Mechanistic PK-PD Model Research Articles

Evaluation of a Bayesian hierarchical pharmacokinetic-pharmacodynamic model for predicting parasitological outcomes in Phase 2 studies of new antimalarial drugs.

The rise of multidrug-resistant malaria requires accelerated development of novel antimalarial drugs. Pharmacokinetic-pharmacodynamic (PK-PD) models relate blood antimalarial drug concentrations with the parasite-time profile to inform dosing regimens. We performed a simulation study to assess the utility of a Bayesian hierarchical mechanistic PK-PD model for predicting parasite-time profiles for a Phase 2 study of a new antimalarial drug, cipargamin. We simulated cipargamin concentration- and malaria parasite-profiles based on a Phase 2 study of eight volunteers who received cipargamin 7 days after inoculation with malaria parasites. The cipargamin profiles were generated from a two-compartment PK model and parasite profiles from a previously published biologically informed PD model. One thousand PK-PD data sets of eight patients were simulated, following the sampling intervals of the Phase 2 study. The mechanistic PK-PD model was incorporated in a Bayesian hierarchical framework, and the parameters were estimated. Population PK model parameters describing absorption, distribution, and clearance were estimated with minimal bias (mean relative bias ranged from 1.7% to 8.4%). The PD model was fitted to the parasitaemia profiles in each simulated data set using the estimated PK parameters. Posterior predictive checks demonstrate that our PK-PD model adequately captures the simulated PD profiles. The bias of the estimated population average PD parameters was low-moderate in magnitude. This simulation study demonstrates the viability of our PK-PD model to predict parasitological outcomes in Phase 2 volunteer infection studies. This work will inform the dose-effect relationship of cipargamin, guiding decisions on dosing regimens to be evaluated in Phase 3 trials.

Mechanistic PK-PD model of alendronate treatment of postmenopausal osteoporosis predicts bone site-specific response.

Alendronate is the most widely used drug for postmenopausal osteoporosis (PMO). It inhibits bone resorption, affecting osteoclasts. Pharmacokinetics (PK) and pharmacodynamics (PD) of alendronate have been widely studied, but few mathematical models exist to simulate its effect. In this work, we have developed a PK model for alendronate, valid for short- and long-term treatments, and a mechanistic PK-PD model for the treatment of PMO to predict bone density gain (BDG) at the hip and lumbar spine. According to our results, at least three compartments are required in the PK model to predict the effect of alendronate in both the short and long terms. Clinical data of a 2-year treatment of alendronate, reproduced by our PK-PD model, demonstrate that bone response is site specific (hip: 7% BDG, lumbar spine: 4% BDG). We identified that this BDG is mainly due to an increase in tissue mineralization and a decrease in porosity. The difference in BDG between sites is linked to the different loading and dependence of the released alendronate on the bone-specific surface and porosity. Osteoclast population diminishes quickly within the first month of alendronate treatment. Osteoblast population lags behind but also falls due to coupling of resorption and formation. Two dosing regimens were studied (70 mg weekly and 10 mg daily), and both showed very similar BDG evolution, indicating that alendronate accumulates quickly in bone and saturates. The proposed PK-PD model could provide a valuable tool to analyze the effect of alendronate and to design patient-specific treatments, including drug combinations.

Early Feasibility Assessment: A Method for Accurately Predicting Biotherapeutic Dosing to Inform Early Drug Discovery Decisions.

The application of model-informed drug discovery and development (MID3) approaches in the early stages of drug discovery can help determine feasibility of drugging a target, prioritize between targets, or define optimal drug properties for a target product profile (TPP). However, applying MID3 in early discovery can be challenging due to the lack of pharmacokinetic (PK) and pharmacodynamic (PD) data at this stage. Early Feasibility Assessment (EFA) is the application of mechanistic PKPD models, built from first principles, and parameterized by data that is readily available early in drug discovery to make effective dose predictions. This manuscript demonstrates the ability of EFA to make accurate predictions of clinical effective doses for nine approved biotherapeutics and outlines the potential of extending this approach to novel therapeutics to impact early drug discovery decisions.

