The role of mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modelling in translational research of biologics

Integrating Multiscale Modeling with Drug Effects for Cancer Treatment

In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system's pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute.

A mechanistic pharmacokinetic/pharmacodynamic model of factor D inhibition in cynomolgus monkeys by lampalizumab for the treatment of geographic atrophy

Lampalizumab is an antigen-binding fragment of a humanized monoclonal antibody against complement factor D (CFD), a rate-limiting enzyme in the activation and amplification of the alternative complement pathway (ACP), which is in phase III clinical trials for the treatment of geographic atrophy. Understanding of the pharmacokinetics, pharmacodynamics, and biodistribution of lampalizumab following intravitreal administration in the ocular compartments and systemic circulation is limited but crucial for selecting doses that provide optimal efficacy and safety. Here, we sought to construct a semimechanistic and integrated ocular-systemic pharmacokinetic-pharmacodynamic model of lampalizumab in the cynomolgus monkey to provide a quantitative understanding of the ocular and systemic disposition of lampalizumab and CFD inhibition. The model takes into account target-mediated drug disposition, target turnover, and drug distribution across ocular tissues and systemic circulation. Following intravitreal administration, lampalizumab achieves rapid equilibration across ocular tissues. Lampalizumab ocular elimination is relatively slow, with a τ1/2 of approximately 3 days, whereas systemic elimination is rapid, with a τ1/2 of 0.8 hours. Target-independent linear clearance is predominant in the eye, whereas target-mediated clearance is predominant in the systemic circulation. Systemic CFD synthesis was estimated to be high (7.8 mg/day); however, the amount of CFD entering the eye due to influx from the systemic circulation was small (<10%) compared with the lampalizumab dose and is thus expected to have an insignificant impact on the clinical dose-regimen decision. Our findings support the clinical use of intravitreal lampalizumab to achieve significant ocular ACP inhibition while maintaining low systemic exposure and minimal systemic ACP inhibition.

Utility of free and total target measurements as target engagement and efficacy biomarkers in biotherapeutic development--opportunities and challenges

For biotherapeutics directed against soluble targets, most often monoclonal antibodies (mAbs), their therapeutic efficacy theoretically is driven by the magnitude and duration of free target suppression. However, for soluble targets of rapid turnover and low abundance, it can be technically challenging to directly measure the lowering of free target following treatment with biologics. The opportunities, challenges, and practical approaches to assess free and bound soluble targets and the utility of free and bound target measurements as biomarkers for target engagement and efficacy are covered in this review. In particular, case examples are presented to illustrate the interplay between drug and free/bound target, and how an integrated bioanalytical and pharmacokinetic/target engagement/pharmacodynamic (PK/TE/PD) modeling approach can be used to assess the target engagement for biologics directed against soluble targets with rapid turnover. Important caveats of the modeling approach in the absence of free target measurements are also discussed.

Challenges and considerations for development of therapeutic proteins in pediatric patients

Target specificity and generally good tolerability of therapeutic proteins (TPs) present desirable treatment opportunities for pediatric patients. However, little is known on the ontogeny of processes related to the pharmacokinetics (PK) and disposition of TPs. The science, regulatory requirements and strategy of developing TPs for children are evolving. Our current review of TPs, (with focus on monoclonal antibodies and fusion proteins) that were approved for pediatric use indicates that dose-selection for pediatric pivotal studies is often based on adult PK information alone. This approach might not be sufficient if more complex PK properties than simple linear PK are present. Body weight-based dosing for pediatric patients directly scaled down from adult dosing can lead to under-exposure in young pediatric patients who are usually in the lowest body-weight range. Tiered-fixed dosing can be reasonably effective for TPs in achieving comparable exposure in children over a wide age range. The uniqueness of the pediatric population, the practical challenges in conducting clinical studies in this population, as well as regulations from health authorities warrant including pharmacometrics as an integral component of pediatric drug development. We propose a framework distinct from previous proposals, to guide clinical pharmacology strategy for pediatric drug development specifically for TPs.

Bridging the gap between in vitro and in vivo: Dose and schedule predictions for the ATR inhibitor AZD6738

Understanding the therapeutic effect of drug dose and scheduling is critical to inform the design and implementation of clinical trials. The increasing complexity of both mono, and particularly combination therapies presents a substantial challenge in the clinical stages of drug development for oncology. Using a systems pharmacology approach, we have extended an existing PK-PD model of tumor growth with a mechanistic model of the cell cycle, enabling simulation of mono and combination treatment with the ATR inhibitor AZD6738 and ionizing radiation. Using AZD6738, we have developed multi-parametric cell based assays measuring DNA damage and cell cycle transition, providing quantitative data suitable for model calibration. Our in vitro calibrated cell cycle model is predictive of tumor growth observed in in vivo mouse xenograft studies. The model is being used for phase I clinical trial designs for AZD6738, with the aim of improving patient care through quantitative dose and scheduling prediction.

