Development of a quantitative semi-mechanistic model of Alzheimer's disease based on the amyloid/tau/neurodegeneration framework (the Q-ATN model).

INTRODUCTION: A quantitative model of Alzheimer's disease (AD) based on the amyloid/tau/neurodegeneration biomarker framework (Q-ATN model) was developed to sequentially link amyloid positron emission tomography (PET), tau PET, medial temporal cortical thickness, and clinical outcome (Clinical Dementia Rating - Sum of Boxes; CDR-SB). METHODS: Published data and biologically plausible mechanisms were used to construct, calibrate, and validate the model. Clinical trial simulations were performed for different anti-amyloid antibodies, including a 5-year simulation of subcutaneous gantenerumab treatment. RESULTS: The simulated time-course of biomarkers and CDR-SB was consistent with natural history studies and described the effects of several anti-amyloid antibodies observed in trials with positive and negative (or non-significant) outcomes. The 5-year simulation predicts that the beneficial effects of continued anti-amyloid treatment should increase markedly over time. DISCUSSION: The Q-ATN model offers a novel approach for linking amyloid PET to CDR-SB, and provides theoretical support for the potential clinical benefit of anti-amyloid therapy. HIGHLIGHTS: A semi-mechanistic model was developed to link amyloid/tau/neurodegeneration biomarkers to clinical outcome (Q-ATN model). The Q-ATN model describes the disease progression seen in natural history studies. Model simulations agree well with mean data from the aducanumab EMERGE study. A 5-year simulation of gantenerumab predicts greater benefit with longer treatment.

In silico exploration of amyloid-related imaging abnormalities in the gantenerumab open-label extension trials using a semi-mechanistic model.

Introduction: Amyloid-related imaging abnormalities with edema/effusion (ARIA-E) are commonly observed with anti-amyloid therapies in Alzheimer's disease. We developed a semi-mechanistic, in silico model to understand the time course of ARIA-E and its dose dependency. Methods: Dynamic and statistical analyses of data from 112 individuals that experienced ARIA-E in the open-label extension of SCarlet RoAD (a study of gantenerumab in participants with prodromal Alzheimer's disease) and Marguerite RoAD (as study of Gantenerumab in participants with mild Alzheimer's disease) studies were used for model building. Gantenerumab pharmacokinetics, local amyloid removal, disturbance and repair of the vascular wall, and ARIA-E magnitude were represented in the novel vascular wall disturbance (VWD) model of ARIA-E. Results: The modeled individual-level profiles provided a good representation of the observed pharmacokinetics and time course of ARIA-E magnitude. ARIA-E dynamics were shown to depend on the interplay between drug-mediated amyloid removal and intrinsic vascular repair processes. Discussion: Upon further refinement and validation, the VWD model could inform strategies for dosing and ARIA monitoring in individuals with an ARIA-E history.

Disease Modeling and Model-Based Meta-Analyses to Define a New Direction for a Phase III Program of Gantenerumab in Alzheimer's Disease.

Selecting the right dose is a significant challenge in designing clinical development programs, especially for slowly progressing diseases lacking predictive biomarkers of efficacy that may require long-term treatment to assess clinical benefit. Gantenerumab, a fully human monoclonal antibody (mAb) that binds to aggregated amyloid-beta, was tested in two 24-month phase III studies (NCT01224106, NCT02051608) in participants with prodromal and mild Alzheimer's disease (AD), respectively. Dosing in the first phase III study was suspended after a preplanned interim futility analysis in 2014. Subsequently, a dose-response relationship was observed in a subgroup of fast AD progressors that, together with contemporary aducanumab (another anti-amyloid-beta mAb) data, indicated higher doses may be needed for clinical efficacy. The gantenerumab phase III studies were therefore transformed into dose-finding, open-label extension (OLE) trials. Two exposure-response models were developed to support dose selection via simulations for the OLEs: a pharmacokinetics (PK)/PET (positron emission tomography) model describing amyloid removal using PET data from low-dose gantenerumab and high-dose aducanumab, and a PK/ARIA-E (amyloid-related imaging abnormalities-edema) model describing the occurrence of ARIA-E events leveraging an existing bapineuzumab model. Multiple regimens were designed to gradually up-titrate participants to the target dose of 1,200 mg gantenerumab every 4 weeks to mitigate the increased risk of ARIA-E events that may be associated with higher doses of anti-amyloid-beta antibodies. Favorable OLE data that matched well with model predictions supported the decision to continue the gantenerumab clinical development program and further apply model-based analytical techniques to optimize the design of new phase III studies.

