Across-Species Scaling of Monoclonal Antibody Pharmacokinetics Using a Minimal PBPK Model

Sialic Acid Mediated Endothelial and Hepatic Uptake: A Mechanism based Mathematic Model Elucidating the Complex Pharmacokinetics and Pharmacodynamics of Efmarodocokin Alfa, a Variably Glycosylated Fusion Protein

Sialic acid (SA) is crucial for protecting glycoproteins from clearance. Efmarodocokin alfa (IL-22Fc), a fusion protein agonist that links IL-22 to the crystallizable fragment (Fc) of human IgG4, contains 8 N-glycosylation sites and exhibits heterogeneous and variable terminal sialylation biodistribution. This presents a unique challenge for Pharmacokinetic (PK) and Pharmacodynamic (PD) analysis and cross-species translation. In this study, we sought to understand how varying SA levels and heterogeneous distribution contribute to IL-22Fc's complex PKPD properties. We initially used homogenous drug material with varying SA levels to examine PKPD in mice. Population PKPD analysis based on mouse data revealed that SA was a critical covariate simultaneously accounting for the substantial between subject variability (BSV) in clearance (CL), distribution clearance (CLd), and volume of distribution (Vd). In addition to the well-established mechanism by which SA inhibits ASGPR activity, we hypothesized a novel mechanism by which decrease in SA increases the drug uptake by endothelial cells. This decrease in SA, leading to more endothelial uptake, was supported by the neonatal Fc receptor (FcRn) dependent cell-based transcytosis assay. The population analysis also suggested in vivo EC50 (IL-22Fc stimulating Reg3β) was independent on SA, while the in-vitro assay indicated a contradictory finding of SA-in vitro potency relationship. We created a mechanism based mathematical (MBM) PKPD model incorporating the decrease in SA mediated endothelial and hepatic uptake, and successfully characterized the SA influence on IL-22Fc PK, as well as the increased PK exposure being responsible for increased PD. Thereby, the MBM model supported that SA has no direct impact on EC50, aligning with the population PKPD analysis. Subsequently, using the MBM PKPD model, we employed 5 subpopulation simulations to reconstitute the heterogeneity of drug material. The simulation accurately predicted the PKPD of heterogeneously and variably sialylated drug in mouse, monkey and human. The successful prospective validation confirmed the MBM's ability to predict IL-22Fc PK across variable SA levels, homogenous to heterogeneous material, and across species (R2=0.964 for clearance prediction). Our model prediction suggests an average of 1 mol/mol SA increase leads to a 50% increase in drug exposure. This underlines the significance of controlling sialic acid levels during lot-to-lot manufacturing.

A Minimal PBPK/PD Model with Expansion-Enhanced Target-Mediated Drug Disposition to Support a First-in-Human Clinical Study Design for a FLT3L-Fc Molecule

FLT3L-Fc is a half-life extended, effectorless Fc-fusion of the native human FLT3-ligand. In cynomolgus monkeys, treatment with FLT3L-Fc leads to a complex pharmacokinetic/pharmacodynamic (PK/PD) relationship, with observed nonlinear PK and expansion of different immune cell types across different dose levels. A minimal physiologically based PK/PD model with expansion-enhanced target-mediated drug disposition (TMDD) was developed to integrate the molecule's mechanism of action, as well as the complex preclinical and clinical PK/PD data, to support the preclinical-to-clinical translation of FLT3L-Fc. In addition to the preclinical PK data of FLT3L-Fc in cynomolgus monkeys, clinical PK and PD data from other FLT3-agonist molecules (GS-3583 and CDX-301) were used to inform the model and project the expansion profiles of conventional DC1s (cDC1s) and total DCs in peripheral blood. This work constitutes an essential part of our model-informed drug development (MIDD) strategy for clinical development of FLT3L-Fc by projecting PK/PD in healthy volunteers, determining the first-in-human (FIH) dose, and informing the efficacious dose in clinical settings. Model-generated results were incorporated in regulatory filings to support the rationale for the FIH dose selection.

Investigating the synergistic effects of immunotherapy and normalization treatment in modulating tumor microenvironment and enhancing treatment efficacy

We developed a comprehensive mathematical model of cancer immunotherapy that takes into account: i) Immune checkpoint blockers (ICBs) and the interactions between cancer cells and the immune system, ii) characteristics of the tumor microenvironment, such as the tumor hydraulic conductivity, interstitial fluid pressure, and vascular permeability, iii) spatial and temporal variations of the modeled components within the tumor and the surrounding host tissue, iv) the transport of modeled components through the vasculature and between the tumor-host tissue with convection and diffusion, and v) modeling of the tumor draining lymph nodes were the antigen presentation and the development of cytotoxic immune cells take place. Our model successfully reproduced experimental data from various murine tumor types and predicted immune system profiling, which is challenging to achieve experimentally. It showed that combination of ICB therapy and normalization treatments, that aim to improve tumor perfusion, decreases interstitial fluid pressure and increases the concentration of both innate and adaptive immune cells at the tumor center rather than the periphery. Furthermore, using the model, we investigated the impact of modeled components on treatment outcomes. The analysis found that the number of functional vessels inside the tumor region and the ICB dose administered have the largest impact on treatment outcomes.

Kinetic modeling of the plasma pharmacokinetic profiles of ADAMTS13 fragment and its Fc-fusion counterpart in mice

Introduction: Fusion of the fragment crystallizable (Fc) to protein therapeutics is commonly used to extend the circulation time by enhancing neonatal Fc-receptor (FcRn)-mediated endosomal recycling and slowing renal clearance. This study applied kinetic modeling to gain insights into the cellular processing contributing to the observed pharmacokinetic (PK) differences between the novel recombinant ADAMTS13 fragment (MDTCS) and its Fc-fusion protein (MDTCS-Fc). Methods: For MDTCS and MDTCS-Fc, their plasma PK profiles were obtained at two dose levels following intravenous administration of the respective proteins to mice. The plasma PK profiles of MDTCS were fitted to a kinetic model with three unknown protein-dependent parameters representing the fraction recycled (FR) and the rate constants for endocytosis (kup, for the uptake into the endosomes) and for the transfer from the plasma to the interstitial fluid (kpi). For MDTCS-Fc, the model was modified to include an additional parameter for binding to FcRn. Parameter optimization was done using the Cluster Gauss-Newton Method (CGNM), an algorithm that identifies multiple sets of approximate solutions ("accepted" parameter sets) to nonlinear least-squares problems. Results: As expected, the kinetic modeling results yielded the FR of MDTCS-Fc to be 2.8-fold greater than that of MDTCS (0.8497 and 0.3061, respectively). In addition, MDTCS-Fc was predicted to undergo endocytosis (the uptake into the endosomes) at a slower rate than MDTCS. Sensitivity analyses identified the association rate constant (kon) between MDTCS-Fc and FcRn as a potentially important factor influencing the plasma half-life in vivo. Discussion: Our analyses suggested that Fc fusion to MDTCS leads to changes in not only the FR but also the uptake into the endosomes, impacting the systemic plasma PK profiles. These findings may be used to develop recombinant protein therapeutics with extended circulation time.

Expansion of platform physiologically-based pharmacokinetic model for monoclonal antibodies towards different preclinical species: cats, sheep, and dogs

Monoclonal antibodies (mAbs) are becoming an important therapeutic option in veterinary medicine, and understanding the pharmacokinetic (PK) of mAbs in higher-order animal species is also important for human drug development. To better understand the PK of mAbs in these animals, here we have expanded a platform physiological-based pharmacokinetic (PBPK) model to characterize the disposition of mAbs in three different preclinical species: cats, sheep, and dogs. We obtained PK data for mAbs and physiological parameters for the three different species from the literature. We were able to describe the PK of mAbs following intravenous (IV) or subcutaneous administration in cats, IV administration in sheep, and IV administration dogs reasonably well by fixing the physiological parameters and just estimating the parameters related to the binding of mAbs to the neonatal Fc receptor. The platform PBPK model presented here provides a quantitative tool to predict the plasma PK of mAbs in dogs, cats, and sheep. The model can also predict mAb PK in different tissues where the site of action might be located. As such, the mAb PBPK model presented here can facilitate the discovery, development, and preclinical-to-clinical translation of mAbs for veterinary and human medicine. The model can also be modified in the future to account for more detailed compartments for certain organs, different pathophysiology in the animals, and target-mediated drug disposition.

