Balaji Agoram

Use of pharmacokinetic/ pharmacodynamic modelling for starting dose selection in first-in-human trials of high-risk biologics

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT Recent regulatory guidance has highlighted the importance of using pharmacokinetic-pharmacodynamic (PK-PD) modelling in the selection of starting doses in first-in-human trials of high-risk biologics. However, limited examples exist in literature illustrating this procedure. WHAT THIS STUDY ADDS An interpretation of the recommended dose-selection methodology and the minimum anticipated biological effect level (MABEL) principle, contained in the updated European Medicines Agency guidance on risk-mitigation strategies for first-in-human studies, is presented. Some literature and simulation-based examples of the application of PK-PD modelling principles to starting dose selection using in vitro and in vivo data under the MABEL paradigm are highlighted, along with the advantages and limitations of this approach. AIMS To illustrate the use of pharmacokinetic-pharmacodynamic (PK-PD) models to select rational starting doses in clinical trials within the minimum anticipated biological effect level (MABEL) principle using literature data and through simulations. METHODS The new European Medicines Agency guidance on starting dose selection of high-risk biologics was analysed considering the basic pharmacological properties and preclinical testing limitations of many biologics. The MABEL approach to dose selection was illustrated through simulations and through literature-reported examples on the selection of starting doses for biologics such as antibodies based on in vitro biomarker data, in vivo PK and PK-PD data. RESULTS Literature reports indicating the use of preclinical pharmacological and toxicological data to select successfully safe starting doses in line with the MABEL principle are summarized. PK-PD model-based simulations of receptor occupancy for an anti-IgE antibody system indicate that the relative abundance of IgE in animal models and patients and the turnover rate of the IgE-antibody complex relative to the off-rate of the antibody from IgE are important determinants of in vivo receptor occupancy. CONCLUSIONS Mechanistic PK-PD models are capable of integrating preclinical in vitro and in vivo data to select starting doses rationally in first-in-human trials. Biological drug-receptor interaction dynamics is complex and multiple factors affect the dose-receptor occupancy relationship. Thus, these factors should be taken into account when selecting starting doses.

Integration not isolation: arguing the case for quantitative and systems pharmacology in drug discovery and development

Quantitative and systems pharmacology (QSP) is an emerging modelling technique that combines the flexibility of systems biology and tractability of compartmental pharmacokinetic-pharmacodynamic modelling techniques. Historically, there has been extensive use of QSP within the field of pharmacokinetics to optimise drug biopharmaceutical properties. However, application to target and biomarker selection, and design of preclinical and clinical studies is limited, but growing rapidly. In this article we highlight the impact of QSP within drug discovery and development by citing examples from within the field of pharmacology and we argue for a more systematic integration of QSP within the drug discovery and development paradigm.

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).

Inhalation by Design: Novel Tertiary Amine Muscarinic M3 Receptor Antagonists with Slow Off-Rate Binding Kinetics for Inhaled Once-Daily Treatment of Chronic Obstructive Pulmonary Disease

A novel tertiary amine series of potent muscarinic M(3) receptor antagonists are described that exhibit potential as inhaled long-acting bronchodilators for the treatment of chronic obstructive pulmonary disease. Geminal dimethyl functionality present in this series of compounds confers very long dissociative half-life (slow off-rate) from the M(3) receptor that mediates very long-lasting smooth muscle relaxation in guinea pig tracheal strips. Optimization of pharmacokinetic properties was achieved by combining rapid oxidative clearance with targeted introduction of a phenolic moiety to secure rapid glucuronidation. Together, these attributes minimize systemic exposure following inhalation, mitigate potential drug-drug interactions, and reduce systemically mediated adverse events. Compound 47 (PF-3635659) is identified as a Phase II clinical candidate from this series with in vivo duration of action studies confirming its potential for once-daily use in humans.

Systems Pharmacology Models Can Be Used to Understand Complex Pharmacokinetic‐Pharmacodynamic Behavior: An Example Using 5‐Lipoxygenase Inhibitors

Zileuton, a 5‐lipoxygenase (5LO) inhibitor, displays complex pharmaokinetic (PK)‐pharmacodynamic (PD) behavior. Available clinical data indicate a lack of dose–bronchodilatory response during initial treatment, with a dose response developing after ~1–2 weeks. We developed a quantitative systems pharmacology (QSP) model to understand the mechanism behind this phenomenon. The model described the release, maturation, and trafficking of eosinophils into the airways, leukotriene synthesis by the 5LO enzyme, leukotriene signaling and bronchodilation, and the PK of zileuton. The model provided a plausible explanation for the two‐phase bronchodilatory effect of zileuton–the short‐term bronchodilation was due to leukotriene inhibition and the long‐term bronchodilation was due to inflammatory cell infiltration blockade. The model also indicated that the theoretical maximum bronchodilation of both 5LO inhibition and leukotriene receptor blockade is likely similar. QSP modeling provided interesting insights into the effects of leukotriene modulation.