Use of quantitative clinical pharmacology to improve early clinical development success in neurodegenerative diseases.

INTRODUCTION: The success rate of pharmaceutical Research & Development (R&D) is much lower compared to other industries such as micro-electronics or aeronautics with the probability of a successful clinical development to approval in central nervous system (CNS) disorders hovering in the single digits (7%). Areas covered: Inspired by adjacent engineering-based industries, we argue that quantitative modeling in CNS R&D might improve success rates. We will focus on quantitative techniques in early clinical development, such as PharmacoKinetic-PharmacoDynamic modeling, clinical trial simulation, model-based meta-analysis and the mechanism-based physiology-based pharmacokinetic modeling, and quantitative systems pharmacology. Expert commentary: Mechanism-based computer modeling rely less on existing clinical datasets, therefore can better generalize than Big Data analytics, including prospectively and quantitatively predicting the clinical outcome of new drugs. More specifically, exhaustive post-hoc analysis of failed trials using individual virtual human trial simulation could illuminate underlying causes such as lack of sufficient functional target engagement, negative pharmacodynamic interactions with comedications and genotypes, and mismatched patient population. These insights are beyond the capacity of artificial intelligence (AI) methods as they are many more possible combinations than subjects. Unlike 'black box' approaches in AI, mechanism-based platforms are transparent and based on biologically sound assumptions that can be interrogated.

Mathematical Disease Progression Modeling in Type 2/3 Spinal Muscular Atrophy.

INTRODUCTION: We propose a mathematical model to empirically describe spinal muscular atrophy (SMA) progression assessed by the 3 domains of the motor function measure (MFM) scale. The model implements development and deterioration of muscle function. METHODS: Nonlinear mixed-effects modeling was applied to data from 2 observational studies and 1 prospective clinical efficacy study comprising 190 healthy participants and 277 patients with type 2/3 SMA. RESULTS: The model evidenced correlations between parameter estimates for different MFM domains. Slower development in MFM domain D1 (standing and transfers) was associated with faster deterioration for MFM domains D2 (proximal and axial motricity) and D3 (distal motor function). DISCUSSION: The model describes all individual data well, although sparseness and variability of observational data prevented numerically stable estimation of parameters. Treatment duration in clinical studies was too limited to determine a proper drug-effect model that could differentiate between symptomatic and disease modifying effects. Muscle Nerve 58: 528-535, 2018.

A semi-mechanistic model of bone mineral density and bone turnover based on a circular model of bone remodeling.

Development of novel therapies for bone diseases can benefit from mathematical models that predict drug effect on bone remodeling biomarkers. Therefore, a bone cycle model (BCM) was developed that takes into consideration the concept of the basic multicellular unit and the dynamic equilibrium of bone remodeling. The model is a closed form cyclical model with four compartments representing resorption, formation, primary mineralization, and secondary mineralization. Equations describing the time course of bone turnover biomarkers were developed using the flow rate of bone cycle units (BCU) between the compartments or the amount of BCU in each compartment. A disease progression model representing bone loss in osteoporosis, a vitamin D and calcium supplementation (placebo) model, and a drug model for antiresorptive treatments were added to the model. Initial model parameter values were derived from published bone turnover data. The BCM accurately described biomarker-time profiles in postmenopausal women receiving either placebo or bisphosphonate treatment. The slow continual increase in bone mineral density (BMD) observed after 1 year of treatment was accurately described when changes in bone turnover were combined with increases in mineralization. For this purpose, the secondary mineralization compartment was replaced by three catenary chain compartments representing increasing mineral content. The refined BCM satisfactorily predicted biomarker profiles after long-term (10-year) bisphosphonate treatment. Furthermore, the model successfully described individual bone turnover markers and BMD results following treatment with denosumab in postmenopausal women. Analyses with this model could be used to optimize dosing regimens and to predict effects of novel osteoporotic treatments.

