Exposure-Effect Population Model of Inolimomab, a Monoclonal Antibody Administered in First-Line Treatment for Acute Graft-Versus-Host Disease
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- Dartois, C., Freyer, G., Michallet, M. et al. Clin Pharmacokinet (2007) 46: 417. doi:10.2165/00003088-200746050-00004
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Background and objective
Inolimomab, a monoclonal antibody against interleukin (IL)-2Rα (CD25) has shown promising results in the treatment of corticosteroid-resistant acute graft-versus-host disease (GvHD). The objective of the present study was to characterise the pharmacokinetic and pharmacodynamic properties of inolimomab as first-line treatment in this condition.
The data came from 21 patients with acute GvHD (8 with an International Bone Marrow Transplant Registry [IBMTR] score of B, 11 with a score of C and 2 with a score of D) following haematopoietic stem cell transplantation after a median delay of 26 days (range 10–127 days). Inolimomab was administered at 0.1, 0.2, 0.3 or 0.4 mg/kg daily in association with methylprednisolone (2 mg/kg) for 8 or 16 days depending on the status at day 9. Then, for responder patients, administrations were continued three times weekly until day 28. Inolimomab concentrations and pharmacodynamic data (acute GvHD scores) were recorded during the study. The pharmacodynamic data were assessed in four grades according to the IBMTR and Glucksberg classification in parallel with Karnofsky scores. A population analysis was developed using a nonlinear mixedeffects model to define the pharmacokinetic model, to test covariates and, when apparent, to model the exposure-effect relationship by a proportional odds model. The modelling was finally qualified by a predictive check.
The best pharmacokinetic model was two-compartmental. For each score, the most demonstrative exposure-effect graphics linked the cumulative area under the concentration-time curve to cumulated probabilities of observing a specific score. This relationship was identified as a maximum effect model for the skin (with two patient subpopulations: sensitive/less sensitive) and a linear model for the intestinal tract and liver. No covariate was identified as influencing any of these parameters.
Inolimomab exposure-effect relationships as first-line treatment for acute GvHD have been identified and modelled. The discovered dose-effect relationship allows confirmation of the treatment response, thereby establishing the first step towards optimising the inolimomab dosage in future trials.
Allogeneic haematopoietic stem cell transplantation is an effective and curative treatment for many haematological malignancies related to the existence of a graft-versus-malignancy effect. However, it is frequently associated with graft-versus-host disease (GvHD), which is still responsible for a high rate of treatment-related mortality. Acute GvHD usually involves the skin, liver and intestinal tract, but lymphoid and haematopoietic tissues can also be affected. It is induced by alloreactive T cells from the donor, which react against the recipient’s tissues and organs. Standard GvHD prophylaxis consists of administering a combination of immunosuppressive drugs, ciclosporin and methotrexate being the classical combination. Other therapeutic approaches have been tested, including T-cell depletion, which can be performed in vivo or ex vivo. The incidence of GvHD decreases, but this is at the cost of a high risk of rejection and relapse associated with delayed immune reconstitution. The first-line treatment of acute GvHD is based on corticosteroids, usually methylprednisolone at the dose of 2–2.5 mg/kg/day. However, corticosteroid resistance is observed in ≊40% of patients and therefore requires alternative treatment.[6,7] No standard therapy really exists for corticosteroid-refractory acute GvHD. Therapy could be based on high-dose corticosteroids (10–15 mg/kg/day) either alone or in combination with antithymocyte globulins or monoclonal anti-T-cell preparations.[8–10] In some cases, although it cures acute GvHD, this treatment is responsible for strong immunosuppression, leading to an increased incidence of severe bacterial infections, viral infections, and an increased risk of Epstein-Barr virus-related lymphoproliferative disorders.[11,12] Because of its inhibitory effects on activated T cells, inolimomab (Leukotac®1, OPi SA, Limonest, France) could be useful for the treatment of acute GvHD. This murine monoclonal antibody specifically targets the α chain (CD25) of the interleukin-2 (IL-2) receptor. Activated T cells express the inducible IL-2Rα chain, whereas resting cells and their precursors do not. Consequently, fewer adverse experiences are expected owing to lower and more targeted immunosuppressive activity. Some clinical trials have already been performed in corticosteroid-resistant acute GvHD patients and have shown some promising results in terms of response and survival.[13–17]
A clinical trial of inolimomab, given in combination with corticosteroids, was conducted as initial therapy for acute GvHD. As the compound was well tolerated, this clinical trial was expected to show a better, longer and less heterogeneous overall response than would be expected in corticosteroid-resistant patients. This study presents the original population pharmacokinetic-pharmacodynamic modelling of these clinical trial data, showing an exposure-effect relationship of a monoclonal antibody for the first time in this indication. The specific aims were: (i) to model the pharmacokinetics of inolimomab given as a repeated dose; (ii) to identify inolimomab exposure-effect relationships on different efficacy markers in acute GvHD; and (iii) to propose a model in order to help future dose optimisation of this treatment.