Are drug holidays a safe option in treatment of osteoporosis? — Insights from an in silico mechanistic PK–PD model of denosumab treatment of postmenopausal osteoporosis

Recent reviews by the clinical bone research community suggest caution with prescription of drug holidays for patients with postmenopausal osteoporosis (PMO) treated with denosumab for an extended period of time. Main reasons for this suggestion are based on the fact that discontinuation of denosumab treatment leads to a relapse of osteoclastic bone resorption and a loss of bone mineral density (BMD) to pre-treatment levels at only 12–28 months. The question remains what is the best treatment option for cases where it is required to discontinue and/or reduce the drug dose and what are the consequences on BMD and bone turnover markers (BTMs). The latter questions are difficult to be addressed using clinical trials alone given the large number of parameter combinations involved to answer this problem.In this paper, we apply a recently developed in silico mechanistic pharmacokinetic–pharmacodynamic (PK–PD) model of the effect of denosumab on bone remodelling in PMO. To address the above clinical relevant questions, we design a wide range of current and virtual treatment regimens to study the effect of drug holiday duration and therapy resumption on the evolution of BTMs, BMD and mineral content. Our numerical simulation results indicate the symptomatic effect of denosumab, which is lost once treatment is stopped. This effect is most clearly seen on rapid loss of BMD to pre-treatment levels 12 months after the last injection (8% and 3.6% per year in the lumbar spine and femoral neck, respectively). Also, we identify that independently of the duration of drug holiday (i.e. 12, 16 or 18 months) resuming treatment can restore BMD quite effectively. However, the latter result does not consider the possibility of potential fractures that can occur during the drug holiday. Finally, we identify a treatment case most promising for achieving maintenance of BMD and mineral content, while moderately increasing BTMs. The latter case uses no drug holiday, but reduces the most commonly prescribed denosumab dose (60 mg every 6 months) by half at same interval.

Modelling of neutrophil dynamics in children receiving busulfan or treosulfan for haematopoietic stem cell transplant conditioning

Busulfan and treosulfan are cytotoxic agents used in the conditioning regime prior to paediatric haematopoietic stem cell transplantation (HSCT). These agents cause suppression of myeloid cells leaving patients severely immunocompromised in the early post-HSCT period. The main objectives were: (i) to establish a mechanistic pharmacokinetic-pharmacodynamic (PKPD) model for the treatment and engraftment effects on neutrophil counts comparing busulfan and treosulfan-based conditioning, and (ii) to explore current dosing schedules with respect to time to HSCT. Data on 126 patients, 72 receiving busulfan (7 months-18 years, 5.1-47.0 kg) and 54 treosulfan (4 months-17 years, 3.8-35.8 kg), were collected. In total, 8935 neutrophil count observations were recorded during the study period in addition to drug concentrations to develop a mechanistic PKPD model. Absolute neutrophil count profiles were modelled semimechanistically, accounting for transplant effects and differing set points pre- and post-transplant. PK were best described by 2-compartment models for both drugs. The Friberg semimechanistic neutropenia model was applied with a linear model for busulfan and a maximum efficacy model for treosulfan describing drug effects at various stages of neutrophil maturation. System parameters were consistent across both drugs. The HSCT was represented by an amount of progenitor cells enhancing the neutrophils' proliferation and maturation compartments. Alemtuzumab was found to enhance the proliferative rate under which the absolute neutrophil count begin to grow after HSCT. A semimechanistic PKPD model linking exposure to either busulfan or treosulfan to the neutrophil reconstitution dynamics was successfully built. Alemtuzumab coadministration enhanced the neutrophil proliferative rate after HSCT. Treosulfan administration was suggested to be delayed with respect to time to HSCT, leaving less time between the end of the administration and stem cell infusion.

Study of the combined effects of PTH treatment and mechanical loading in postmenopausal osteoporosis using a new mechanistic PK-PD model.

One of only a few approved and available anabolic treatments for severe osteoporosis is daily injections of PTH (1-34). This drug has a specific dual action which can act either anabolically or catabolically depending on the type of administration, i.e. intermittent or continuous, respectively. In this paper, we present a mechanistic pharmacokinetic-pharmacodynamic model of the action of PTH in postmenopausal osteoporosis. This model accounts for anabolic and catabolic activities in bone remodelling under intermittent and continuous administration of PTH. The model predicts evolution of common bone biomarkers and bone volume fraction (BV/TV) over time. We compared the relative changes in BV/TV resulting from a daily injection of 20 [Formula: see text]g of PTH with experimental data from the literature. Simulation results indicate a site-specific bone gain of 8.66[Formula: see text] (9.4 ± 1.13[Formula: see text]) at the lumbar spine and 3.14[Formula: see text] (2.82 ± 0.72[Formula: see text]) at the femoral neck. Bone gain depends nonlinearly on the administered dose, being, respectively, 0.68[Formula: see text], 3.4[Formula: see text] and 6.16[Formula: see text] for a 10, 20 and 40 [Formula: see text]g PTH dose at the FN over 2 years. Simulations were performed also taking into account a bone mechanical disuse to reproduce elderly frail subjects. The results show that mechanical disuse ablates the effects of PTH and leads to a 1.08% reduction of bone gain at the FN over a 2-year treatment period for the 20 [Formula: see text]g of PTH. The developed model can simulate a range of pathological conditions and treatments in bones including different PTH doses, different mechanical loading environments and combinations. Consequently, the model can be used for testing and generating hypotheses related to synergistic action between PTH treatment and physical activity.