A drug-disease model describing the effect of oseltamivir neuraminidase inhibition on influenza virus progression.

A population drug-disease model was developed to describe the time course of influenza virus with and without oseltamivir treatment and to investigate opportunities for antiviral combination therapy. Data included viral titers from 208 subjects, across 4 studies, receiving placebo and oseltamivir at 20 to 200 mg twice daily for 5 days. A 3-compartment mathematical model, comprising target cells infected at rate ß, free virus produced at rate p and cleared at rate c, and infected cells cleared at rate δ, was implemented in NONMEM with an inhibitory Hill function on virus production (p), accounting for the oseltamivir effect. In congruence with clinical data, the model predicts that the standard 75-mg regimen initiated 2 days after infection decreased viral shedding duration by 1.5 days versus placebo; the 150-mg regimen decreased shedding by an additional average 0.25 day. The model also predicts that initiation of oseltamivir sooner postinfection, specifically at day 0.5 or 1, results in proportionally greater decreases in viral shedding duration of 5 and 3.5 days, respectively. Furthermore, the model suggests that combining oseltamivir (acting to subdue virus production rate) with an antiviral whose activity decreases viral infectivity (ß) results in a moderate additive effect dependent on therapy initiation time. In contrast, the combination of oseltamivir with an antiviral whose activity increases viral clearance (c) shows significant additive effects independent of therapy initiation time. The utility of the model for investigating the pharmacodynamic effects of novel antivirals alone or in combination on emergent influenza virus strains warrants further investigation.

Neuraminidase inhibitors for treatment of human and avian strain influenza: A comparative modeling study.

Treatment of seasonal influenza viral infections using antivirals such as neuraminidase inhibitors (NAIs) has been proven effective if administered within 48h post-infection. However, there is growing evidence that antiviral treatment of infections with avian-derived strains even as late as 6 days post-infection (dpi) can significantly reduce infection severity and duration. Using a mathematical model of in-host influenza viral infections which can capture the kinetics of both a short-lived, typical, seasonal infection and a severe infection exhibiting sustained viral titer, we explore differences in the effects of NAI treatment on both types of influenza viral infections. Comparison of our model's behavior against experimental data from patients naturally infected with avian strains yields estimates for the times at which patients were infected that are consistent with those reported by the patients, and estimates of drug efficacies that are lower for patients who died than for those who recovered. In addition, our model suggests that the sustained, high, viral titers often seen in more severe influenza virus infections are the reason why antiviral treatment delayed by as much as 6 dpi will still lead to reduced viral titers and shortened illness. We conclude that NAIs may be an effective and beneficial treatment strategy against more severe strains of influenza virus characterized by high, sustained, viral titers. We believe that our mathematical model will be an effective tool in guiding treatment of severe influenza viral infections with antivirals.

Exploring cell tropism as a possible contributor to influenza infection severity.

Several mechanisms have been proposed to account for the marked increase in severity of human infections with avian compared to human influenza strains, including increased cytokine expression, poor immune response, and differences in target cell receptor affinity. Here, the potential effect of target cell tropism on disease severity is studied using a mathematical model for in-host influenza viral infection in a cell population consisting of two different cell types. The two cell types differ only in their susceptibility to infection and rate of virus production. We show the existence of a parameter regime which is characterized by high viral loads sustained long after the onset of infection. This finding suggests that differences in cell tropism between influenza strains could be sufficient to cause significant differences in viral titer profiles, similar to those observed in infections with certain strains of influenza A virus. The two target cell mathematical model offers good agreement with experimental data from severe influenza infections, as does the usual, single target cell model albeit with biologically unrealistic parameters. Both models predict that while neuraminidase inhibitors and adamantanes are only effective when administered early to treat an uncomplicated seasonal infection, they can be effective against more severe influenza infections even when administered late.