Patients and Treatment
The data were collected from an open-label, dose-escalating, nonrandomised phase I–II study of inolimomab in combination with corticosteroids (methylprednisolone 2 mg/kg) as first-line therapy for grade II–IV acute GvHD following allogeneic haematopoietic stem cell transplantation. The main objective of this trial was to establish the pharmacokinetics of four dosages of inolimomab. Six French institutions participated in the study (Hôpital Edouard Herriot, Lyon; Centre Jean Perrin, Clermont-Ferrand; Institut Paoli Calmettes, Marseille; Hôpital Claude Hurriez, Lille; Hôtel Dieu, Nantes; Hôpital Henri Mondor, Créteil). The study protocol was approved by the Independent Ethics Committee of Lyon — Centre Léon Bérard. The inclusion criteria included: age ≥18 years, grade II–IV acute GvHD following haematopoietic stem cell transplantation using either allogeneic bone marrow or allogeneic peripheral blood progenitor cells, and provision of informed consent to participate in the study. Patients were excluded if they were receiving corticosteroids for prophylaxis against acute GvHD or had acute GvHD after donor lymphocyte infusions. Diagnosis and classification of acute GvHD was done according to the Seattle criteria (the Glucksberg classification)[18,19] and the International Bone Marrow Transplant Registry (IBMTR) classification.
After their eligibility was confirmed, 21 patients were registered and assigned to one of four cohorts to receive a 30-minute intravenous inolimomab infusion (0.1, 0.2, 0.3 or 0.4 mg/kg), with five patients in each dose group except for the 0.3 mg/kg group, which had six patients. The treatment was divided into the induction and maintenance regimen phases. The induction regimen was given from day 1 to day 8 and consisted of a once-daily intravenous infusion of inolimomab at the patient’s assigned dose level. The clinical response assessed at day 9 determined subsequent treatment. Patients with a complete response were assigned to receive the maintenance regimen. Patients with a partial response, mixed response, no response or disease progression were reassigned to the induction regimen for 1 week. The maintenance regimen consisted of administration of intravenous inolimomab three times weekly at the patient’s induction dose level. During both the induction and maintenance regimen phases, all patients received a concomitant intravenous infusion of methylprednisolone. Patients received between 6 and 22 administrations of inolimomab depending on the duration of their induction and maintenance regimen phases. The entire treatment period lasted a maximum of 4 weeks.
The median number of pharmacokinetic samples per patient was 12 (range 7–23) and the total number was 318. Blood samples for pharmacokinetic analysis (including peak and trough concentrations of inolimomab) were collected prior to infusion of the study medication and then 30 minutes, 2 hours, 8 hours and 16 hours after cessation of the infusion on day 1; prior to the infusion and 30 minutes after cessation of the infusion on days 2, 3 and 8; and prior to the infusion and 30 minutes after cessation of the infusion from day 9 to day 28 for the first three infusions. After collection, the blood samples were centrifuged and the serum samples were stored at −20°C until analysis.