Utility of Minimal Physiologically Based Pharmacokinetic Models for Assessing Fractional Distribution, Oral Absorption, and Series-Compartment Models of Hepatic Clearance

Minimal physiologically based pharmacokinetic (mPBPK) models are physiologically relevant, require less information than full PBPK models, and offer flexibility in pharmacokinetics (PK). The well-stirred hepatic model (WSM) is commonly used in PBPK, whereas the more plausible dispersion model (DM) poses computational complexities. The series-compartment model (SCM) mimics the DM but is easier to operate. This work implements the SCM and mPBPK models for assessing fractional tissue distribution, oral absorption, and hepatic clearance using literature-reported blood and liver concentration-time data in rats for compounds mainly cleared by the liver. Further handled were various complexities, including nonlinear hepatic binding and metabolism, differing absorption kinetics, and sites of administration. The SCM containing one to five (n) liver subcompartments yields similar fittings and provides comparable estimates for hepatic extraction ratio (ER), prehepatic availability (Fg ), and first-order absorption rate constants (ka ). However, they produce decreased intrinsic clearances (CLint ) and liver-to-plasma partition coefficients (Kph ) with increasing n as expected. Model simulations demonstrated changes in intravenous and oral PK profiles with alterations in Kph and ka and with hepatic metabolic zonation. The permeability (PAMPA P) of the various compounds well explained the fitted fractional distribution (fd ) parameters. The SCM and mPBPK models offer advantages in distinguishing systemic, extrahepatic, and hepatic clearances. The SCM allows for incorporation of liver zonation and is useful in assessing changes in internal concentration gradients potentially masked by similar blood PK profiles. Improved assessment of intraorgan drug concentrations may offer insights into active moieties driving metabolism, biliary excretion, pharmacodynamics, and hepatic toxicity. SIGNIFICANCE STATEMENT: The minimal physiologically based pharmacokinetic model and the series-compartment model are useful in assessing oral absorption and hepatic clearance. They add flexibility in accounting for various drug- or system-specific complexities, including fractional distribution, nonlinear binding and saturable hepatic metabolism, and hepatic zonation. These models can offer improved insights into the intraorgan concentrations that reflect physiologically active moieties often driving disposition, pharmacodynamics, and toxicity.

Application of Modelling and Simulation Approaches to Predict Pharmacokinetics of Therapeutic Monoclonal Antibodies in Pediatric Population

Ethical regulations and limited paediatric participants are key challenges that contribute to a median delay of 6 years in paediatric mAb approval. To overcome these barriers, modelling and simulation methodologies have been adopted to design optimized paediatric clinical studies and reduce patient burden. The classical modelling approach in paediatric pharmacokinetic studies for regulatory submissions is to apply body weight-based or body surface area-based allometric scaling to adult PK parameters derived from a popPK model to inform the paediatric dosing regimen. However, this approach is limited in its ability to account for the rapidly changing physiology in paediatrics, especially in younger infants. To overcome this limitation, PBPK modelling, which accounts for the ontogeny of key physiological processes in paediatrics, is emerging as an alternative modelling strategy. While only a few mAb PBPK models have been published, PBPK modelling shows great promise demonstrating a similar prediction accuracy to popPK modelling in an Infliximab paediatric case study. To facilitate future PBPK studies, this review consolidated comprehensive data on the ontogeny of key physiological processes in paediatric mAb disposition. To conclude, this review discussed different use-cases for pop-PK and PBPK modelling and how they can complement each other to increase confidence in pharmacokinetic predictions.

Complex PK-PD of an engineered IL-15/IL-15Rα-Fc fusion protein in cynomolgus monkeys: QSP modeling of lymphocyte dynamics

XmAb24306 is a lymphoproliferative interleukin (IL)-15/IL-15 receptor α (IL-15Rα) Fc-fusion protein currently under clinical investigation as an immunotherapeutic agent for cancer treatment. XmAb24306 contains mutations in IL-15 that attenuate its affinity to the heterodimeric IL-15 receptor βγ (IL-15R). We observe substantially prolonged pharmacokinetics (PK) (half-life ∼ 2.5 to 4.5 days) in single- and repeat-dose cynomolgus monkey (cyno) studies compared to wild-type IL-15 (half-life ∼ 1 hour), leading to increased exposure and enhanced and durable expansion of NK cells, CD8+ T cells and CD4-CD8- (double negative [DN]) T cells. Drug clearance varied with dose level and time post-dose, and PK exposure decreased upon repeated dosing, which we attribute to increased target-mediated drug disposition (TMDD) resulting from drug-induced lymphocyte expansion (i.e., pharmacodynamic (PD)-enhanced TMDD). We developed a quantitative systems pharmacology (QSP) model to quantify the complex PKPD behaviors due to the interactions of XmAb24306 with multiple cell types (CD8+, CD4+, DN T cells, and NK cells) in the peripheral blood (PB) and lymphoid tissues. The model, which includes nonspecific drug clearance, binding to and TMDD by IL15R differentially expressed on lymphocyte subsets, and resultant lymphocyte margination/migration out of PB, expansion in lymphoid tissues, and redistribution to the blood, successfully describes the systemic PK and lymphocyte kinetics observed in the cyno studies. Results suggest that after 3 doses of every-two-week (Q2W) doses up to 70 days, the relative contributions of each elimination pathway to XmAb24306 clearance are: DN T cells > NK cells > CD8+ T cells > nonspecific clearance > CD4+ T cells. Modeling suggests that observed cellular expansion in blood results from the influx of cells expanded by the drug in lymphoid tissues. The model is used to predict lymphoid tissue expansion and to simulate PK-PD for different dose regimens. Thus, the model provides insight into the mechanisms underlying the observed PK-PD behavior of an engineered cytokine and can serve as a framework for the rapid integration and analysis of data that emerges from ongoing clinical studies in cancer patients as single-agent or given in combination.

Pharmacokinetics of antibodies during pregnancy: General pharmacokinetics and pregnancy related physiological changes (Part 1)

Pharmacokinetics (PK) studies are important to determine a safe and effective dose of both small and large molecule drugs. Intrinsic factors such as pregnancy can substantially alter the PK of a drug. Several PK studies have been published for small molecules administered during pregnancy, but such investigations are scarce for macromolecules including monoclonal and polyclonal antibodies. In this part 1 of 2 reviews, we first provide a general description of macromolecule drugs, the PK differences with small molecules, and current knowledge on their absorption, distribution, metabolism and elimination in non-pregnant subjects. We then review in detail the physiological changes during pregnancy. While some of the physiologic adaptions of pregnancy, for example increased plasma volume and cardiac output, are expected to impact PK of antibody therapeutics, the effects of others, such as increased GFR and altered immune responses are not fully understood. We conclude that further investigations are needed to fully elucidate how pregnancy can impact PK properties of macromolecules.