Pharmacokinetics of tralokinumab in adolescents with asthma: implications for future dosing

AIMS Tralokinumab, an investigational human immunoglobulin G4 monoclonal antibody, potently and specifically neutralizes interleukin-13, a central mediator of asthma. Tralokinumab has shown improvements in clinical endpoints in adults with uncontrolled asthma. The present study explored the pharmacokinetics (PK) and safety of a single tralokinumab dose, and utilized a population PK modelling and simulation approach to evaluate the optimal dosing strategy for adolescents. METHODS Adolescent subjects with asthma, using daily controller medication, received a single subcutaneous dose of tralokinumab 300 mg. Safety, immunogenicity and PK data were collected during a 57-day follow-up. A population PK model was developed using data from the present study and prior studies in adults. Simulations were performed to evaluate dose adjustment requirements for adolescents. RESULTS Twenty adolescents (12-17 years) were enrolled; all completed the study. No clinically relevant safety findings or antidrug antibodies were detected. PK parameters were similar to those observed in adults. PK modelling showed that body weight was a minor predictor of tralokinumab PK; after incorporating body weight into the PK model, a 15% (nonparametric 95% confidence interval 5%, 26%) lower clearance was found in adolescents compared with adults [173 (151, 209) vs. 204 (191, 229) ml day(-1)]. Simulations showed no therapeutically relevant differences in exposures between adolescent and adult populations, and similar PK profiles for weight-based (4 mg kg(-1)) and fixed (300 mg) fortnightly subcutaneous doses of tralokinumab. CONCLUSION Single-dose administration of tralokinumab 300 mg in adolescents was well tolerated, with a PK profile similar to that in adults. Exposure predictions suggest that dose adjustment is not required for adolescents.

Effects of IL-1β-Blocking Therapies in Type 2 Diabetes Mellitus: A Quantitative Systems Pharmacology Modeling Approach to Explore Underlying Mechanisms.

Recent clinical studies suggest sustained treatment effects of interleukin‐1β (IL‐1β)–blocking therapies in type 2 diabetes mellitus. The underlying mechanisms of these effects, however, remain underexplored. Using a quantitative systems pharmacology modeling approach, we combined ex vivo data of IL‐1β effects on β‐cell function and turnover with a disease progression model of the long‐term interactions between insulin, glucose, and β‐cell mass in type 2 diabetes mellitus. We then simulated treatment effects of the IL‐1 receptor antagonist anakinra. The result was a substantial and partly sustained symptomatic improvement in β‐cell function, and hence also in HbA1C, fasting plasma glucose, and proinsulin–insulin ratio, and a small increase in β‐cell mass. We propose that improved β‐cell function, rather than mass, is likely to explain the main IL‐1β–blocking effects seen in current clinical data, but that improved β‐cell mass might result in disease‐modifying effects not clearly distinguishable until >1 year after treatment.

Methodologies for Quantitative Systems Pharmacology (QSP) Models: Design and Estimation

With the increased interest in the application of quantitative systems pharmacology (QSP) models within medicine research and development, there is an increasing need to formalize model development and verification aspects. In February 2016, a workshop was held at Roche Pharma Research and Early Development to focus discussions on two critical methodological aspects of QSP model development: optimal structural granularity and parameter estimation. We here report in a perspective article a summary of presentations and discussions.

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.

A Mathematical Modeling Approach to Understanding the Effect of Anti‐Interleukin Therapy on Eosinophils

Emerging T‐helper type 2 (Th2) cytokine‐based asthma therapies, such as tralokinumab, lebrikizumab (anti‐interleukin (IL)‐13), and mepolizumab (anti‐IL‐5), have shown differences in their blood eosinophil (EOS) response. To better understand these effects, we developed a mathematical model of EOS dynamics. For the anti‐IL‐13 therapies, lebrikizumab and tralokinumab, the model predicted an increase of 30% and 10% in total and activated EOS in the blood, respectively, and a decrease in the total and activated EOS in the airways. The model predicted a rapid decrease in total and activated EOS levels in blood and airways for the anti‐IL‐5 therapy mepolizumab. All model‐based predictions were consistent with published clinical observations. The modeling approach provided insights into EOS response after treatment with Th2‐targeted therapies, and supports the hypothesis that an increase in blood EOS after anti‐IL‐13 therapy is part of the pharmacological action of these therapies.