Abstract 297: AZD4573: Mechanistic PKPD model linking CDK9 inhibition to Mcl1 depletion and induction of apoptosis in preclinical AML model

Abstract Cyclin-dependent kinase 9 (CDK9) regulates elongation of transcription through phosphorylation of RNA polymerase II (pSer2-RNAPII), and its short-term inhibition results in the selective downregulation of genes with short-lived transcripts and labile proteins - including the anti-apoptotic protein Mcl1. AZD4573 is a selective inhibitor of CDK9 with short pharmacokinetic (PK) half-life. Intermittent dosing of AZD4573 in mouse MV411 (AML cell line) xenograft models results in progressive reduction in tumor volume with the mechanism of action believed to be via induction of apoptosis following depletion of Mcl1. The aim of this work was to derive a quantitative understanding of the relationships between extent and duration of CDK9 inhibition, depletion of Mcl1 and rate of induction of apoptosis in MV411 tumor cells. A mechanistic model has been established that quantitatively and dynamically connects AZD4573 plasma and tumor PK to the rate and extent of modulation of pSer2-RNAPII and Mcl1 in the tumor and rate of induction of cell death (as measured by reduction in tumor volume). Tumor pSer2-RNAPII and Mcl1 pharmacodynamics were modeled using a series of linked indirect response models. Production rate of pSer2-RNAPII was modeled as being directly inhibited by AZD4573 concentration in the tumor. Production rate of Mcl1 was linked to pSer2-RNAPII via a series of transit compartments to capture the transcription/translation driven delay in onset of response. Induction of intrinsic apoptosis in the MV411 tumor cells was modelled as being inhibited by Mcl1. Tumor pSer2-RNAPII exhibited a rapid, dose-dependent decrease following IP dosing of AZD4573 in mice. The free concentration of AZD4573 that resulted in half-maximal inhibition of pSer2-RNAPII production rate was estimated to be in the range 11-21 nM. Following a brief delay, tumor Mcl1 also exhibited a relatively rapid decrease that was proportional to the pSer2-RNAPII response. Mcl1 protein half-life was estimated to be 0.3 hr. Rate of induction of apoptosis could be decribed as a saturable first-order process (Kmax ~ 0.2 hr-1) and appeared to exhibit a steep response to the depletion of Mcl1, with reduction of Mcl1 to 25% (of the baseline value) being estimated to result in half-maximal rate of induction of apoptosis in the MV411 cells. The described MV411 PKPD/efficacy model has been assumed to be representative of AML in human patients and was used to derive preliminary predictions of clinical efficacy at a range of possible IV dosing regimens. Citation Format: Douglas Ferguson, Theresa Proia, Justin Cidado, Scott Boiko, Maryann San Martin, Steven Criscione, Wenlin Shao, Lisa Drew. AZD4573: Mechanistic PKPD model linking CDK9 inhibition to Mcl1 depletion and induction of apoptosis in preclinical AML model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 297.

Translational mixed-effects PKPD modelling of recombinant human growth hormone - from hypophysectomized rat to patients.