Development and application of a simple pharmacokinetic model that quantitatively describes the distribution and elimination of the commonly measured proteins

Increased plasma concentrations of a variety of cellular enzymes (alanine transaminase, aspartate aminotransferase, alkaline phosphatase, amylase, etc.) are commonly used as routine screening tests for a range of conditions. An increased concentration usually is assumed to result from an increased rate of delivery to the plasma. Factors such as decreased metabolism or excretion or altered extravascular distribution usually are ignored. As a prelude to a detailed analysis of all the factors producing altered plasma enzyme levels, we have reviewed the relevant literature describing the pharmacokinetics (PK) of 13 of the commonly measured plasma proteins and developed a PK model that provides a simple physiological description of all the data. Our model starts with the general 3-compartment, 6-parameter system previously developed for albumin and interprets the fluxes in terms of unidirectional sieved protein convectional volume flows from the plasma to the two tissue compartments and equal lymph flows returning to the plasma. This greatly constrains the model such that each protein is characterized by only two adjustable parameters (plasma clearance and sieving factor). In addition to accurately fitting the plasma kinetics, the model can accurately describe the tissue and lymph protein PK. For example, it can describe the thoracic duct lymph protein concentration following an intravenous infusion or the plasma concentration following a subcutaneous tissue injection. This simple model provides a satisfactory framework for the PK of 12 of the 13 proteins investigated. The glycoprotein intestinal alkaline phosphatase is the exception, requiring the addition of a liver recycling compartment involving the asialoglycoprotein receptor.

Review of the Existing Translational Pharmacokinetics Modeling Approaches Specific to Monoclonal Antibodies (mAbs) to Support the First-In-Human (FIH) Dose Selection

The interest in therapeutic monoclonal antibodies (mAbs) has continuously growing in several diseases. However, their pharmacokinetics (PK) is complex due to their target-mediated drug disposition (TMDD) profiles which can induce a non-linear PK. This point is particularly challenging during the pre-clinical and translational development of a new mAb. This article reviews and describes the existing PK modeling approaches used to translate the mAbs PK from animal to human for intravenous (IV) and subcutaneous (SC) administration routes. Several approaches are presented, from the most empirical models to full physiologically based pharmacokinetic (PBPK) models, with a focus on the population PK methods (compartmental and minimal PBPK models). They include the translational approaches for the linear part of the PK and the TMDD mechanism of mAbs. The objective of this article is to provide an up-to-date overview and future perspectives of the translational PK approaches for mAbs during a model-informed drug development (MIDD), since the field of PK modeling has gained recently significant interest for guiding mAbs drug development.

Application of physiologically-based pharmacokinetic models for therapeutic proteins and other novel modalities

The past two decades have seen diversification of drug development pipelines and approvals from traditional small molecule therapies to alternative modalities including monoclonal antibodies, engineered proteins, antibody drug conjugates (ADCs), oligonucleotides and gene therapies. At the same time, physiologically-based pharmacokinetic (PBPK) models for small molecules have seen increased industry and regulatory acceptance.This review focusses on the current status of the application of PBPK models to these newer modalities and give a perspective on the successes, challenges and future directions of this field.There is greatest experience in the development of PBPK models for therapeutic proteins, and PBPK models for ADCs benefit from prior experience for both therapeutic proteins and small molecules. For other modalities, the application of PBPK models is in its infancy.Challenges are discussed and a common theme is lack of availability of physiological and experimental data to characterise systems and drug parameters to enable a priori prediction of pharmacokinetics. Furthermore, sufficient clinical data are required to build confidence in developed models.The PBPK modelling approach provides a quantitative framework for integrating knowledge and data from multiple sources and can be built on as more data becomes available.

Mathematical Models to Characterize the Absorption, Distribution, Metabolism, and Excretion of Protein Therapeutics

Therapeutic proteins (TPs) have ranked among the most important and fastest-growing classes of drugs in the clinic, yet the development of successful TPs is often limited by unsatisfactory efficacy. Understanding pharmacokinetic (PK) characteristics of TPs is key to achieving sufficient and prolonged exposure at the site of action, which is a prerequisite for eliciting desired pharmacological effects. PK modeling represents a powerful tool to investigate factors governing in vivo disposition of TPs. In this mini-review, we discuss many state-of-the-art models that recapitulate critical processes in each of the absorption, distribution, metabolism/catabolism, and excretion pathways of TPs, which can be integrated into the physiologically-based pharmacokinetic framework. Additionally, we provide our perspectives on current opportunities and challenges for evolving the PK models to accelerate the discovery and development of safe and efficacious TPs. SIGNIFICANCE STATEMENT: This minireview provides an overview of mechanistic pharmacokinetic (PK) models developed to characterize absorption, distribution, metabolism, and elimination (ADME) properties of therapeutic proteins (TPs), which can support model-informed discovery and development of TPs. As the next-generation of TPs with diverse physicochemical properties and mechanism-of-action are being developed rapidly, there is an urgent need to better understand the determinants for the ADME of TPs and evolve existing platform PK models to facilitate successful bench-to-bedside translation of these promising drug molecules.

Development of New Strategies for Malaria Chemoprophylaxis: From Monoclonal Antibodies to Long-Acting Injectable Drugs

Drug discovery for malaria has traditionally focused on orally available drugs that kill the abundant, parasitic blood stage. Recently, there has also been an interest in injectable medicines, in the form of monoclonal antibodies (mAbs) with long-lasting plasma half-lives or long-lasting depot formulations of small molecules. These could act as prophylactic drugs, targeting the sporozoites and other earlier parasitic stages in the liver, when the parasites are less numerous, or as another intervention strategy targeting the formation of infectious gametocytes. Generally speaking, the development of mAbs is less risky (costly) than small-molecule drugs, and they have an excellent safety profile with few or no off-target effects. Therefore, populations who are the most vulnerable to malaria, i.e., pregnant women and young children would have access to such new treatments much faster than is presently the case for new antimalarials. An analysis of mAbs that were successfully developed for oncology illustrates some of the feasibility aspects, and their potential as affordable drugs in low- and middle-income countries.

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.

Pharmacokinetic/pharmacodynamic modeling for dose selection for the first-in-human trial of the activated Factor XII inhibitor garadacimab (CSL312)

Factor XII (FXII) is a serine protease involved in multiple cascades, including the kallikrein–kinin system. It may play a role in diseases in which the downstream cascades are dysregulated, such as hereditary angioedema. Garadacimab (CSL312) is a first‐in‐class, fully human, monoclonal antibody targeting activated FXII (FXIIa). We describe how translational pharmacokinetic (PK) and pharmacodynamic (PD) modeling enabled dose selection for the phase I, first‐in‐human trial of garadacimab. The PK/PD data used for modeling were derived from preclinical PK/PD and safety studies. Garadacimab plasma concentrations rose with increasing dose, and clear dose‐related PD effects were observed (e.g., a mechanism‐based prolongation of activated partial thromboplastin time). The PK/PD profile from cynomolgus monkeys was used to generate minimal physiologically‐based pharmacokinetic (mPBPK) models with target‐mediated drug disposition (TMDD) for data prediction in cynomolgus monkeys. These models were later adapted for prediction of human data to establish dose selection. Based on the final mPBPK model with TMDD and assuming a weight of 70 kg for an adult human, a minimal inhibition (<10%) of FXIIa with a starting dose of 0.1 mg/kg garadacimab and a near maximal inhibition (>95%) at 10 mg/kg garadacimab were predicted. The phase I study is complete, and data on exposure profiles and inhibition of FXIIa‐mediated kallikrein activity observed in the trial support and validate these simulations. This emphasizes the utility and relevance of translational modeling and simulation in drug development.