Quantification was carried out in the OPi Research Department by a validated inolimomab ELISA according to Good Laboratory Practice. To trap inolimomab, serum samples were put onto a coated plate with goat polyclonal anti-mouse immunoglobulin antibodies. Next, sheep polyclonal anti-mouse IgG1 antibodies used as tracer antibodies were added to the mixture. After incubation with 3,3′,5,5′-tetramethylbenzidine substrate, the reaction was stopped by the addition of sulphuric acid and the absorption was read photometrically to quantify the samples. The range of the immunoassay was 0.15–10 µg/mL, with a sensitivity of >100 ng/mL, a sample intra-assay variation of 8% and a sample inter-assay variation of 11%.
Pharmacokinetic and pharmacodynamic analyses were carried out with nonlinear mixed-effect modelling using NONMEM software Version V. Different pharmacokinetic models were tested, including one-, two- and three-compartment models, coupled with linear or nonlinear processes, such as saturable elimination. Interindividual pharmacokinetic parameter variability was assumed to follow log-normal distribution with non-zero correlations. Residual unexplained variability was modelled as multiplicative. The first-order conditional estimation (FOCE) INTERACTION method was used to fit all pharmacokinetic models. Models were evaluated through goodness-of-fit plots[23–25] and the parameter precision was estimated by an asymptotic covariance matrix. Nested models were compared according to likelihood ratio tests (decrease of the NONMEM objective function between the reduced and full model by 3.84, corresponding to a nominal p-value of 0.05 for one additional parameter).
For each pharmacodynamic timepoint assessment, inolimomab exposures were estimated from individual pharmacokinetic profiles predicted from the previously described model. They were defined as either the maximal serum concentration (Cmax), the area under the serum concentration-time curve (AUC) over the last dosing interval, the cumulated AUC, or the AUC intensity (cumulated AUC/duration) from the first to the last dosing before pharmacodynamic assessment. The cumulated AUC corresponded to the cumulated sum of all AUCs computed for each dosing interval before pharmacodynamic assessment; the duration used in AUC intensity calculation corresponded to the treatment duration before pharmacodynamic assessment. Graphical exploration of the exposure-effect relationships was performed with all pharmacodynamic assessments by plotting the estimated cumulative probabilities of ordered scores (composite and organ scores) versus distribution quantiles (25%, 50%, 75% and 100%) of the above-defined drug exposures. Apparent relationships were then quantified by proportional odds models. The cumulative probabilities of the observed score were linked to pharmacokinetic exposure through logit transformation. The nature of this link was tested with different pharmacodynamic models such as the maximum effect (Emax), log-linear or linear models. Interindividual variability of some key parameters was assumed to follow either a normal or a log-normal distribution. Parameter estimation was performed using the Laplacian estimation method in NONMEM. The adequacy of the different developed models and selection of the basic model were evaluated by comparing predicted and observed probabilities.
The model qualification for the pharmacokinetic and pharmacokinetic-pharmacodynamic models was conducted in two steps. With regard to the pharmacokinetic model, after inspection of the basic graphics (predictions of a typical patient versus observations, individual predictions versus observations, weighted residuals versus observations, individual predictions and observations versus time), a visual predictive check was conducted. It consisted of simulating (with NONMEM) 200 new datasets with identical patients, dosage regimens and sampling times, and then graphically comparing the simulated concentrations with the observed ones. The qualification of the pharmacokinetic-pharmacodynamic model was also based on a visual predictive check. Here, the purpose was to test the model’s ability to predict the probability of observing a grade. Therefore, we compared graphically the model predicted grade-exposure relationship with the observed one. Then, a predictive check was specifically conducted to qualify the pharmacokinetic-pharmacodynamic model for its clinical purpose.[28,29] It consisted of simulating (using NONMEM) 1000 new datasets by sampling patients with their score record time and simulating the grade for each measurement. Then we compared the statistic deduced from these simulations with the observed ones. This statistic, which is a quantity that depends only on data, was chosen in order to highlight the treatment effect.