We aimed to develop a mechanistic mixed-effects pharmacokinetic (PK)-pharmacodynamic (PD) (PKPD) model for recombinant human growth hormone (rhGH) in hypophysectomized rats and to predict the human PKPD relationship. A non-linear mixed-effects model was developed from experimental PKPD studies of rhGH and effects of long-term treatment as measured by insulin-like growth factor 1 (IGF-1) and bodyweight gain in rats. Modelled parameter values were scaled to human values using the allometric approach with fixed exponents for PKs and unscaled for PDs and validated through simulations relative to patient data. The final model described rhGH PK as a two compartmental model with parallel linear and non-linear elimination terms, parallel first-order absorption with a total s.c. bioavailability of 87% in rats. Induction of IGF-1 was described by an indirect response model with stimulation of kin and related to rhGH exposure through an Emax relationship. Increase in bodyweight was directly linked to individual concentrations of IGF-1 by a linear relation. The scaled model provided robust predictions of human systemic PK of rhGH, but exposure following s.c. administration was over predicted. After correction of the human s.c. absorption model, the induction model for IGF-1 well described the human PKPD data. A translational mechanistic PKPD model for rhGH was successfully developed from experimental rat data. The model links a clinically relevant biomarker, IGF-1, to a primary clinical end-point, growth/bodyweight gain. Scaling of the model parameters provided robust predictions of the human PKPD in growth hormone-deficient patients including variability.

Pharmacokinetic and Pharmacodynamic Properties of Romiplostim

Background:Chronic Immune thrombocytopenia (ITP) is characterized by low platelet counts, resulting from increased platelet destruction and inadequate platelet production. Romiplostim is a 59 kDa peptibody which binds to and activates the thrombopoietin (TPO) receptor on platelet precursors in the bone marrow, and increases platelet counts. This analysis integrates the pharmacokinetic (PK) and pharmacodynamic (PD) properties of romiplostim in animals, healthy volunteers and patients with ITP, and describes its intricate PK-PD inter-relationship.Methods and Results:In healthy subjects, over a wide range of doses examined, the PK and PD (platelet response) of romiplostim were dependent on both the dose administered and the baseline platelet counts. Following SC administration, platelet counts increased in a dose-dependent fashion after 4 to 9 days, peaking at 12 to 16 days (Wang Clin Pharmacol Ther. 2004;76:628-38). When romiplostim binds to the TPO receptor on megakaryocytes and platelets, the peptibody-receptor complex is internalized and degraded inside the cells. Therefore, as platelet counts increase, a higher number of free receptors are available to clear romiplostim (Wang AAPS J. 2010;12:729-40). Results from rodent studies suggest that as the dose increases, the TPO receptors become saturated and the contribution of the kidney to clearance increases. Additionally, proteolysis plays a role in the clearance of romiplostim; however, the cytochrome P450 enzymes are not involved in protein catabolism (Wang Pharm Res. 2011;28:1931-8), hence there are no known drug-drug interactions or dietary restrictions (Nplate Prescribing Information 2014).Following SC administration, serum concentrations of romiplostim were markedly lower, however, platelet response was similar after the same dose of intravenous (IV) and SC administration (Wang Clin Pharmacol Ther. 2004;76:628-38). This suggests that the PD response is driven by the length of time that the romiplostim concentrations remained above a threshold rather than by the magnitude of concentrations achieved. This effect was verified in a mechanistic PK-PD modeling study in animals (Krzyzanski Pharm Res. 2013;30:655-69). In patients with ITP receiving SC romiplostim at a dose of 1 mcg/kg, the peak platelet response was achieved at 18 days (range 8 to 43; Bussel N Engl J Med. 2006;355:1672-81). Pharmacodynamic model analysis showed that compared with healthy subjects, patients with ITP had a shorter platelet life span and a decreased rate of production of progenitor cells, but no major difference in the time to maturation of megakaryocytes. The PD response in this modeling analysis was not notably affected by age, body weight, sex, and race (Perez-Ruixo J Clin Pharmacol. 2012;52:1540-51). The frequency of once-weekly dosing was selected because once every 2 weeks dosing was determined to be inadequate to achieve and maintain platelet counts in the therapeutic range (Bussel N Engl J Med. 2006;355:1672-81). A mechanistic PK-PD model based on data from the healthy subjects further suggested that weekly dosing resulted in a sustained platelet response while dosing less frequently resulted in high fluctuation of platelet counts (Wang AAPS J. 2010;12:729-40). Large inter- and intra-individual variability in the PD response was observed at a given dose; therefore, dose adjustments should be made based on a patient’s platelet counts, using a titrated dosing scheme to prevent having platelet counts over 400 x 109/L (Perez-Ruixo J Clin Pharmacol. 2012;52:1540-51).Conclusion:Romiplostim is a peptibody that binds and activates the TPO receptor, and consequently increases platelet production in individuals with chronic ITP. The peptibody-receptor complex is internalized and degraded inside the cells, without involvement of the liver. Romiplostim’s PD response is driven by the length of time that its concentrations remained above a threshold rather than by the magnitude of concentrations achieved. Moreover, weekly dosing has demonstrated a sustained platelet response while less frequent dosing resulted in fluctuating platelet counts. DisclosuresArkam:Amgen Inc.: Employment, Equity Ownership. Off Label Use: Romiplostim is a thrombopoietin receptor agonist indicated for the treatment of thrombocytopenia in patients with chronic immune thrombocytopenia (ITP) who have had an insufficient response to corticosteroids, immunoglobulins, or splenectomy. This abstract also describes PK data from healthy volunteers.. Doshi:Amgen Inc.: Employment, Equity Ownership. Yang:Amgen Inc.: Employment, Equity Ownership.