A Single Animal Species-Based Prediction of Human Clearance and First-in-Human Dose of Monoclonal Antibodies: Beyond Monkey

These days, there is a lot of emphasis on the prediction of human clearance (CL) from a single species for monoclonal antibodies (mabs). Many studies indicate that monkey is the most suitable species for the prediction of human clearance for mabs. However, it is not well established if rodents (mouse or rat) can also be used to predict human CL for mabs. The objectives of this study were to predict and compare human CL as well as first-in-human dose of mabs from mouse or rat, ormonkey. Four methods were used for the prediction of human CL of mabs. These methods were: use of four allometric exponents (0.75, 0.80, 0.85, and 0.90), a minimal physiologically based pharmacokinetics method (mPBPK), lymph flow rate, and liver blood flow rate. Based on the predicted CL, first-in-human dose of mabs was projected using either exponent 1.0 (linear scaling) or exponent 0.85, and human-equivalent dose (HED) from each of these species. The results of the study indicated that rat or mouse could provide a reasonably accurate prediction of human CL as well as first-in-human dose of mabs. When exponent 0.85 was used for CL prediction, there were 78%, 95%, and 92% observations within a 2-fold prediction error for mouse, rat, and monkey, respectively. Predicted human dose fell within the observed human dose range (administered to humans) for 10 out of 13 mabs for mouse, 11 out of 12 mabs for rat, and 12 out of 15 mabs for monkey. Overall, the clearance and first-in-human dose of mabs were predicted reasonably well by all three species (a single species). On average, monkey may be the best species for the prediction of human clearance and human dose but mouse or rat especially; rat can be a very useful species for conducting the aforementioned studies.

Analyze impact of tumor-associated kinetics on antibody delivery in solid tumors with a physiologically based pharmacokinetics/pharmacodynamics model

Monoclonal antibody (mAb)-based drugs are critical anti-cancer therapies. Unfortunately, therapeutic efficacy can be compromised by spatially heterogeneous intratumoral Ab deposition. Binding-site barriers arising from Ab and tumor-associated kinetics often underlie this phenomenon. Quantitative insight into these issues may lead to more efficient drug delivery. Difficulties in addressing this issue include (1) lack of techniques to quantify critical kinetic events, (2) lack of a pharmacokinetic/pharmacodynamic (PK/PD) model to assess important parameters for specific tumor types, and (3) uncertainty or variability of critical kinetic factors even within a single tumor type. This study developed a mechanism-based PK/PD model to profile heterogeneous distribution of Ab within tumors and tested this model using real-life experimental data. Model simulations incorporating several uncertainties were used to determine how mAb and tumor-associated kinetics influence receptor occupancy. Simulations were also used to predict the potential impact of these findings in preclinical tumor models and human tumors. We found significant differences in tumor-associated kinetics between groups in which mAb therapy was effective versus groups in which it was ineffective. These kinetic differences included rates of tumor-associated antigen (TAA) degradation, TAA expression, apparent flow rates of interstitial fluid, and ratios of Ab-TAA complex internalization to TAA degradation. We found less significant differences in mAb kinetics, including rates of clearance or affinity for target antigens. In conclusion, our mechanism-based PK/PD model suggests that TAA-associated kinetic factors participate more significantly than those associated with the Ab in generating barriers to mAb delivery and distribution in tumors.

A minimal physiologically based pharmacokinetic model to characterize colon TNF suppression and treatment effects of an anti-TNF monoclonal antibody in a mouse inflammatory bowel disease model

Biotherapeutic drugs against tumor necrosis factor (TNF) are effective treatments for moderate to severe inflammatory bowel disease (IBD). Here, we evaluated CNTO 5048, an antimurine TNF surrogate monoclonal antibody (mAb), in a CD45RB^high adoptive T cell transfer mouse colitis model, which allows examination of the early immunological events associated with gut inflammation and the therapeutic effects. The study was designed to quantitatively understand the effects of IBD on CNTO 5048 disposition, the ability of CNTO 5048 to neutralize pathogenic TNF at the colon under disease conditions, and the impact of dosing regimen on CNTO 5048 treatment effect. CNTO 5048 and TNF concentrations in both mice serum and colon homogenate were also measured. Free TNF concentrations in colon, but not in serum, were shown to correlate well with the colon pharmacodynamic readout, such as the summed histopathology score and neutrophil score. A minimal physiologically based pharmacokinetic (mPBPK) model was developed to characterize CNTO 5048 PK and disposition, as well as colon soluble TNF target engagement (TE). The mPBPK/TE model reasonably captured the observed data and provided a quantitative understanding of an anti-TNF mAb on its colon TNF suppression and therapeutic effect in a physiologically relevant IBD animal model. These results also provided insights into the potential benefits of using induction doses for the treatment of IBD patients.

Spreadsheet-Based Minimal Physiological Models for the Prediction of Clearance of Therapeutic Proteins in Pediatric Patients

There is a growing interest in the use of physiologically based pharmacokinetic (PBPK) models as clinical pharmacology drug development tools. In PBPK modeling, not every organ or physiological parameter is required, leading to the development of a minimal PBPK (mPBPK) model, which is simple and efficient. The objective of this study was to streamline mPBPK modeling approaches and enable straightforward prediction of clearance of protein-based products in children. Four mPBPK models for scaling clearance from adult to children were developed and evaluated on Excel spreadsheets using (1) liver and kidneys; (2) liver, kidneys, and skin; (3) liver, kidneys, skin, and lymph; and (4) interstitial, lymph, and plasma volume. There were 35 therapeutic proteins with a total of 113 observations across different age groups (premature neonates to adolescents). For monoclonal and polyclonal antibodies, more than 90% of observations were within a 0.5- to 2-fold prediction error for all 4 methods. For nonantibodies, 79% to 100% of observations were within the 0.5- to 2-fold prediction error for the 4 different methods. Methods 1 and 4 provided the best results, >90% of the total observations were within the 0.5- to 2-fold prediction error for all 3 classes of protein-based products across a wide age range. The precision of clearance prediction was comparatively lower in children ≤2 years of age vs older children (>2 years of age) with methods 1 and 4 predicting 80% to 100% and 75% to 90% of observations within the 0.5- to 2-fold prediction error, respectively. The results of the study indicated that mPBPK models can be developed on spreadsheets, with acceptable performance for prediction of clearance.

Comparison of Various Approaches to Translate Non-Linear Pharmacokinetics of Monoclonal Antibodies from Cynomolgus Monkey to Human

BACKGROUND AND OBJECTIVES

The prediction of pharmacokinetics of monoclonal antibodies (mAbs) exhibiting non-linear pharmacokinetics in preclinical species to human is challenging, and very limited scientific work has been published in this field of research. Therefore, we have conducted an elaborate comparative assessment to determine the most reliable preclinical to clinical scaling strategy for mAbs with non-linear pharmacokinetics.

METHODS

We have compared three different scaling approaches to predict human pharmacokinetics from cynomolgus monkey. In the first approach, cynomolgus monkey pharmacokinetic parameters estimated using a two-compartment model with parallel linear and non-linear elimination were allometrically scaled to simulate human pharmacokinetics. In the second approach, allometric exponents were integrated with a minimal physiologically based pharmacokinetic (mPBPK) model to translate human pharmacokinetics. In the third approach, we have employed a species time-invariant method, wherein a two-compartment model with parallel linear and non-linear elimination was used as a framework model for simulation of the human profile.

RESULTS

Human exposure parameters projected by an integrated allometric method were only within two fold for approximately 45-70% of predictions at different doses of five mAbs evaluated, while approximately 70-80% of Cmax and AUC predictions by integrated mPBPK modelling as well as the species time-invariant method were within two-fold error. The average fold error for clearance predictions by the integrated mPBPK method was 1.10-1.45 fold, whilst for the species time-variant and integrated allometric methods, the average fold error was between 1.04 and 1.37 fold and 1.24 and 2.13 fold, respectively.

CONCLUSIONS

Our findings suggest that the species time-variant method and mPBPK proposed by us can be employed to reliably translate non-linear pharmacokinetics of mAbs from cynomolgus monkey to human.

