacokinetic/pharmacodynamic (PK/PD) modeling approaches and requires a thorough understanding of the biology of the target and the relative binding and pharmacological activity of the mAb in animals and humans. These investigations provide the essential information required for the selection of a safe starting dose and escalation for FIH trials based on toxicology and pharmacology data and the minimal anticipated biological effect level (MABEL) by integrating all available in vivo and in vitro data. In this review, strategies for estimation of the MABEL for mAbs specific for both membrane and soluble targets are presented and the scientific and regulatory challenges highlighted.

Dynamics of target-mediated drug disposition

We present a mathematical analysis of the basic model underlying target-mediated drug disposition (TMDD) in which a ligand is supplied through an initial bolus or through a constant rate infusion and forms a complex with a receptor (target), which is supplied and removed continuously. Ligand and complex may be eliminated according to first-order processes. We assume that the total receptor pool (free and bound) is constant in time and we give a geometrical description of the evolution of the concentrations of ligand, receptor and receptor-ligand complex which offers a transparent way to compare the full model with simpler models such as the quasi-steady-state (QSS) model, the quasi-equilibrium (QE) model and the empirical Michaelis-Menten (MM) model; we also give precise conditions on the parameters in the TMDD model for the validity of these reduced models. We relate characteristic properties of time courses to parameter regimes and, in particular, we identify and explain non-monotone dependence of the time-to-steady-state on the infusion rate. Finally, we discuss how the volume of the central compartment may be overestimated because of singular initial behaviour of the time course of the ligand concentration.