Mechanism - Based Translational Pharmacokinetic - Pharmacodynamic Model to Predict Intraocular Pressure Lowering Effect of Drugs in Patients with Glaucoma or Ocular Hypertension

To develop a mechanism based translational pharmacokinetic-pharmacodynamic (PKPD) model in preclinical species and to predict the intraocular pressure (IOP) following drug treatment in patients with glaucoma or ocular hypertension (OHT). Baseline diurnal IOP of normotensive albino rabbits, beagle dogs and patients with glaucoma or OHT was collected from literature. In addition, diurnal IOP of patients treated with brimonidine or Xalatan® were also obtained from literature. Healthy normotensive New Zealand rabbits were topically treated with a single drop of 0.15% brimonidine tartrate and normotensive beagle dogs were treated with a single drop of Xalatan®. At pre-determined time intervals, IOP was measured and aqueous humor samples were obtained from a satellite group of animals. Population based PKPD modeling was performed to describe the IOP data and the chosen model was extended to predict the IOP in patients. Baseline IOP clearly depicts a distinctive circadian rhythm in rabbits versus human. An aqueous humor dynamics based physiological model was developed to describe the baseline diurnal IOP across species. Model was extended to incorporate the effect of drug administration on baseline IOP in rabbits and dogs. The translational model with substituted human aqueous humor dynamic parameters predicted IOP in patients following drug treatment. A physiology based mechanistic PKPD model was developed to describe the baseline and post-treatment IOP in animals. The preclinical PKPD model was successfully translated to predict IOP in patients with glaucoma or OHT and can be applied in assisting dose and treatment selection and predicting outcome of glaucoma clinical trials.

Mechanistic Pharmacokinetic-Pharmacodynamic Modeling of BACE1 Inhibition in Monkeys: Development of a Predictive Model for Amyloid Precursor Protein Processing

This study was conducted to determine the pharmacokinetics (PK) and pharmacodynamics (PD) of two novel inhibitors of β-site amyloid precursor protein (APP)-cleaving enzyme (BACE1), GNE-629 [(4S,4a'S,10a'S)-2-amino-8'-(2-fluoropyridin-3-yl)-1-methyl-3',4',4a',10a'-tetrahydro-1'H-spiro[imidazole-4,10'-pyrano[4,3-b]chromen]-5(1H)-one] and GNE-892 [(R)-2-amino-1,3',3'-trimethyl-7'-(pyrimidin-5-yl)-3',4'-dihydro-2'H-spiro[imidazole-4,1'-naphthalen]-5(1H)-one], and to develop a PK-PD model to predict in vivo effects based solely on in vitro activity and PK. GNE-629 and GNE-892 concentrations and PD biomarkers including amyloid β (Aβ) in the plasma and cerebrospinal fluid (CSF), and secreted APPβ (sAPPβ) and secreted APPα (sAPPα) in the CSF were measured after a single oral administration of GNE-629 (100 mg/kg) or GNE-892 (30 or 100 mg/kg) in cynomolgus monkeys. A mechanistic PK-PD model was developed to simultaneously characterize the plasma Aβ and CSF Aβ, sAPPα, and sAPPβ using GNE-629 in vivo data. This model was used to predict the in vivo effects of GNE-892 after adjustments based on differences in in vitro cellular activity and PK. The PK-PD model estimated GNE-629 CSF and free plasma IC₅₀ of 0.0033 μM and 0.065 μM, respectively. These differences in CSF and free plasma IC₅₀ suggest that different mechanisms are involved in Aβ formation in these two compartments. The predicted in vivo effects for GNE-892 using the PK-PD model were consistent with the observed data. In conclusion, a PK-PD model was developed to mechanistically describe the effects of BACE1 inhibition on Aβ, sAPPβ, and sAPPα in the CSF, and Aβ in the plasma. This model can be used to prospectively predict in vivo effects of new BACE1 inhibitors using just their in vitro activity and PK data.