Meta-Assessment of Metformin Absorption and Disposition Pharmacokinetics in Nine Species

The objective of this study was to systematically assess literature datasets and quantitatively analyze metformin PK in plasma and some tissues of nine species. The pharmacokinetic (PK) parameters and profiles of metformin in nine species were collected from the literature. Based on a simple allometric scaling, the systemic clearances (CL) of metformin in these species highly correlate with body weight (BW) (R2 = 0.85) and are comparable to renal plasma flow in most species except for rabbit and cat. Reported volumes of distribution (VSS) varied appreciably (0.32 to 10.1 L/kg) among species. Using the physiological and anatomical variables for each species, a minimal physiologically based pharmacokinetic (mPBPK) model consisting of blood and two tissue compartments (Tissues 1 and 2) was used for modeling metformin PK in the nine species. Permeability-limited distribution (low fd1 and fd2) and a single tissue-to-plasma partition coefficient (Kp) value for Tissues 1 and 2 were applied in the joint mPBPK fitting. Nonlinear regression analysis for common tissue distribution parameters along with species-specific CL values reasonably captured the plasma PK profiles of metformin across most species, except for rat and horse with later time deviations. In separate fittings of the mPBPK model to each species, Tissue 2 was considered as slowly-equilibrating compartment consisting of muscle and skin based on in silico calculations of the mean transit times through tissues. The well-fitted mPBPK model parameters for absorption and disposition PK of metformin for each species were compared with in vitro/in vivo results found in the literature with regard to the physiological details and physicochemical properties of metformin. Bioavailability and absorption rates decreased with the increased BW among the species. Tissues such as muscle dominate metformin distribution with low permeability and partitioning while actual tissue concentrations found in rats and mice show likely transporter-mediated uptake in liver, kidney, and gastrointestinal tissues. Metformin has diverse pharmacologic actions, and this assessment revealed allometric relationships in its absorption and renal clearance but considerable variability in actual and modeled tissue distribution probably caused by transporter differences.

Modeling Pharmacokinetics and Pharmacodynamics of Therapeutic Antibodies: Progress, Challenges, and Future Directions

With more than 90 approved drugs by 2020, therapeutic antibodies have played a central role in shifting the treatment landscape of many diseases, including autoimmune disorders and cancers. While showing many therapeutic advantages such as long half-life and highly selective actions, therapeutic antibodies still face many outstanding issues associated with their pharmacokinetics (PK) and pharmacodynamics (PD), including high variabilities, low tissue distributions, poorly-defined PK/PD characteristics for novel antibody formats, and high rates of treatment resistance. We have witnessed many successful cases applying PK/PD modeling to answer critical questions in therapeutic antibodies’ development and regulations. These models have yielded substantial insights into antibody PK/PD properties. This review summarized the progress, challenges, and future directions in modeling antibody PK/PD and highlighted the potential of applying mechanistic models addressing the development questions.

Physiologically based pharmacokinetic (PBPK) modeling of RNAi therapeutics: Opportunities and challenges

Physiologically based pharmacokinetic (PBPK) modeling is a powerful tool with many demonstrated applications in various phases of drug development and regulatory review. RNA interference (RNAi)-based therapeutics are a class of drugs that have unique pharmacokinetic properties and mechanisms of action. With an increasing number of RNAi therapeutics in the pipeline and reaching the market, there is a considerable amount of active research in this area requiring a multidisciplinary approach. The application of PBPK models for RNAi therapeutics is in its infancy and its utility to facilitate the development of this new class of drugs is yet to be fully evaluated. From this perspective, we briefly discuss some of the current computational modeling approaches used in support of efficient development and approval of RNAi therapeutics. Considerations for PBPK model development are highlighted both in a relative context between small molecules and large molecules such as monoclonal antibodies and as it applies to RNAi therapeutics. In addition, the prospects for drawing upon other recognized avenues of PBPK modeling and some of the foreseeable challenges in PBPK model development for these chemical modalities are briefly discussed. Finally, an exploration of the potential application of PBPK model development for RNAi therapeutics is provided. We hope these preliminary thoughts will help initiate a dialogue between scientists in the relevant sectors to examine the value of PBPK modeling for RNAi therapeutics. Such evaluations could help standardize the practice in the future and support appropriate guidance development for strengthening the RNAi therapeutics development program.

Improving priors for human monoclonal antibody linear pharmacokinetic parameters by using half-lives from non-human primates

Obtaining a good prior for the linear pharmacokinetics of new monoclonal antibodies (mAbs) would be an advantage not only for designing first-in-human (FIH) studies but also for stabilizing fitting of data with non-linear target-mediated disposition models. We estimated the pharmacokinetics from FIH studies for five mAbs using a two-compartment model, both separately and together, using a simple pool, a third hierarchical level of random effects for between mAb differences and non-human-primate half-lives as a predictor covariate for said differences. There was good agreement between compounds for the rapidly accessible central volume of 2.9 L (70 kg human), but clearances and peripheral volumes differed with terminal half-lives ranging from 15 to 28 days. The simple pool of human studies gave inter-individual variability estimates of 32% coefficient of variation (CV) for clearance and 33% CV for peripheral volume, larger than for separate fits (13-26% CV and 15-35% CV for clearance and volume respectively). Using third level hierarchical random effects gave inter-individual variability estimates close to those of separate fits (24% and 16% CV respectively). The between-mAb differences became predictable if non-human primate body weight scaled terminal half-life estimates were included as covariates on clearance and peripheral volume. In conclusion, ignoring inter-mAb variation leads to inflated estimates of inter-individual variability and unrealistic simulations for FIH studies. However, by using 70 kg body weight scaled terminal half-life estimates from non-human primates one can account for between-mAb differences and provide non-inflated priors for the linear pharmacokinetic parameters of new mAbs.

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.

Modeling the dynamics of antibody-target binding in living tumors

Antibodies have become an attractive class of therapeutic agents for solid tumors, mainly because of their high target selectivity and affinity. The target binding properties of antibodies are critical for their efficacy and toxicity. Our lab has developed a bioluminescence resonance energy transfer (BRET) imaging approach that directly supports the measurement of the binding dynamics between antibodies and their targets in the native tumor environment. In the present study, we have developed a spatially resolved computational model analyzing the longitudinal BRET imaging data of antibody–target binding and exploring the mechanisms of biphasic binding dynamics between a model antibody cetuximab and its target, the epidermal growth factor receptor (EGFR). The model suggested that cetuximab is bound differently to EGFR in the stroma-rich area than in stroma-poor regions, which was confirmed by immunofluorescence staining. Compared to the binding in vitro, cetuximab bound to EGFR to a “slower-but-tighter” degree in the living tumors. These findings have provided spatially resolved characterizations of antibody–target binding in living tumors and have yielded many mechanistic insights into the factors that affect antibody interactions with its targets and treatment efficacy.

Transitioning from Basic toward Systems Pharmacodynamic Models: Lessons from Corticosteroids

Technology in bioanalysis, -omics, and computation have evolved over the past half century to allow for comprehensive assessments of the molecular to whole body pharmacology of diverse corticosteroids. Such studies have advanced pharmacokinetic and pharmacodynamic (PK/PD) concepts and models that often generalize across various classes of drugs. These models encompass the "pillars" of pharmacology, namely PK and target drug exposure, the mass-law interactions of drugs with receptors/targets, and the consequent turnover and homeostatic control of genes, biomarkers, physiologic responses, and disease symptoms. Pharmacokinetic methodology utilizes noncompartmental, compartmental, reversible, physiologic [full physiologically based pharmacokinetic (PBPK) and minimal PBPK], and target-mediated drug disposition models using a growing array of pharmacometric considerations and software. Basic PK/PD models have emerged (simple direct, biophase, slow receptor binding, indirect response, irreversible, turnover with inactivation, and transduction models) that place emphasis on parsimony, are mechanistic in nature, and serve as highly useful "top-down" methods of quantitating the actions of diverse drugs. These are often components of more complex quantitative systems pharmacology (QSP) models that explain the array of responses to various drugs, including corticosteroids. Progressively deeper mechanistic appreciation of PBPK, drug-target interactions, and systems physiology from the molecular (genomic, proteomic, metabolomic) to cellular to whole body levels provides the foundation for enhanced PK/PD to comprehensive QSP models. Our research based on cell, animal, clinical, and theoretical studies with corticosteroids have provided ideas and quantitative methods that have broadly advanced the fields of PK/PD and QSP modeling and illustrates the transition toward a global, systems understanding of actions of diverse drugs. SIGNIFICANCE STATEMENT: Over the past half century, pharmacokinetics (PK) and pharmacokinetics/pharmacodynamics (PK/PD) have evolved to provide an array of mechanism-based models that help quantitate the disposition and actions of most drugs. We describe how many basic PK and PK/PD model components were identified and often applied to the diverse properties of corticosteroids (CS). The CS have complications in disposition and a wide array of simple receptor-to complex gene-mediated actions in multiple organs. Continued assessments of such complexities have offered opportunities to develop models ranging from simple PK to enhanced PK/PD to quantitative systems pharmacology (QSP) that help explain therapeutic and adverse CS effects. Concurrent development of state-of-the-art PK, PK/PD, and QSP models are described alongside experimental studies that revealed diverse CS actions.