Molecular mechanism matters: Benefits of mechanistic computational models for drug development

Making drug development a more efficient and cost-effective process will have a transformative effect on human health. A key, yet underutilized, tool to aid in this transformation is mechanistic computational modeling. By incorporating decades of hard-won prior knowledge of molecular interactions, cellular signaling, and cellular behavior, mechanistic models can achieve a level of predictiveness that is not feasible using solely empirical characterization of drug pharmacodynamics. These models can integrate diverse types of data from cell culture and animal experiments, including high-throughput systems biology experiments, and translate the results into the context of human disease. This provides a framework for identification of new drug targets, measurable biomarkers for drug action in target tissues, and patient populations for which a drug is likely to be effective or ineffective. Additionally, mechanistic models are valuable in virtual screening of new therapeutic strategies, such as gene or cell therapy and tissue regeneration, identifying the key requirements for these approaches to succeed in a heterogeneous patient population. These capabilities, which are distinct from and complementary to those of existing drug development strategies, demonstrate the opportunity to improve success rates in the drug development pipeline through the use of mechanistic computational models.

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.

Integrated PK-PD and agent-based modeling in oncology

Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.

Pharmacodynamics, pharmacokinetics, and tolerability of intravenous or subcutaneous GC1113, a novel erythropoiesis-stimulating agent

BACKGROUND AND OBJECTIVES

GC1113, a hybrid Fc-fused erythropoietin, is a novel erythropoiesis-stimulating agent that is expected to have an extended duration of action. The preclinical data showed that the hemoglobin increase lasted longer following GC1113 administration than it did following the administration of darbepoetin alfa (NESP®). This study aimed to investigate the pharmacodynamic and pharmacokinetic characteristics and tolerability profiles of GC1113 in humans after single intravenous or subcutaneous administration and to compare the results with those for darbepoetin alfa.

METHODS

A dose-block randomized, placebo- and active-controlled, dose-escalation phase I clinical trial was conducted in 96 healthy volunteers. Blood samples were collected before and up to 672 h after drug administration and the serum erythropoietin concentration following the GC1113 or darbepoetin alfa administration was measured by an ELISA. The reticulocyte counts were measured for pharmacodynamic assessments. Pharmacokinetic and pharmacodynamic parameters were determined using non-compartmental methods.

RESULTS

The reticulocyte count-time profiles in the intravenous GC1113 3-5 μg/kg groups were comparable with those of the darbepoetin alfa 30 μg group. After subcutaneous administration of GC1113, reticulocyte count peaked later and decreased more slowly than it did following darbepoetin alfa administration. GC1113 (0.3-5 μg/kg intravenous, 1-8 μg/kg subcutaneous) was well-tolerated in the volunteers, and no immunogenicity was observed.

CONCLUSION

GC1113 was tolerated and effective in the studied dose range; these findings could be applied to further clinical studies with patients.

Pharmacokinetics, pharmacodynamics and safety of QGE031 (ligelizumab), a novel high-affinity anti-IgE antibody, in atopic subjects

BACKGROUND

Using a monoclonal antibody with greater affinity for IgE than omalizumab, we examined whether more complete suppression of IgE provided greater pharmacodynamic effects, including suppression of skin prick responses to allergen.

OBJECTIVE

To explore the pharmacokinetics, pharmacodynamics and safety of QGE031 (ligelizumab), a novel high-affinity humanized monoclonal IgG1κ anti-IgE.

METHODS

Preclinical assessments and two randomized, placebo-controlled, double-blind clinical trials were conducted in atopic subjects. The first trial administered single doses of QGE031 (0.1-10 mg/kg) or placebo intravenously, while the second trial administered two to four doses of QGE031 (0.2- 4 mg/kg) or placebo subcutaneously at 2-week intervals. Both trials included an open-label omalizumab arm.

RESULTS

Sixty of 73 (82%) and 96 of 110 (87%) subjects completed the intravenous and subcutaneous studies, respectively. Exposure to QGE031 and its half-life depended on the QGE031 dose and serum IgE level. QGE031 had a biexponential pharmacokinetic profile after intravenous administration and a terminal half-life of approximately 20 days. QGE031 demonstrated dose- and time-dependent suppression of free IgE, basophil FcεRI and basophil surface IgE superior in extent (free IgE and surface IgE) and duration to omalizumab. At Day 85, 6 weeks after the last dose, skin prick wheal responses to allergen were suppressed by > 95% and 41% in subjects treated subcutaneously with QGE031 (2 mg/kg) or omalizumab, respectively (P < 0.001). Urticaria was observed in QGE031- and placebo-treated subjects and was accompanied by systemic symptoms in one subject treated with 10 mg/kg intravenous QGE031. There were no serious adverse events.

CONCLUSION AND CLINICAL RELEVANCE

These first clinical data for QGE031, a high-affinity IgG1κ anti-IgE, demonstrate that increased suppression of free IgE compared with omalizumab translated to superior pharmacodynamic effects in atopic subjects, including those with high IgE levels. QGE031 may therefore benefit patients unable to receive, or suboptimally treated with, omalizumab.