Mechanism-based PK–PD model for the prolactin biological system response following an acute dopamine inhibition challenge: quantitative extrapolation to humans

The aim of this investigation was to develop a mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) model for the biological system prolactin response following a dopamine inhibition challenge using remoxipride as a paradigm compound. After assessment of baseline variation in prolactin concentrations, the prolactin response of remoxipride was measured following (1) single intravenous doses of 4, 8 and 16 mg/kg and (2) following double dosing of 3.8 mg/kg with different time intervals. The mechanistic PK-PD model consisted of: (i) a PK model for remoxipride concentrations in brain extracellular fluid; (ii) a pool model incorporating prolactin synthesis, storage in lactotrophs, release into- and elimination from plasma; (iii) a positive feedback component interconnecting prolactin plasma concentrations and prolactin synthesis; and (iv) a dopamine antagonism component interconnecting remoxipride brain extracellular fluid concentrations and stimulation of prolactin release. The most important findings were that the free brain concentration drives the prolactin release into plasma and that the positive feedback on prolactin synthesis in the lactotrophs, in contrast to the negative feedback in the previous models on the PK-PD correlation of remoxipride. An external validation was performed using a dataset obtained in rats following intranasal administration of 4, 8, or 16 mg/kg remoxipride. Following simulation of human remoxipride brain extracellular fluid concentrations, pharmacodynamic extrapolation from rat to humans was performed, using allometric scaling in combination with independent information on the values of biological system specific parameters as prior knowledge. The PK-PD model successfully predicted the system prolactin response in humans, indicating that positive feedback on prolactin synthesis and allometric scaling thereof could be a new feature in describing complex homeostatic mechanisms.

Abstract A37: Development of biologics targeting soluble ligands: Novel biomarker and PK-PD analyzes examining free and total ligand profile following treatment with carlumab (anti-CCL2 mAb).

Abstract Background: Despite the large numbers of antibodies targeting soluble ligands in development in oncology and other therapeutic areas, very few reports have described pharmacodynamic (PD)/ mechanism of action (MOA) biomarkers of free ligand or total (antibody-complexed) ligand and their PK-PD relationship. Carlumab is a human IgG1 monoclonal antibody that binds the chemokine CCL2, which is a potent chemoattractant for tumor associated macrophages and promotes tumor growth and metastasis. Therapeutic targeting of CCL2 was based on the hypothesis that carlumab binding would inhibit chemokine activity and block tumor inflammation and macrophage differentiation thereby impairing tumor growth and metastases. Because proof of concept (POC) is a major milestone in early drug development, the objective of this study was to develop key PD/MOA biomarkers to facilitate the clinical evaluation of POC for carlumab. This required the development of robust analytical assays to accurately measure free and total CCL2 concentrations in the serum, and mechanistic PK-PD modeling for data analysis. Methods: Carlumab was evaluated in three oncology clinical studies (as monotherapy in a Phase 1 first-in-human trial in patients with solid tumors, a Phase 1b chemotherapy combination study, and as a single agent Phase 2a study in patients with advanced prostate cancer). Biomarkers evaluated included free and total CCL2 concentrations in serum, a broad panel of soluble biomarkers, bone turnover markers, and circulating tumor cell (CTC) enumeration. Sequential tumor biopsies in ten patients from Phase 1 study yielded 4 paired specimens for immunohistochemical analysis of tumor associated macrophages (TAMs). A mechanistic PK-PD model that simultaneously characterized free and total CCL2, and carlumab concentrations in serum was used to estimate biologically effective doses that would inhibit CCL2 signaling. Results: Analysis of CCL2 levels following carlumab administration revealed a rapid fall in free CCL2 as expected; however, post-treatment free CCL2 levels rapidly rebounded and quickly exceeded pretreatment serum concentrations. Two different analytical methods showed that carlumab suppressed CCL2 levels for only ∼24 hrs followed by a sustained increase in CCL2 concentration with subsequent treatment. These surprising results suggest that carlumab was ineffective at neutralizing free CCL2. PK-PD modeling confirmed the transient suppression of free CCL2 consistent with a higher carlumab dissociation constant (Kd) for CCL2 binding in vivo. Finally, carlumab did not affect other biomarkers including bone turnover markers or CTC numbers, consistent with an inability to impact CCL2 signaling. No evidence of clinical efficacy was observed in any of carlumab clinical trials. Conclusion: Development of robust analytical assays to measure free and total CCL2 concentration and utilization of mechanistic PK-PD modeling facilitated the clinical evaluation of POC for carlumab. The unexpected increase in free CCL2 concentration and the lack of CCL2 target suppression likely explain the absence of carlumab clinical activity. Supportive biomarker analyzes and mechanistic PK-PD modeling are important components of the early development clinical plan for developing biologics against soluble ligands. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr A37.