The biodistribution of therapeutic proteins: Mechanism, implications for pharmacokinetics, and methods of evaluation

Therapeutic proteins (TPs) are a diverse drug class that include monoclonal antibodies (mAbs), recombinantly expressed enzymes, hormones and growth factors, cytokines (e.g. chemokines, interleukins, interferons), as well as a wide range of engineered fusion scaffolds containing IgG1 Fc domain for half-life extension. As the pharmaceutical industry advances more potent and selective protein-based medicines through discovery and into the clinical stages of development, it has become widely appreciated that a comprehensive understanding of the mechanisms of TP biodistribution can aid this endeavor. This review aims to highlight the literature that has advanced our understanding of the determinants of TP biodistribution. A particular emphasis is placed on the multi-faceted role of the neonatal Fc receptor (FcRn) in mAb and Fc-fusion protein disposition. In addition, characterization of the TP-target interaction at the cell-level is discussed as an essential strategy to establish pharmacokinetic-pharmacodynamic (PK/PD) relationships that may lead to more informed human dose projections during clinical development. Methods for incorporation of tissue and cell-level parameters defining these characteristics into higher-order mechanistic and semi-mechanistic PK models will also be presented.

Image-guided mathematical modeling for pharmacological evaluation of nanomaterials and monoclonal antibodies

While plasma concentration kinetics has traditionally been the predictor of drug pharmacological effects, it can occasionally fail to represent kinetics at the site of action, particularly for solid tumors. This is especially true in the case of delivery of therapeutic macromolecules (drug-loaded nanomaterials or monoclonal antibodies), which can experience challenges to effective delivery due to particle size-dependent diffusion barriers at the target site. As a result, disparity between therapeutic plasma kinetics and kinetics at the site of action may exist, highlighting the importance of target site concentration kinetics in determining the pharmacodynamic effects of macromolecular therapeutic agents. Assessment of concentration kinetics at the target site has been facilitated by non-invasive in vivo imaging modalities. This allows for visualization and quantification of the whole-body disposition behavior of therapeutics that is essential for a comprehensive understanding of their pharmacokinetics and pharmacodynamics. Quantitative non-invasive imaging can also help guide the development and parameterization of mathematical models for descriptive and predictive purposes. Here, we present a review of the application of state-of-the-art imaging modalities for quantitative pharmacological evaluation of therapeutic nanoparticles and monoclonal antibodies, with a focus on their integration with mathematical models, and identify challenges and opportunities. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Diagnostic Tools > in vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

Enzyme and Transporter Kinetics for CPT-11 (Irinotecan) and SN-38: An Insight on Tumor Tissue Compartment Pharmacokinetics Using PBPK

BACKGROUND

Computational tools are becoming more and more powerful and comprehensive as compared to past decades in facilitating pharmaceutical, pharmacological and clinical practice. Anticancer agents are used either as monotherapy or in combination therapy to treat malignant conditions of the body. A single antineoplastic agent may be used in different types of malignancies at different doses according to the stage of the disease.

OBJECTIVE

To study the behavior of CPT-11 (Irinotecan) and its metabolite SN-38 in tumor tissue compartment through the Whole Body-Physiologically Pharmacokinetics (WB-PBPK) and to determine the activity of metabolic enzymes and transporters participating in the disposition of CPT-11 and SN-38 working in their physiological environment inside the human body.

METHODS

Whole body PBPK approach is used to determine the activity of different metabolic enzymes and transporters involved in the disposition of CPT-11 and its active metabolite, SN-38. The concentrations and pharmacokinetic parameters of the parent compound and its metabolite administered at clinically applicable dose via the intravenous route in the tumor tissue are predicted using this approach.

RESULTS

The activity rate constants of metabolic enzymes and transporters of CPT-11 are derived at their natural anatomic locations. Concentration-time curves of CPT-11 and SN-38 with their 5th to 95th percentage range are achieved at the tumor tissue level. Mean tumor tissue pharmacokinetics of both compounds are determined in a population of 100 individuals.

CONCLUSION

Tumor tissue concentration-time curves of CPT-11 and SN-38 can be determined via PBPK modeling. Rate constants of enzymes and transporters can be shown for healthy and tumor bearing individuals. The results will throw light on the effective concentration of active compound at its target tissue at the clinically applied IV dose.

Prediction of active human dose: learnings from 20 years of Merck KGaA experience, illustrated by case studies

High-quality dose predictions based on a good understanding of target engagement is one of the main translational goals in drug development. Here, we systematically evaluate active human dose predictions for 15 Merck KGaA/EMD Serono assets spanning several modalities and therapeutic areas. Using case studies, we illustrate the value of adhering to the translational best practices of having an exposure-response relationship in an appropriate animal model; having validated, translatable pharmacodynamic (PD) biomarkers measurable in Phase I populations in the right tissue; having a deeper understanding of biology; and capturing uncertainties in predictions. Given the gap in publications on the subject, we believe that the learnings from this unique diverse data set, which are generic to the industry, will trigger actions to improve future predictions.

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.

ATLAS mPBPK: A MATLAB-Based Tool for Modeling and Simulation of Minimal Physiologically-Based Pharmacokinetic Models

Minimal physiologically-based pharmacokinetic (mPBPK) models are frequently used to model plasma pharmacokinetic (PK) data and utilize and yield physiologically relevant parameters. Compared with classical compartment and whole-body physiologically-based pharmacokinetic modeling approaches, mPBPK models maintain a structure of intermediate physiological complexity that can be adequately informed by plasma PK data. In this tutorial, we present a MATLAB-based tool for the modeling and simulation of mPBPK models (ATLAS mPBPK) of small and large molecules. This tool enables the users to perform the following: (i) PK data visualization, (ii) simulation, (iii) parameter optimization, and (iv) local sensitivity analysis of mPBPK models in a simple and efficient manner. In addition to the theoretical background and implementation of the different tool functionalities, this tutorial includes simulation and sensitivity analysis showcases of small and large molecules with and without target-mediated drug disposition.

Whole-Body Physiologically Based Pharmacokinetic Modeling of Trastuzumab and Prediction of Human Pharmacokinetics

In the present study, we evaluated the pharmacokinetics (PK) of trastuzumab and sought to predict human PK based on animal studies, through the use of optical imaging and a whole-body physiologically based pharmacokinetic (WB-PBPK) modeling approach. The PK study was conducted in 24 mice, where serial blood samples were withdrawn and major organs were isolated after the last blood withdrawal. The drug concentrations in blood and major organs were measured via optical imaging. The WB-PBPK model was constructed using known physiological values including the volumes of major organs and blood/lymphatic flow. The NONMEM software (version 7.3) was used to determine tissue partition coefficients. Using the WB-PBPK model, a clinical trial simulation was performed with reference to human physiological values acquired from the literature. The simulated human PK was then compared with the actual PK observed in the previous study in which healthy male subjects received 6 mg/kg trastuzumab (Herceptin^®) via intravenous route. The ratio of the simulated versus observed area under the concentration-time curve was 1.02 and that of maximal concentration was 0.72. The current study describes the potential synergistic applications of WB-PBPK and optical imaging in human PK prediction based on preclinical data obtained in early-stage drug development.