Implementation of pharmacokinetic and pharmacodynamic strategies in early research phases of drug discovery and development at Novartis Institute of Biomedical Research

Characterizing the relationship between the pharmacokinetics (PK, concentration vs. time) and pharmacodynamics (PD, effect vs. time) is an important tool in the discovery and development of new drugs in the pharmaceutical industry. The purpose of this publication is to serve as a guide for drug discovery scientists toward optimal design and conduct of PK/PD studies in the research phase. This review is a result of the collaborative efforts of DMPK scientists from various Metabolism and Pharmacokinetic (MAP) departments of the global organization Novartis Institute of Biomedical Research (NIBR). We recommend that PK/PD strategies be implemented in early research phases of drug discovery projects to enable successful transition to drug development. Effective PK/PD study design, analysis, and interpretation can help scientists elucidate the relationship between PK and PD, understand the mechanism of drug action, and identify PK properties for further improvement and optimal compound design. Additionally, PK/PD modeling can help increase the translation of in vitro compound potency to the in vivo setting, reduce the number of in vivo animal studies, and improve translation of findings from preclinical species into the clinical setting. This review focuses on three important elements of successful PK/PD studies, namely partnership among key scientists involved in the study execution; parameters that influence study designs; and data analysis and interpretation. Specific examples and case studies are highlighted to help demonstrate key points for consideration. The intent is to provide a broad PK/PD foundation for colleagues in the pharmaceutical industry and serve as a tool to promote appropriate discussions on early research project teams with key scientists involved in PK/PD studies.

Using physiologically-based pharmacokinetic-guided "body-on-a-chip" systems to predict mammalian response to drug and chemical exposure

The continued development of in vitro systems that accurately emulate human response to drugs or chemical agents will impact drug development, our understanding of chemical toxicity, and enhance our ability to respond to threats from chemical or biological agents. A promising technology is to build microscale replicas of humans that capture essential elements of physiology, pharmacology, and/or toxicology (microphysiological systems). Here, we review progress on systems for microscale models of mammalian systems that include two or more integrated cellular components. These systems are described as a "body-on-a-chip", and utilize the concept of physiologically-based pharmacokinetic (PBPK) modeling in the design. These microscale systems can also be used as model systems to predict whole-body responses to drugs as well as study the mechanism of action of drugs using PBPK analysis. In this review, we provide examples of various approaches to construct such systems with a focus on their physiological usefulness and various approaches to measure responses (e.g. chemical, electrical, or mechanical force and cellular viability and morphology). While the goal is to predict human response, other mammalian cell types can be utilized with the same principle to predict animal response. These systems will be evaluated on their potential to be physiologically accurate, to provide effective and efficient platform for analytics with accessibility to a wide range of users, for ease of incorporation of analytics, functional for weeks to months, and the ability to replicate previously observed human responses.

Pharmacokinetics and pharmacokinetic-pharmacodynamic correlations of therapeutic peptides

Peptides, defined as polymers of less than 50 amino acids with a molecular weight of less than 10 kDa, represent a fast-growing class of new therapeutics which has unique pharmacokinetic characteristics compared to large proteins or small molecule drugs. Unmodified peptides usually undergo extensive proteolytic cleavage, resulting in short plasma half-lives. As a result of their low permeability and susceptibility to catabolic degradation, therapeutic peptides usually have very limited oral bioavailability and are administered either by the intravenous, subcutaneous, or intramuscular route, although other routes such as nasal delivery are utilized as well. Distribution processes are mainly driven by a combination of diffusion and to a lesser degree convective extravasation dependent on the size of the peptide, with volumes of distribution frequently not larger than the volume of the extracellular body fluid. Owing to the ubiquitous availability of proteases and peptidases throughout the body, proteolytic degradation is not limited to classic elimination organs. Since peptides are generally freely filtered by the kidneys, glomerular filtration and subsequent renal metabolism by proteolysis contribute to the elimination of many therapeutic peptides. Although small peptides have usually limited immunogenicity, formation of anti-drug antibodies with subsequent hypersensitivity reactions has been described for some peptide therapeutics. Numerous strategies have been applied to improve the pharmacokinetic properties of therapeutic peptides, especially to overcome their metabolic instability, low permeability, and limited tissue residence time. Applied techniques include amino acid substitutions, modification of the peptide terminus, inclusion of disulfide bonds, and conjugation with polymers or macromolecules such as antibody fragments or albumin. Application of model-based pharmacokinetic-pharmacodynamic correlations has been widely used for therapeutic peptides in support of drug development and dosage regimen design, especially because their targets are often well-described endogenous regulatory pathways and processes.

Preclinical PK/PD modeling and human efficacious dose projection for a glucokinase activator in the treatment of diabetes

Human Hexokinase IV, or glucokinase (GK), is a regulator of glucose concentrations in the body. It plays a key role in pancreatic insulin secretion as well as glucose biotransformation in the liver, making it a potentially viable target for treatment of Type 2 diabetes. Allosteric activators of GK have been shown to decrease blood glucose concentrations in both animals and humans. Here, the development of a mathematical model is presented that describes glucose modulation in an ob/ob mouse model via administration of a potent GK activator, with the goal of projecting a human efficacious dose and plasma exposure. The model accounts for the allosteric interaction between GK, the activator, and glucose using a modified Hill function. Based on model simulations using data from the ob/ob mouse and in vitro studies, human projections of glucose response to the GK activator are presented, along with dose and regimen predictions to maintain clinically significant decreases in blood glucose in a Type 2 diabetic patient. This effort serves as a basis to build a detailed mechanistic understanding of GK and its role as a therapeutic target for Type 2 diabetes, and it highlights the benefits of using such an approach in a drug discovery setting.