Interactive visualization and communication for increased impact of pharmacometrics.

The art of pharmacometric activities (also called modeling and simulation) is in developing the appropriate model to describe the data at hand. In a subsequent step, outputs from the model are frequently used for quantitative decision making: what is the appropriate dose and dosing regimen, should the dose be individualized, what percentage of patients can be expected to reach therapeutic levels of exposure, and more. However, a good model does not automatically lead to a good decision-making process, which implies clinical team decisions on the population to be treated, the clinical end point, the dose, and the dosing regimen. The authors argue that seeing is believing: interactive visualization helps the communication process of clinical teams substantially. A flow of arguments guided by visualization of the model-predicted consequences of choosing a particular setup makes the discussion transparent and enhances quantitative decision making. The use of interactive visualization tools (such as the Berkeley Madonna software system) for pharmacometric results facilitates effective communication, enhanced quantitative decision making, and thus increases the impact of pharmacometrics in drug development.

Population pharmacokinetic/pharmacodynamic model for C.E.R.A. in both ESA-naive and ESA-treated chronic kidney disease patients with renal anemia.

This study aimed to develop a population pharmacokinetic/pharmacodynamic (PK/PD) model for C.E.R.A., a continuous erythropoietin receptor activator. C.E.R.A. is administered via intravenous (IV) and subcutaneous (SC) routes once every 2 weeks (Q2W) or once every 4 weeks (Q4W), respectively, to correct or maintain hemoglobin levels in chronic kidney disease (CKD) patients. Population models were specified to describe C.E.R.A. (PK) and hemoglobin (PD) concentrations over time, using data from 3 phase III, open-label, randomized, parallel-group, multicenter studies that examined IV or SC C.E.R.A. administration Q2W and Q4W in erythropoiesis-stimulating agent (ESA)-naive and ESA-treated patients. C.E.R.A. PK was described by a 1-compartment model: drug clearance = 0.75 L/d, volume of distribution = 4.72 L, and half-life = 105 hours in accordance with previous reported values. The PD model, a life span sequential PK/PD model, adequately described hemoglobin data. Dosing schedule, administration route, and study type did not affect drug-related PD parameters or system-specific parameters (eg, red blood cell life span). This model adequately described C.E.R.A.'s PK and PD properties according to C.E.R.A. posology, thus permitting simulations exploring alternative drug administration scenarios. It supports use of C.E.R.A. IV and SC; Q2W for anemia correction in ESA-Naïve CKD patients and monthly administration in the hemoglobin maintenance phase.

Assessment of neuropsychiatric adverse events in influenza patients treated with oseltamivir: a comprehensive review.