Physiologically-based modeling of monoclonal antibody pharmacokinetics in drug discovery and development

Over the past few decades, monoclonal antibodies (mAbs) have become one of the most important and fastest growing classes of therapeutic molecules, with applications in a wide variety of disease areas. As such, understanding of the determinants of mAb pharmacokinetic (PK) processes (absorption, distribution, metabolism, and elimination) is crucial in developing safe and efficacious therapeutics. In the present review, we discuss the use of physiologically-based pharmacokinetic (PBPK) models as an approach to characterize the in vivo behavior of mAbs, in the context of the key PK processes that should be considered in these models. Additionally, we discuss current and potential future applications of PBPK in the drug discovery and development timeline for mAbs, spanning from identification of potential target molecules to prediction of potential drug-drug interactions. Finally, we conclude with a discussion of currently available PBPK models for mAbs that could be implemented in the drug development process.

Pre-Clinical Testing of Therapies for Traumatic Brain Injury

Despite the large number of promising neuroprotective agents identified in experimental traumatic brain injury (TBI) studies, none has yet shown meaningful improvements in long-term outcome in clinical trials. To develop recommendations and guidelines for pre-clinical testing of pharmacological or biological therapies for TBI, the Moody Project for Translational Traumatic Brain Injury Research hosted a symposium attended by investigators with extensive experience in pre-clinical TBI testing. The symposium participants discussed issues related to pre-clinical TBI testing including experimental models, therapy and outcome selection, study design, data analysis, and dissemination. Consensus recommendations included the creation of a manual of standard operating procedures with sufficiently detailed descriptions of modeling and outcome measurement procedures to permit replication. The importance of the selection of clinically relevant outcome variables, especially related to behavior testing, was noted. Considering the heterogeneous nature of human TBI, evidence of therapeutic efficacy in multiple, diverse (e.g., diffuse vs. focused) rodent models and a species with a gyrencephalic brain prior to clinical testing was encouraged. Basing drug doses, times, and routes of administration on pharmacokinetic and pharmacodynamic data in the test species was recommended. Symposium participants agreed that the publication of negative results would reduce costly and unnecessary duplication of unsuccessful experiments. Although some of the recommendations are more relevant to multi-center, multi-investigator collaborations, most are applicable to pre-clinical therapy testing in general. The goal of these consensus guidelines is to increase the likelihood that therapies that improve outcomes in pre-clinical studies will also improve outcomes in TBI patients.

Injectable anti-malarials revisited: discovery and development of new agents to protect against malaria

Over the last 15 years, the majority of malaria drug discovery and development efforts have focused on new molecules and regimens to treat patients with uncomplicated or severe disease. In addition, a number of new molecular scaffolds have been discovered which block the replication of the parasite in the liver, offering the possibility of new tools for oral prophylaxis or chemoprotection, potentially with once-weekly dosing. However, an intervention which requires less frequent administration than this would be a key tool for the control and elimination of malaria. Recent progress in HIV drug discovery has shown that small molecules can be formulated for injections as native molecules or pro-drugs which provide protection for at least 2 months. Advances in antibody engineering offer an alternative approach whereby a single injection could potentially provide protection for several months. Building on earlier profiles for uncomplicated and severe malaria, a target product profile is proposed here for an injectable medicine providing long-term protection from this disease. As with all of such profiles, factors such as efficacy, cost, safety and tolerability are key, but with the changing disease landscape in Africa, new clinical and regulatory approaches are required to develop prophylactic/chemoprotective medicines. An overall framework for these approaches is suggested here.

Tissue Physiology of Cynomolgus Monkeys: Cross-Species Comparison and Implications for Translational Pharmacology

We previously performed a comparative assessment of tissue-level vascular physiological parameters in mice and rats, two of the most commonly utilized species in translational drug development. The present work extends this effort to non-human primates by measuring tissue- and organ-level vascular volumes (V_v), interstitial volumes (V_i), and blood flow rates (Q) in cynomolgus monkeys. These measurements were accomplished by red blood cell labeling, extracellular marker infusion, and rubidium chloride bolus distribution, respectively, the same methods used in previous rodent measurements. In addition, whole-body blood volumes (BV) were determined across species. The results demonstrate that V_v, V_i, and Q, measured using our methods scale approximately by body weight across mouse, rat, and monkey in the tissues considered here, where allometric analysis allowed extrapolation to human parameters. Significant differences were observed between the values determined in this study and those reported in the literature, including V_v in muscle, brain, and skin and Q in muscle, adipose, heart, thymus, and spleen. The impact of these differences for selected tissues was evaluated via sensitivity analysis using a physiologically based pharmacokinetic model. The blood-brain barrier in monkeys was shown to be more impervious to an infused radioactive tracer, indium-111-pentetate, than in mice or rats. The body weight-normalized total BV measured in monkey agreed well with previously measured value in rats but was lower than that in mice. These findings have important implications for the common practice of scaling physiological parameters from rodents to primates in translational pharmacology.

A minimal physiologically based pharmacokinetic model to investigate FcRn-mediated monoclonal antibody salvage: Effects of Kon, Koff, endosome trafficking, and animal species

Manipulation of binding affinity between monoclonal antibodies (mAbs) and the neonatal Fc receptor (FcRn) has been leveraged to extend mAb half-life; however, the steps required for success remain ambiguous and experimental observations are inconsistent. Recent models have considered the time course of endosomal transit a major contributor to the relationship between FcRn affinity and antibody half-life. Our objective was to develop a minimal physiologically based pharmacokinetic model to explain how changes in IgG-FcRn association rate constant (K_on), dissociation rate constant (K_off), and endosomal transit time [T_(w)] translate to improved IgG clearance across mice, monkeys and humans. By simulating mAb clearance across physiological values of K_on, K_off, and T_(w), we found that lowering K_off improves clearance only until the dissociation half-life reaches endosomal transit time. In contrast, K_on influenced clearance independently of T_(w).The model was then applied to fit 66 mAb plasma profiles across species digitized from the literature, and clearance of mAb (CL_IgG) and vascular fluid-phase endocytosis rate (CL_up) were estimated. We found that CL_IgG scaled well with body weight (allometric exponent of 0.90). After accounting for mAbs with significant FcRn binding at physiological pH, CL_up was allometrically scalable (exponent 0.72). For the antibodies surveyed, K_on was more highly correlated with CL_IgG across all species. The relationship between K_off and K_D with CL_IgG was largely inconsistent. Taken together, this model provides a parsimonious approach to evaluate endosomal transit kinetics using only mAb plasma concentrations. These findings reinforce the idea that endosomal transit kinetics should be considered when modeling FcRn salvage.

Multi-Center Pre-clinical Consortia to Enhance Translation of Therapies and Biomarkers for Traumatic Brain Injury: Operation Brain Trauma Therapy and Beyond

Current approaches have failed to yield success in the translation of neuroprotective therapies from the pre-clinical to the clinical arena for traumatic brain injury (TBI). Numerous explanations have been put forth in both the pre-clinical and clinical arenas. Operation Brain Trauma Therapy (OBTT), a pre-clinical therapy and biomarker screening consortium has, to date, evaluated 10 therapies and assessed three serum biomarkers in nearly 1,500 animals across three rat models and a micro pig model of TBI. OBTT provides a unique platform to exploit heterogeneity of TBI and execute the research needed to identify effective injury specific therapies toward precision medicine. It also represents one of the first multi-center pre-clinical consortia for TBI, and through its work has yielded insight into the challenges and opportunities of this approach. In this review, important concepts related to consortium infrastructure, modeling, therapy selection, dosing and target engagement, outcomes, analytical approaches, reproducibility, and standardization will be discussed, with a focus on strategies to embellish and improve the chances for future success. We also address issues spanning the continuum of care. Linking the findings of optimized pre-clinical consortia to novel clinical trial designs has great potential to help address the barriers in translation and produce successes in both therapy and biomarker development across the field of TBI and beyond.