Tissue bioanalysis of biotherapeutics and drug targets to support PK/PD

Contemporary drug discovery leverages quantitative modeling and simulation with increasing emphasis, both to gain deeper knowledge of drug targets and mechanisms as well as improve predictions between preclinical models and clinical applications, such as first-in-human dose projections. Proliferation of novel biotherapeutic modalities increases the need for applied PK/PD modeling as a quantitative tool to advance new therapies. Of particular relevance is the understanding of exposure, target binding and associated pharmacology at the target site of interest. Bioanalytical methods are key to informing PK/PD models and require assessment of both PK and PD end points. Where targets are sequestered in tissues (noncirculating), the ability to quantitatively measure drug or biomarker in tissue compartments becomes particularly important. This perspective provides an overview of contemporary applications of quantitative bioanalysis in tissue compartments as applied to PK and PD assessments associated with novel biotherapeutics. Case studies and key references are provided.

Effect of antigen binding affinity and effector function on the pharmacokinetics and pharmacodynamics of anti-IgE monoclonal antibodies

Modulating the binding affinities to IgE or changing the FcγR binding properties of anti-IgE antibodies offers an opportunity to enhance the therapeutic potential of anti-IgE antibodies, but the influence of increased affinity to IgE or reduced Fc effector function on the pharmacological properties of anti-IgE therapies remains unclear. Our studies were designed to characterize the pharmacokinetics, pharmacodynamics and immune-complex distribution of two high-affinity anti-IgE monoclonal antibodies, high-affinity anti-IgE antibody (HAE) 1 and 2, in mice and monkeys. HAE1, also known as PRO98498, is structurally similar to omalizumab (Xolair®), a humanized anti-IgE IgG1 marketed for the treatment of asthma, but differs by 9 amino acid changes in the complementarity-determining region resulting in a 23-fold improvement in affinity. HAE2 is similar to HAE1, but its Fc region was altered to reduce binding to Fcγ receptors. As expected given the decreased binding to Fcγ receptors, systemic exposure to pre-formed HAE2:IgE complexes in mice was greater (six-fold) and distribution to the liver lower (four-fold) compared with HAE1:IgE complexes. In monkeys, systemic exposure to HAE1 was similar to that previously observed for omalizumab in this species, but required comparatively lower serum drug concentrations to suppress free IgE levels. HAE2 treatment resulted in greater exposure and greater increase of total IgE, relative to HAE1, because of decreased clearance of HAE2:IgE complexes. Overall, these data suggest that increased binding affinity to IgE may provide a more effective therapeutic for asthma patients, and that retaining FcγR binding of the anti-IgE antibody is important for elimination of anti-IgE:IgE complexes.

Pharmacokinetics of Peptide-Fc fusion proteins

Peptide-Fc fusion proteins (or peptibodies) are chimeric proteins generated by fusing a biologically active peptide with the Fc-domain of immunoglobulin G. In this review, we describe recent studies that have evaluated the absorption, distribution, metabolism, and excretion characteristics of peptibodies. Key features of the pharmacokinetics of peptibodies include their extended half-life due to recycling by the neonatal Fc receptor (FcRn), a substantial contribution by renal excretion to total clearance and, for certain peptibodies, target-mediated drug disposition. The prolonged half-life of peptibodies permits less-frequent dose administration compared with small therapeutic peptides, thereby supporting patient convenience and compliance. Hence, a considerable number of peptibodies are currently in preclinical and clinical development. Investigation of the metabolism (biotransformation) of biologics is an evolving area of research: ligand-binding mass spectrometry techniques have been employed for the characterization of the peptibody romiplostim, providing a new approach to evaluation of the degradation products of biologics. Pharmacokinetic/pharmacodynamic modeling and simulation techniques have been used to predict the pharmacokinetics of peptibodies which can inform clinical decision-making, particularly selection of dosing regimens. This integrated review highlights the distinct pharmacokinetic characteristics of peptibodies and their influence on the drug development process for this emerging family of therapeutics.

The development of a fully-integrated immune response model (FIRM) simulator of the immune response through integration of multiple subset models

Background

The complexity and multiscale nature of the mammalian immune response provides an excellent test bed for the potential of mathematical modeling and simulation to facilitate mechanistic understanding. Historically, mathematical models of the immune response focused on subsets of the immune system and/or specific aspects of the response. Mathematical models have been developed for the humoral side of the immune response, or for the cellular side, or for cytokine kinetics, but rarely have they been proposed to encompass the overall system complexity. We propose here a framework for integration of subset models, based on a system biology approach.