Systems Pharmacology: Bridging Systems Biology and Pharmacokinetics-Pharmacodynamics (PKPD) in Drug Discovery and Development

Mechanistic PKPD models are now advocated not only by academic and industrial researchers, but also by regulators. A recent development in this area is based on the growing realisation that innovation could be dramatically catalysed by creating synergy at the interface between Systems Biology and PKPD, two disciplines which until now have largely existed in 'parallel universes' with a limited track record of impactful collaboration. This has led to the emergence of systems pharmacology. Broadly speaking, this is the quantitative analysis of the dynamic interactions between drug(s) and a biological system to understand the behaviour of the system as a whole, as opposed to the behaviour of its individual constituents; thus, it has become the interface between PKPD and systems biology. It applies the concepts of Systems Engineering, Systems Biology, and PKPD to the study of complex biological systems through iteration between computational and/or mathematical modelling and experimentation. Application of systems pharmacology can now impact across all stages of drug research and development, ranging from very early discovery programs to large-scale Phase 3/4 patient studies, and has the potential to become an integral component of a new 'enhanced quantitative drug discovery and development' (EQD3) R&D paradigm.

PK–PD Modeling of Protein Drugs: Implications in Assay Development

Pharmacokinetic-pharmacodynamic (PK-PD) modeling is an integral part of the preclinical and clinical development of protein drugs. Bioanalytical data from appropriately selected and well-characterized PK and PD biomarker assays can be incorporated into mechanistic PK-PD models and allow a quantitative relationship between protein drug exposure, target modulation, and biochemical, physiological and pathophysiological effects to be established. The selection of PD biomarkers that assess target engagement and modulation in the extracellular milieu and downstream cellular effects can provide proof-of-mechanism and define the magnitude and duration of target modulation following drug administration. The PK-PD data can provide an important link between magnitude of target modulation and clinical efficacy and safety outcomes, and guide the selection of doses and dosing schedules for clinical trials. In this article, approaches to the selection and development of fit-for-purpose, PK and PD assays for protein drugs are reviewed, and the applications of the assay results in PK-PD models are discussed.

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

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. 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. 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. 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. 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. 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.

Mechanism-Based Pharmacokinetic-Pharmacodynamic Models of In Vitro Fungistatic and Fungicidal Effects against Candida albicans

Mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) models describing the fungistatic activity of fluconazole and the fungicidal activity of caspofungin were developed using dynamic in vitro models. Antifungal-drug pharmacokinetics was simulated in vitro, assuming a one-compartment model with an elimination half-life of 3 h and using a wide (1 to 10,000) range of initial concentrations. The number of CFUs over time was determined for up to 31 h and used for PK-PD modeling. A model incorporating first-order natural growth and natural death, plus a maximum number of viable Candida cells, was used to characterize Candida growth in the absence of a drug. Fluconazole was considered to inhibit Candida growth and caspofungin to stimulate Candida death according to an Emax pharmacodynamic model. The data were analyzed with Nonmem, using a population approach. A good fit of the data was obtained with satisfactory estimates of PK-PD parameters, especially with drug concentrations producing 50% of the maximal effect: 50% inhibitory concentrations for fluconazole growth inhibition and 50% effective concentrations for caspofungin death stimulation. In conclusion, mechanistic PK-PD models were successfully developed to describe, respectively, the fungistatic and fungicidal activities of fluconazole and caspofungin in vitro. These models provide much better information on the drug effects over time than the traditional PK-PD index based on MICs. However, they need to be further characterized.