Minimal physiologically-based pharmacokinetic modeling of DSTA4637A, A novel THIOMAB™ antibody antibiotic conjugate against Staphylococcus aureus, in a mouse model

DSTA4637A, a THIOMAB™ antibody-antibiotic conjugate targeting Staphylococcus aureus, has shown promising bactericidal activity in a mouse model. DSTA4637A consists of a monoclonal anti-S. aureus antibody with an average of two rifalogue antibiotic molecules, dmDNA31, linked to its light chains. The goal of this study was to develop a minimal physiologically-based pharmacokinetic (mPBPK) model to characterize the pharmacokinetic (PK) properties of three analytes of DSTA4637A (i.e., total antibody, antibody-conjugated dmDNA31, and unconjugated dmDNA31) in mice, and to predict pharmacokinetics of DSTA4637A analytes in humans, as well as to provide an initial assessment for potential PK drug-drug interactions (DDI) in clinical trials via cross-species scaling of the mPBPK model. In the proposed model, selected organs, including heart, liver, and kidney, were connected anatomically with plasma and lymph flows. Mouse plasma and tissue concentrations of the three analytes of DSTA4637A were fitted simultaneously to estimate the PK parameters. Cross-species scaling of the model was performed by integrating allometric scaling and human physiological parameters. The final mPBPK model was able to successfully capture PK profiles of three DSTA4637A analytes in mouse plasma and in investigated organs. The model predicted a steady-state peak unbound dmDNA31 concentration lower than 5% of the IC₅₀ of dmDNA31 towards cytochrome P450 following 100 mg/kg weekly intravenous dose, which suggests a low risk of PK DDI in humans for DSTA4637A with co-administered cytochrome P450 substrates. The proposed mPBPK modeling and cross-species scaling approaches provide valuable tools that facilitate the understanding and translation of DSTA4637A disposition from preclinical species to humans.

Evaluation of the Effects of Animal Growth and Previous Exposure on the Pharmacokinetics of Rituximab in Rats

With a long half-life, pharmacokinetic (PK) evaluation of monoclonal antibodies in rodents lasts multiple weeks during which the animals may grow significantly. We evaluated the impact of weight, age, and previous drug exposure on the PK of rituximab. Serum concentrations of rituximab were measured after intravenous and subcutaneous dosing in Sprague Dawley rats aged between 7 and 21 weeks and weighing between 200 and 600 g. The growth of rats during the study was incorporated into the model through the increase of the volumes of compartments in relation to the rats total body weight. The final model successfully captured all the data; and no difference was observed in the rituximab PK profiles between exposure naïve and redosed or young and older rats. Incorporating the rodent growth over the time course of the study into the PK model was shown to be important for providing a more physiological description of the disposition of rituximab, especially when young and rapidly growing animals are used. Redosing the same rats with monoclonal antibodies might be a viable strategy for reducing the use of laboratory animals in accordance with the 3R principles.

A Minimal Physiologically Based Pharmacokinetic Model with a Nested Endosome Compartment for Novel Engineered Antibodies

We proposed here a minimal physiologically based pharmacokinetic (mPBPK) model for a group of novel engineered antibodies in mice and humans. These antibodies are designed with altered binding properties of their Fc domain with neonatal Fc receptor (FcRn) or the Fab domain with their cognate targets (recycling antibodies) in acidic endosomes. To enable simulations of such binding features in the change of antibody pharmacokinetics and its target suppression, we nested an endothelial endosome compartment in parallel with plasma compartment based on our previously established mPBPK model. The fluid-phase pinocytosis rate from plasma to endothelial endosomes was reflected by the clearance of antibodies in FcRn dysfunctional humans or FcRn-knockout mice. The endosomal recycling rate of FcRn-bound antibodies was calculated based on the reported endosomal transit time. The nonspecific catabolism in endosomes was fitted using pharmacokinetic data of a human wild-type IgG₁ adalimumab in humans and B21M in human FcRn (hFcRn) transgenic mice. The developed model adequately predicted the pharmacokinetics of infliximab, motavizumab, and an Fc variant of motavizumab in humans and the pharmacokinetics of bevacizumab, an Fc variant of bevacizumab, and a recycling antibody PH-IgG₁ and its non-pH dependent counterpart NPH-IgG₁ in hFcRn transgenic mice. Our proposed model provides a platform for evaluation of the pharmacokinetics and disposition behaviors of Fc-engineered antibodies and recycling antibodies.

Characterization and Interspecies Scaling of rhTNF-α Pharmacokinetics with Minimal Physiologically Based Pharmacokinetic Models

Tumor necrosis factor-α (TNF-α) is a soluble cytokine and target of specific monoclonal antibodies (mAbs) and other biologic agents used in the treatment of inflammatory diseases. These biologics exert their pharmacological effects through binding and neutralizing TNF-α, and thus they prevent TNF-α from interacting with its cell surface receptors. The magnitude of the pharmacological effects is governed not only by the pharmacokinetics (PK) of mAbs, but also by the kinetic fate of TNF-α We have examined the pharmacokinetics of recombinant human TNF-α (rhTNF-α) in rats at low doses and quantitatively characterized its pharmacokinetic features with a minimal physiologically based pharmacokinetic model. Our experimental and literature-digitalized PK data of rhTNF-α in rats across a wide range of doses were applied to global model fitting. rhTNF-α exhibits permeability rate-limited tissue distribution and its elimination is comprised of a saturable clearance pathway mediated by tumor necrosis factor receptor binding and disposition and renal filtration. The resulting model integrated with classic allometry was further used for interspecies PK scaling and resulted in model predictions that agreed well with experimental measurements in monkeys. In addition, a semimechanistic model was proposed and applied to explore the absorption kinetics of rhTNF-α following s.c. and other routes of administration. The model suggests substantial presystemic degradation of rhTNF-α for s.c. and i.m. routes and considerable lymph uptake contributing to the overall systemic absorption through the stomach wall and gastrointestinal wall routes of dosing. This report provides comprehensive modeling and key insights into the complexities of absorption and disposition of a major cytokine.

Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification

Modeling and simulation of drug disposition has emerged as an important tool in drug development, clinical study design and regulatory review, and the number of physiologically based pharmacokinetic (PBPK) modeling related publications and regulatory submissions have risen dramatically in recent years. However, the extent of use of PBPK modeling by researchers, and the public availability of models has not been systematically evaluated. This review evaluates PBPK-related publications to 1) identify the common applications of PBPK modeling; 2) determine ways in which models are developed; 3) establish how model quality is assessed; and 4) provide a list of publically available PBPK models for sensitive P450 and transporter substrates as well as selective inhibitors and inducers. PubMed searches were conducted using the terms "PBPK" and "physiologically based pharmacokinetic model" to collect published models. Only papers on PBPK modeling of pharmaceutical agents in humans published in English between 2008 and May 2015 were reviewed. A total of 366 PBPK-related articles met the search criteria, with the number of articles published per year rising steadily. Published models were most commonly used for drug-drug interaction predictions (28%), followed by interindividual variability and general clinical pharmacokinetic predictions (23%), formulation or absorption modeling (12%), and predicting age-related changes in pharmacokinetics and disposition (10%). In total, 106 models of sensitive substrates, inhibitors, and inducers were identified. An in-depth analysis of the model development and verification revealed a lack of consistency in model development and quality assessment practices, demonstrating a need for development of best-practice guidelines.