Results

A dynamic simulator, the Fully-integrated Immune Response Model (FIRM), was built in a stepwise fashion by integrating published subset models and adding novel features. The approach used to build the model includes the formulation of the network of interacting species and the subsequent introduction of rate laws to describe each biological process. The resulting model represents a multi-organ structure, comprised of the target organ where the immune response takes place, circulating blood, lymphoid T, and lymphoid B tissue. The cell types accounted for include macrophages, a few T-cell lineages (cytotoxic, regulatory, helper 1, and helper 2), and B-cell activation to plasma cells. Four different cytokines were accounted for: IFN-γ, IL-4, IL-10 and IL-12. In addition, generic inflammatory signals are used to represent the kinetics of IL-1, IL-2, and TGF-β. Cell recruitment, differentiation, replication, apoptosis and migration are described as appropriate for the different cell types. The model is a hybrid structure containing information from several mammalian species. The structure of the network was built to be physiologically and biochemically consistent. Rate laws for all the cellular fate processes, growth factor production rates and half-lives, together with antibody production rates and half-lives, are provided. The results demonstrate how this framework can be used to integrate mathematical models of the immune response from several published sources and describe qualitative predictions of global immune system response arising from the integrated, hybrid model. In addition, we show how the model can be expanded to include novel biological findings. Case studies were carried out to simulate TB infection, tumor rejection, response to a blood borne pathogen and the consequences of accounting for regulatory T-cells.

Conclusions

The final result of this work is a postulated and increasingly comprehensive representation of the mammalian immune system, based on physiological knowledge and susceptible to further experimental testing and validation. We believe that the integrated nature of FIRM has the potential to simulate a range of responses under a variety of conditions, from modeling of immune responses after tuberculosis (TB) infection to tumor formation in tissues. FIRM also has the flexibility to be expanded to include both complex and novel immunological response features as our knowledge of the immune system advances.

Organ-on-a-chip technology and microfluidic whole-body models for pharmacokinetic drug toxicity screening

Microscale cell culture platforms better mimic the in vivo cellular microenvironment than conventional, macroscale systems. Microscale cultures therefore elicit a more authentic response from cultured cells, enabling physiologically realistic in vitro tissue models to be constructed. The fabrication of interconnecting microchambers and microchannels allows drug absorption, distribution, metabolism and elimination to be simulated, and enables precise manipulation of fluid flow to replicate blood circulation. Complex, multi-organ interactions can be investigated using "organ-on-a-chip" toxicology screens. By reproducing the dynamics of multi-organ interaction, the dynamics of various diseases and drug activities can be studied in mechanistic detail. In this review, we summarize the current status of technologies related to pharmacokinetic-based drug toxicity testing, and the use of microtechnology for reproducing the interaction between multiple organs.

Pharmacokinetic studies of protein drugs: past, present and future

Among the growing number of therapeutic proteins on the market, there is an emergence of biotherapeutics designed from our comprehension of the physiological mechanisms responsible for their peripheral and tissue pharmacokinetics. Most of them have been optimized to increase their half-life through glycosylation engineering, polyethylene glycol conjugation or Fc fusion. However, our understanding of biological drug behaviors is still its infancy compared to the huge amount of data regarding small molecular weight drugs accumulated over half a century. Unfortunately, therapeutic proteins share few resemblances with these drugs. For instance drug-targeted-mediated disposition, binding to glycoreceptors, lysosomal recycling, large hydrodynamic volume and electrostatic charge are typical critical characteristics that cannot be derived from our anterior knowledge of classical drugs. However, the numerous discoveries made in the two last decades have driven and will continue to drive new options in biochemical engineering and support the design of complex delivery systems. Most of these new developments will be supported by novel analytical methods for assessing in vitro or in vivo metabolism parameters.

Delivering systems pharmacogenomics towards precision medicine through mathematics

The latest developments of pharmacology in the post-genomic era foster the emergence of new biomarkers that represent the future of drug targets. To identify these biomarkers, we need a major shift from traditional genomic analyses alone, moving the focus towards systems approaches to elucidating genetic variation in biochemical pathways of drug response. Is there any general model that can accelerate this shift via a merger of systems biology and pharmacogenomics? Here we describe a statistical framework for mapping dynamic genes that affect drug response by incorporating its pharmacokinetic and pharmacodynamic pathways. This framework is expanded to shed light on the mechanistic and therapeutic differences of drug response based on pharmacogenetic information, coupled with genomic, proteomic and metabolic data, allowing novel therapeutic targets and genetic biomarkers to be characterized and utilized for drug discovery.

A mathematical analysis of rebound in a target-mediated drug disposition model: I.without feedback

We consider the possibility of free receptor (antigen/cytokine) levels rebounding to higher than the baseline level after one or more applications of an antibody drug using a target-mediated drug disposition model. Using geometry and dynamical systems analysis, we show that rebound will occur if and only if the elimination rate of the drug-receptor product is slower than the elimination rates of the drug and of the receptor. We also analyse the magnitude of rebound through approximations and simulations and demonstrate that it increases if the drug dose increases or if the difference between the elimination rate of the drug-receptor product and the minimum of the elimination rates of the drug and of the receptor increases.