The use of mechanistic DM‐PK‐PD modelling to assess the power of pharmacogenetic studies –CYP2C9 and warfarin as an example

To assess the power of in vivo studies needed to discern the effect of genotype on pharmacokinetics (PK) and pharmacodynamics (PD) using CYP2C9 and (S)-warfarin as an example. Information on the in vitro metabolism of (S)-warfarin and genetic variation in CYP2C9 was incorporated into a mechanistic population-based PK-PD model. The influence of study design on the ability to detect significant differences in PK (AUC(0-12 h)) and PD (AUEC(0-12 h) INR) between CYP2C9 genotypes was investigated. A study size of 90 (based on the natural abundance of genotypes and uniform dosage) was required to achieve 80% power to discriminate the PK of (S)-warfarin between wild type (*1/*1) and the combination of all other genotypes. About 250 subjects were needed to detect a difference in anticoagulant response. The power to detect differences between specific genotypes was much lower. Analysis of experimental comparisons of the PK or PD between wild-type and other individual genotypes indicated that only 21% of cases (20 of 95 comparisons within 11 PD and four PK-PD studies) reported statistically significant differences. This was similar to the percentage expected from our simulations (20%, chi(2) test, P = 0.80). Simulations of studies enriched with specific genotypes indicated that only three and five subjects were required to detect differences in PK and PD between wild type and the *3/*3 genotype, respectively. The utilization of prior information (including in vivo enzymology) in clinical trial simulations can guide the design of subsequent in vivo studies of the impact of genetic polymorphisms, and may help to avoid costly, inconclusive outcomes.

Dose-Incidence Modeling: Consequences of Linking Quantal Measures of Response to Depletion of Critical Tissue Targets

In developing mechanistic PK-PD models, incidence of toxic responses in a population has to be described in relation to measures of biologically effective dose (BED). We have developed a simple dose-incidence model that links incidence with BED for compounds that cause toxicity by depleting critical cellular target molecules. The BED in this model was the proportion of target molecule adducted by the dose of toxic compound. Our modeling approach first estimated the proportion depleted for each dose and then calculated the tolerance distribution for toxicity in relation to either administered dose or log of administered dose. We first examined cases where the mean of the tolerance distribution for toxicity occurred when a significant proportion of target had been adducted (i.e., more than half). When a normal distribution was assumed to exist for the relationship of incidence and BED, the tolerance distribution based on administered dose for these cases becomes asymmetrical and logarithmic transformations of the administered dose axis lead to a more symmetrical distribution. These linked PK-PD models for tissue reactivity, consistent with conclusions from other work for receptor binding models (Lutz et al., 2005), indicate that log normal distributions with administered dose may arise from normal distributions for BED and nonlinear kinetics between BED and administered dose. These conclusions are important for developing biologically based dose response (BBDR) models that link incidences of toxicity or other biological responses to measures of BED.

A semimechanistic and mechanistic population PK-PD model for biomarker response to ibandronate, a new bisphosphonate for the treatment of osteoporosis.

Ibandronate, a highly potent nitrogen-containing bisphosphonate, is the subject of an ongoing clinical development programme that aims to maximize the potential of simplified, less frequent oral and intravenous (i.v.) administration in osteoporosis. A modelling and simulation project was undertaken to characterize further the clinical pharmacology of ibandronate and identify convenient intermittent oral and i.v. regimens for clinical evaluation. Using selected data from clinical studies involving 174 women with postmenopausal osteoporosis (PMO), a classical multicompartmental pharmacokinetic-pharmacodynamic (PK-PD) model was developed that accurately described the PK of i.v. ibandronate in plasma and urine and urinary excretion of the C-telopeptide of the alpha chain of type I collagen (uCTX), a sensitive biomarker of PD response to ibandronate. To reduce processing times, the classical PK-PD model was simplified using a "kinetics of drug action" or kinetic (K)-PD model (i.e. a dose-response model as opposed to a dose-concentration-response model). The performance of the K-PD model was evaluated by fitting data simulated with the PK-PD model under various dosing regimens. The simplified model produced a virtually indistinguishable fit of the data from that of the PK-PD model. The K-PD model was extended to consider the influence of supplemental therapy (calcium with or without vitamin D) on the PD response and validated by retrospectively simulating the uCTX response in a prior Phase III and Phase II/III study of i.v. ibandronate, given once every 3 months, in 3380 women with PMO. The observed median uCTX responses at the scheduled assessment points in the completed studies were within the distribution of the simulated responses. The K-PD model for i.v. ibandronate was extended further to allow simultaneous fitting of uCTX responses after i.v. and oral administration in 676 postmenopausal women with osteoporosis, and validated by retrospectively simulating the data observed in a Phase I study of oral daily ibandronate in 180 women with PMO. The K-PD model adequately described the uCTX response after oral dosing. This validated K-PD model is currently being used to evaluate a range of novel intermittent oral and i.v. ibandronate regimens in an ongoing clinical development programme.