After reports from Japan of neuropsychiatric adverse events (NPAEs) in children taking oseltamivir phosphate (hereafter referred to as oseltamivir [Tamiflu; F. Hoffmann-La Roche Ltd, Basel, Switzerland]) during and after the 2004--5 influenza season, Roche explored possible reasons for the increase in reporting rate and presented regular updates to the US FDA and other regulatory authorities. This review summarizes the results of a comprehensive assessment of the company's own preclinical and clinical studies, post-marketing spontaneous adverse event reporting, epidemiological investigations utilizing health claims and medical records databases and an extensive review of the literature, with the aim of answering the following questions: (i) what the types and rates of neuropsychiatric abnormalities reported in patients with influenza are, and whether these differ in patients who have received oseltamivir compared with those who have not; (ii) what levels of oseltamivir and its active metabolite, oseltamivir carboxylate are achieved in the CNS; (iii) whether oseltamivir and oseltamivir carboxylate have pharmacological activity in the CNS; and (iv) whether there are genetic differences between Japanese and Caucasian patients that result in different levels of oseltamivir and/or oseltamivir carboxylate in the CNS, differences in their metabolism or differences in their pharmacological activity in the CNS. In total, 3051 spontaneous reports of NPAEs were received by Roche, involving 2466 patients who received oseltamivir between 1999 and 15 September 2007; 2772 (90.9%) events originated from Japan, 190 (6.2%) from the US and 89 (2.9%) from other countries. During this period, oseltamivir was prescribed to around 48 million people worldwide. Crude NPAE reporting rates (per 1,000,000 prescriptions) in children (aged < or =16 years) and adults, respectively, were 99 and 28 events in Japan and 19 and 8 in the US. NPAEs were more commonly reported in children (2218 events in 1808 children aged < or =16 years vs 833 in 658 adults) and generally occurred within 48 hours of the onset of influenza illness and initiation of treatment. After categorizing the reported events according to International Classification of Diseases (9th edition) codes, abnormal behaviour (1160 events, 38.0%) and delusions/perceptual disturbances (661 events, 21.7%) were the largest categories of events, and delirium or delirium-like events (as defined by the American Psychiatric Association) were very common in most categories. No difference in NPAE reporting rates between oseltamivir and placebo was found in phase III treatment studies (0.5% vs 0.6%). Analyses of US healthcare claims databases showed the risk of NPAEs in oseltamivir-treated patients (n = 159,386) was no higher than those not receiving antivirals (n = 159,386). Analysis of medical records in the UK General Practice Research Database showed that the adjusted relative risk of NPAEs in influenza patients was significantly higher (1.75-fold) than in the general population. Based on literature reports, NPAEs in Japanese and Taiwanese children with influenza have occurred before the initiation of oseltamivir treatment; events were also similar to those occurring after the initiation of oseltamivir therapy. No clinically relevant differences in plasma pharmacokinetics of oseltamivir and its active metabolite oseltamivir carboxylate were noted between Japanese and Caucasian adults or children. Penetration into the CNS of both oseltamivir and oseltamivir carboxylate was low in Japanese and Caucasian adults (cerebrospinal fluid/plasma maximum concentration and area under the plasma concentration-time curve ratios of approximately 0.03), and the capacity for converting oseltamivir to oseltamivir carboxylate in rat and human brains was low. In animal autoradiography and pharmacokinetic studies, brain : plasma radioactivity ratios were generally 20% or lower. Animal studies showed no specific CNS/behavioural effects after administration of doses corresponding to > or =100 times the clinical dose. Oseltamivir or oseltamivir carboxylate did not interact with human neuraminidases or with 155 known molecular targets in radioligand binding and functional assays. A review of the information published to date on functional variations of genes relevant to oseltamivir pharmacokinetics and pharmacodynamics and simulated gene knock-out scenarios did not identify any plausible genetic explanations for the observed NPAEs. The available data do not suggest that the incidence of NPAEs in influenza patients receiving oseltamivir is higher than in those who do not, and no mechanism by which oseltamivir or oseltamivir carboxylate could cause or worsen such events could be identified.

Population pharmacokinetics of oseltamivir when coadministered with probenecid.

Oseltamivir is a potent, selective, oral neuraminidase inhibitor for the treatment and prophylaxis of influenza. Plasma concentrations of the active metabolite, oseltamivir carboxylate, are increased in the presence of probenecid, suggesting that the combination could allow for the use of reduced doses of oseltamivir. To investigate this proposal, we developed a population pharmacokinetic model and simulated the pharmacokinetics of candidate combination regimens of oral oseltamivir (45 mg and 30 mg twice a day) plus oral probenecid (500 mg/6 hourly). Probenecid plus oseltamivir 45 mg achieved all the pharmacokinetic parameters expected of oseltamivir alone, but combination with oseltamivir 30 mg and dose interval extension approaches did not. An oseltamivir-probenecid combination may compromise tolerability and enhance the potential for drug interactions. In addition, increased dosing requirements may affect compliance and attainment of optimal oseltamivir exposure, potentially facilitating the emergence of viral strains with reduced susceptibility to oseltamivir. These factors, set alongside increased capacity for oseltamivir production, should be carefully considered before an oseltamivir-probenecid combination is used.