Factors influencing magnitude and duration of target inhibition following antibody therapy: implications in drug discovery and development

Antibodies or antibody-related fusion proteins binding to soluble antigens in plasma form an important subclass of approved therapeutics. Pharmaceutical companies are constantly trying to accelerate the pace of drug discovery and development of these antibodies and identify superior candidates in face of significant attrition rates. Understanding the interplay between drug- and target-related factors on magnitude and duration of target inhibition is imperative for successful advancement of these therapeutics. Simulations using a target-mediated drug disposition model were performed to evaluate the influence of antibody-target binding affinity, baseline target concentration, and target turnover on magnitude and duration of soluble target inhibition. These simulations assumed intravenous dosing of the antibody and evaluated multiple parameters over a wide range. These simulations reveal that improvement in affinity reaches a point of diminishing returns following which further improvement in affinity does not alter the magnitude and more importantly the duration of target inhibition. Evaluation of unbound antibody and target kinetics indicated that point of diminishing returns in duration of inhibition was due to target-mediated binding and subsequent elimination of antibody at later time points. Similarly, influence of baseline target concentration and target turnover on magnitude and duration of target inhibition in plasma is shown. Additionally, the fraction of dose eliminated via target mediated elimination (Fel(™)) can be a useful tool to enable selection of strategies to increase duration of target inhibition. The implications of these simulations in drug discovery and development with regard to target identification, antibody optimization, and backup candidate selection are discussed.

Modeling, simulation, and translation framework for the preclinical development of monoclonal antibodies

The industry-wide biopharmaceutical (i.e., biologic, biotherapeutic) pipeline has been growing at an astonishing rate over the last decade with the proportion of approved new biological entities to new chemical entities on the rise. As biopharmaceuticals appear to be growing in complexity in terms of their structure and mechanism of action, so are interpretation, analysis, and prediction of their quantitative pharmacology. We present here a modeling and simulation (M&S) framework for the successful preclinical development of monoclonal antibodies (as an illustrative example of biopharmaceuticals) and discuss M&S strategies for its implementation. Critical activities during early discovery, lead optimization, and the selection of starting doses for the first-in-human study are discussed in the context of pharmacokinetic-pharmacodynamic (PKPD) and M&S. It was shown that these stages of preclinical development are and should be reliant on M&S activities including systems biology (SB), systems pharmacology (SP), and translational pharmacology (TP). SB, SP, and TP provide an integrated and rationalized framework for decision making during the preclinical development phase. In addition, they provide increased target and systems understanding, describe and interpret data generated in vitro and in vivo, predict human PKPD, and provide a rationalized approach to designing the first-in-human study.

Biotherapeutic first-in-human dose selection: making use of preclinical markers

First-in-human dose-selection criteria for biotherapeutics are changing, primarily based on severe adverse events in a single monoclonal antibody trial in healthy volunteers. Spurred by new EMA guidance, the minimum anticipated biological-effect level (MABEL) for estimating a starting human dose from exposure-response preclinical data have been introduced and should help to create long overdue target mechanism-based models focused on exposure-response relationships. Even though clarity of its application is still developing, this has the potential to become the model for most biotherapeutics in the future. However, maximizing benefit from MABEL will require increased efforts to define and create assays for relevant biomarkers of biological activity and safety as pharmacodynamic end points. Currently, this has not been realized sufficiently to make the model applicable to a majority of biotherapeutics; however, this review suggests how it can be applied universally with monoclonal antibodies.

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.

Conference Report: Analytical challenges in the qualification and validation of pharmacodynamic biomarkers

This 1-day workshop, held in association with the Royal Society of Chemistry Analytical Biosciences Group, discussed current concepts in the qualification and validation of biomarker assays for the measurement of pharmacodynamic responses to drugs and vaccines. The venue was Burlington House, the prestigious home of the Royal Society of Chemistry, with delegates drawn from academia, pharmaceutical companies and CROs.

Mechanism-based pharmacokinetic-pharmacodynamic modeling of the dopamine D2 receptor occupancy of olanzapine in rats

Purpose

A mechanism-based PK-PD model was developed to predict the time course of dopamine D₂ receptor occupancy (D₂RO) in rat striatum following administration of olanzapine, an atypical antipsychotic drug.

Methods

A population approach was utilized to quantify both the pharmacokinetics and pharmacodynamics of olanzapine in rats using the exposure (plasma and brain concentration) and D₂RO profile obtained experimentally at various doses (0.01–40 mg/kg) administered by different routes. A two-compartment pharmacokinetic model was used to describe the plasma pharmacokinetic profile. A hybrid physiology- and mechanism-based model was developed to characterize the D₂ receptor binding in the striatum and was fitted sequentially to the data. The parameters were estimated using nonlinear mixed-effects modeling .

Results

Plasma, brain concentration profiles and time course of D₂RO were well described by the model; validity of the proposed model is supported by good agreement between estimated association and dissociation rate constants and in vitro values from literature.

Conclusion

This model includes both receptor binding kinetics and pharmacokinetics as the basis for the prediction of the D₂RO in rats. Moreover, this modeling framework can be applied to scale the in vitro and preclinical information to clinical receptor occupancy.

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).

Improved method to evaluate the ability of compounds to destabilize the cellular plasma membrane

In the paper, we present an improved method for evaluation of a compound ability to destabilize erythrocyte plasma membrane. The proposed method is based on the continuous monitoring of the light scattered by erythrocytes exposed to osmotic pressure differences. The kinetics of hemolysis depends on the plasma membrane mechanics and the extent of the osmotic stress. Generally, the osmotic pressure difference of approximately 150 mOsm is taken for measurements, as a result of the equal volume mixing with the physiological salt solutions. In this approach the hemolytic process completion is not established which may result in poor quality and reproducibility of the experimental data. In consequence, inaccurate parameters of the kinetic are determined due to the low quality fitting to the, widely used, single exponential model. In the paper we propose a new experimental protocol allowing to determine the extended set of parameters for kinetics of hemolysis. Namely, the method of the minimal osmotic pressure difference determination is proposed which ensures the completeness of the hemolytic process. This step allows improving the quality and exactness of the calculated parameters. The developed methodology was tested on two qualitatively different, biologically relevant, experiments; evaluation of the peptide effect on the plasma membrane properties and differentiating between human and rabbit erythrocytes.

From target selection to the minimum acceptable biological effect level for human study: use of mechanism-based PK/PD modeling to design safe and efficacious biologics

In this paper, two applications of mechanism-based modeling are presented with their utility from candidate selection to first-in-human dosage selection. The first example is for a monoclonal antibody against a cytomegalovirus glycoprotein complex, which involves an antibody binding model and a viral load model. The model was used as part of a feasibility analysis prior to antibody generation, setting the specifications for the affinity needed to achieve a desired level of clinical efficacy. The second example is a pharmacokinetic-pharmacodynamic model based on a single-dose pharmacology study in cynomolgus monkey using data on pharmacokinetics, receptor occupancy, and the dynamics of target cell depletion and recovery. The model was used to estimate the MABEL, here defined as the minimum acceptable biological effect level against which a dose is selected for a first-in-human study. From these applications, we demonstrate that mechanism-based PK/PD binding models are useful for predicting human response to biologics compounds. Especially, such models have the ability to integrate preclinical and clinical, in vitro and in vivo information and facilitate rational decision making during various stages of drug discovery and translational research.

Optimizing preclinical study design in oncology research

The current drug development pathway in oncology research has led to a large attrition rate for new drugs, in part due to a general lack of appropriate preclinical studies that are capable of accurately predicting efficacy and/or toxicity in the target population. Because of an obvious need for novel therapeutics in many types of cancer, new compounds are being investigated in human Phase I and Phase II clinical trials before a complete understanding of their toxicity and efficacy profiles is obtained. In fact, for newer targeted molecular agents that are often cytostatic in nature, the conventional preclinical evaluation used for traditional cytotoxic chemotherapies utilizing primary tumor shrinkage as an endpoint may not be appropriate. By utilizing an integrated pharmacokinetic/pharmacodynamic approach, along with proper selection of a model system, the drug development process in oncology research may be improved leading to a better understanding of the determinants of efficacy and toxicity, and ultimately fewer drugs that fail once they reach human clinical trials.

Integration of in silico and in vitro platforms for pharmacokinetic-pharmacodynamic modeling

IMPORTANCE OF THE FIELD

Pharmacokinetic-pharmacodynamic (PK-PD) modeling enables quantitative prediction of the dose-response relationship. Recent advances in microscale technology enabled researchers to create in vitro systems that mimic biological systems more closely. Combination of mathematical modeling and microscale technology offers the possibility of faster, cheaper and more accurate prediction of the drug's effect with a reduced need for animal or human subjects.

AREAS COVERED IN THIS REVIEW

This article discusses combining in vitro microscale systems and PK-PD models for improved prediction of drug's efficacy and toxicity. First, we describe the concept of PK-PD modeling and its applications. Different classes of PK-PD models are described. Microscale technology offers an opportunity for building physical systems that mimic PK-PD models. Recent progress in this approach during the last decade is summarized.

WHAT THE READER WILL GAIN

This article is intended to review how microscale technology combined with cell cultures, also known as 'cells-on-a-chip', can confer a novel aspect to current PK-PD modeling. Readers will gain a comprehensive knowledge of PK-PD modeling and 'cells-on-a-chip' technology, with the prospect of how they may be combined for synergistic effect.

TAKE HOME MESSAGE

The combination of microscale technology and PK-PD modeling should contribute to the development of a novel in vitro/in silico platform for more physiologically-realistic drug screening.

Prediction of exposure-response relationships to support first-in-human study design

In drug development, phase 1 first-in-human studies represent a major milestone as the drug moves from preclinical discovery to clinical development activities. The safety of human subjects is paramount to the conduct of these studies and regulatory considerations guide activities. Forces of evolution on the pharmaceutical industry are re-shaping the first-in-human dose selection strategy. Namely, high attrition rates in part due to lack of efficacy have led to the re-organization of research and development organizations around the umbrella of translational research. Translational research strives to bring basic research advances into the clinic and support the reverse transfer of information to enhance compound selection strategies. Pharmacokinetic/pharmacodynamic (PK/PD) modeling holds a unique position in translational research by attempting to integrate diverse sets of information. PK/PD modeling has demonstrated utility in dose selection and trial design for later stages of drug development and is now being employed with greater prevalence in the translational research setting to manage risk (i.e., oncology and inflammation/immunology). Moving from empirical E (max) models to more mechanistic representations of the biological system, a higher fidelity of human predictions is expected. Strategies that have proven useful for PK predictions are being applied to PK/PD predictions. This review article examines examples of the application of PK/PD modeling in establishing target concentrations for supporting first-in-human study design.