An integrated glucose-insulin model to describe oral glucose tolerance test data in type 2 diabetics.

An integrated model for the glucose-insulin system describing oral glucose tolerance test data was developed, extending on a previously introduced model for intravenous glucose provocations. Model extensions comprised the description of glucose absorption by a chain of transit compartments with a mean transit time of 35 minutes, a bioavailability of 80%, and a representation of the incretin effect, expressed as a direct effect of the glucose absorption rate on insulin secretion. The ability of the model to predict the incretin effect was assessed by simulating the observed difference in insulin response following an oral glucose tolerance test compared with an isoglycemic glucose infusion mimicking an oral glucose tolerance test profile. The extension of the integrated glucose-insulin model to gain information from oral glucose tolerance test data considerably expands its range of applications because the oral glucose tolerance test is one of the most common glucose challenge experiments for assessing the efficacy of hypoglycemic agents in clinical drug development.

An integrated model for glucose and insulin regulation in healthy volunteers and type 2 diabetic patients following intravenous glucose provocations.

An integrated model for the regulation of glucose and insulin concentrations following intravenous glucose provocations in healthy volunteers and type 2 diabetic patients was developed. Data from 72 individuals were included. Total glucose, labeled glucose, and insulin concentrations were determined. Simultaneous analysis of all data by nonlinear mixed effect modeling was performed in NONMEM. Integrated models for glucose, labeled glucose, and insulin were developed. Control mechanisms for regulation of glucose production, insulin secretion, and glucose uptake were incorporated. Physiologically relevant differences between healthy volunteers and patients were identified in the regulation of glucose production, elimination rate of glucose, and secretion of insulin. The model was able to describe the insulin and glucose profiles well and also showed a good ability to simulate data. The features of the present model are likely to be of interest for analysis of data collected in antidiabetic drug development and for optimization of study design.

A multiphase model of the dynamics of HBV infection in HBeAg-negative patients during pegylated interferon-alpha2a, lamivudine and combination therapy.

Using a multiphase bio-mathematical model, we studied the dynamics of hepatitis B virus (HBV) infection in 72 HBeAg-negative patients who received 48 weeks of either lamivudine (3TC; 25 patients); pegylated interferon-alpha2a (peg-IFN-alpha2a) 180 mg weekly plus 3TC (23 patients), or peg-IFN-alpha2a 180 mg weekly plus placebo (24 patients). During the first month of therapy most of the 3TC -/+ peg-IFN-alpha2a treated patients showed a multiphase decay of viral load: during the first two phases, where we hypothesized a direct inhibition of virus production, the mean viral production per infected cell was reduced by 2.22 log10 and 2.36 log10, respectively. At variance, peg-IFN-alpha2a treated patients had a biphasic profile: the first phase HBV DNA decline was slower than that observed in 3TC patients (mean HBV DNA t(1/2) = 1.6 +/- 1.1 days and 9.5 +/- 3.0 h, respectively) and the direct antiviral effect reduced virus production by 1.14 log10. From day 14 onwards (third or second phase according to multi- or biphasic patterns), HBV DNA declined mainly because of the infected hepatocyte clearance that slowed down in approximately 50% of the patients from day 35, possibly because of a negative feedback on the immune system activity. Computing the number of infected cells at the end of therapy we found that peg-IFN-alpha2a and 3TC monotherapy determined a similar reduction of infected hepatocytes (mean: -3.3 log10), whereas there was a greater reduction in combination therapy patients (-5.0 versus -3.3 log10, P = 0.039). In conclusion, peg-IFN-alpha2a, in spite of having direct antiviral activity lower than that of 3TC, achieved a comparable reduction of infected hepatocytes, possibly because of a higher infected cell clearance rate.

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

AIMS: 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. METHODS AND RESULTS: 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. CONCLUSIONS: 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.