Translational pharmacokinetic-pharmacodynamic modelling; application to cardiovascular safety data for PF-00821385, a novel HIV agent

AIM

To assess the translation of pharmacokinetic-pharmacodynamic (PK-PD) relationships for heart rate effects of PF-00821385 in dog and man.

METHODS

Cardiovascular telemetric parameters and concentration data were available for animals receiving active doses (0.5-120 mg kg(-1), n= 4) or vehicle. PF-00821385 was administered to 24 volunteers and pharmacokinetic and vital signs data were collected. PK-PD models were fitted using nonlinear mixed effects.

RESULTS

Compartmental models with linear absorption and clearance were used to describe pharmacokinetic disposition in animal and man. Diurnal variation in heart and pulse rate was best described with a single cosine function in both dog and man. Canine and human heart rate change were described by a linear model with free drug slope 1.76 bpm microM(-1)[95% confidence interval (CI) 1.17, 2.35] in the dog and 0.76 bpm microM(-1) (95% CI 0.54, 1.14) in man.

CONCLUSIONS

The preclinical translational of concentration-response has been described and the potential for further interspecies extrapolation and optimization of clinical trial design is addressed.

Type I interferon receptor is a primary regulator of target-mediated drug disposition of interferon-beta in mice

The purpose of this study is to evaluate the primary mechanism through which interferon (IFN)-beta exhibits target-mediated drug disposition (TMDD) and whether the theoretical assumptions of TMDD models are consistent with experimental pharmacokinetic (PK) data. Recombinant murine IFN-beta was administered as an intravenous injection at two dose levels (0.5 and 1 million IU/kg) to male wild-type (WT) and type-I IFN-alpha/beta receptor subunit (IFNAR-1) knockout (KO) mice (A129S7/SvEvBrd strain). Sampling was conducted at various times (n = 3/time point), and plasma was analyzed for IFN-beta concentrations using a validated enzyme-linked immunosorbent assay. The pharmacodynamic (PD) biomarker was IP-10 mRNA that was isolated from the distal femur bone and quantified using reverse transcription-polymerase chain reaction. An integrated model that includes rapid-binding TMDD and an indirect mechanism of drug action was used to characterize the PK/PD profiles. For an experimental control, PK profiles of recombinant murine erythropoietin (muEPO), another drug that exhibits TMDD, were determined after a single intravenous dose (0.5 microg/kg) in WT and KO animals. The concentration-time profiles for IFN-beta differed substantially at initial times for the WT and KO mice at the same dose levels. These differences are characteristic of ligands exhibiting receptor-mediated disposition and were well described by a rapid-binding TMDD model. No differences in muEPO PK were observed in the control study. In summary, the intact IFNAR receptor is a primary regulator of in vivo IFN-beta exposure. An integrated PK/PD model was successfully used to assess the receptor-mediated disposition and dynamics of IFN-beta.

Applying physiological and biochemical concepts to optimize biological drug development

Posology--the science of dose and regimen--is a critical part of drug development. It is concerned with ensuring that patients experience significant clinical benefit without intolerable adverse effects. It has become apparent, in the case of certain biologics, that one can directly quantitate occupancy or target capture and relate these to clinical responses. With mathematical models that integrate binding concepts with clinical effects, potential posologies can be quickly explored through simulation, thereby liberating research teams from the traditional constraints and simultaneously stimulating innovation.

The application of target information and preclinical pharmacokinetic/pharmacodynamic modeling in predicting clinical doses of a Dickkopf-1 antibody for osteoporosis

PF-04840082 is a humanized prototype anti-Dickkopf-1 (Dkk-1) immunoglobulin isotype G(2) (IgG(2)) antibody for the treatment of osteoporosis. In vitro, PF-04840082 binds to human, monkey, rat, and mouse Dkk-1 with high affinity. After administration of PF-04840082 to rat and monkey, free Dkk-1 concentrations decreased rapidly and returned to baseline in a dose-dependent manner. In rat and monkey, PF-04840082 exhibited nonlinear pharmacokinetics (PK) and a target-mediated drug disposition (TMDD) model was used to characterize PF-04840082 versus Dkk-1 concentration response relationship. PK/pharmacodynamic (PK/PD) modeling enabled estimation of antibody non-target-mediated elimination, Dkk-1 turnover, complex formation, and complex elimination. The TMDD model was translated to human to predict efficacious dose and minimum anticipated biological effect level (MABEL) by incorporating information on typical IgG(2) human PK, antibody-target association/dissociation rates, Dkk-1 expression, and turnover rates. The PK/PD approach to MABEL was compared with the standard "no adverse effect level" (NOAEL) approach to calculating clinical starting doses and a pharmacological equilibrium method. The NOAEL method gave estimates of dose that were too high to ensure safety of clinical trials. The pharmacological equilibrium approach calculated receptor occupancy (RO) based on equilibrium dissociation constant alone and did not take into account rate of turnover of the target or antibody-target complex kinetics and, as a result, it likely produced a substantial overprediction of RO at a given dose. It was concluded that the calculation of MABEL according to the TMDD model was the most appropriate means for ensuring safety and efficacy in clinical studies.