Following promising results observed in 32 corticosteroid-resistant patients who presented with acute GvHD and, more recently, in a retrospective analysis of 85 corticosteroid-resistant patients with grade II–IV acute GvHD, inolimomab was proposed as an upfront therapy. As the investigators in these clinical trials had already observed heterogeneity in the organ response with, for instance, a better and more prolonged response occurring in cutaneous acute GvHD, it therefore clearly appeared that the pharmacodynamics of inolimomab needed to be investigated. Concerning inolimomab and concomitant treatments, patients have received very different exposures in terms of duration as well as dosage. Some investigators carried out a multivariate analysis, suggesting that a higher total dose of inolimomab might be predictive of a better response. In this context, it also appeared important to identify the pharmacokinetics of this drug in order for analyses to take into account the real inolimomab treatment exposure, and to understand more precisely the pharmacodynamics and their relationship to the pharmacokinetics. This type of approach in acute GvHD is not very widespread and has not previously involved any type of monoclonal antibody. Only a few investigators have previously tried to link the pharmacokinetics and pharmacodynamics for prophylactic treatment. For instance, some investigators noticed a correlation between ciclosporin trough blood concentrations in the early post-transplantation period and the probability of observing an acute GvHD. By splitting the population into four groups (no acute GvHD, mild acute GvHD, moderate acute GvHD and severe acute GvHD) they observed a decrease in mean ciclosporin trough blood concentrations for all time periods. Other investigators defined binary criteria as the probability of observing at least grade II acute GvHD and linked this criteria to the busulfan AUC at steady state by a logistic function. Finally, other investigators used a threshold value of the AUC of unbound mycophenolate mofetil in week 1 after transplant to define two groups of patients and observed different cumulative proportions of observing a grade II–IV acute GvHD as a function of time.
Our study modelled the pharmacokinetics of inolimomab and succeeded in modelling its exposure-effect relationship. For pharmacokinetic modelling, the population approach, taking into account design heterogeneity and the individual treatment history, allowed identification of a two-compartment model. Despite some under-predictions at the higher concentrations, the observations were, on the whole, well predicted and the model was qualified for calculating individual treatment exposure, which could not be directly computed from the observed data.
To highlight pharmacokinetic-pharmacodynamic relationships, we initially considered acute GvHD according to the Glucksberg and IBMTR reference scores and the Karnofsky classification. Since those combined scores are not arranged in order (i.e. grade 0 < grade I < grade II…), the pharmacokinetic-pharmacodynamic relationship is not easy to reveal. For instance, grade B in the IBMTR classification can correspond to a grade 2 of skin involvement and two grades 0 of liver and intestinal involvement or a grade 0 of skin involvement, a grade 1 of liver involvement and a grade 2 of intestinal involvement. We found out that the calculation of the IBMTR and Glucksberg grades, as well as of the global performance provided by the Karnofsky score, are not adapted to highlighting an exposure-effect relationship of inolimomab. In fact, some investigators have already identified better efficacy of inolimomab in a cutaneous form of acute GvHD. In the context of targeted efficacy in one organ, one can easily understand that a composite measure of the effect is not relevant to the pharmacokinetic-pharmacodynamic analysis.
Our pharmacokinetic-pharmacodynamic analysis logically focused on each of the three organs and on treatment exposure. It clearly appeared that the relationship was significant regardless of which treatment exposure measurement was chosen. The treatment effect reached a maximum for the skin and was modelled with an Emax model. A mixture model revealed two populations of patients: sensitive and non-sensitive.[36–38] For the liver as well as for the intestinal tract, the treatment effect appeared only above a threshold of cumulated AUC. It was illustrated by a large decrease in patients with severe symptoms (grade 4) and a significant increase in patients without symptoms (grade 0). This means that a larger exposure than that needed for the skin is required to reach the same efficacy in those organs. It also explains why clinically, the skin is the first organ to be cured whereas it seems to be more difficult to treat the liver and the intestinal tract. This is illustrated by the pharmacokinetic-pharmacodynamic graphs at day 8: from 15% to 20% of patients still present with the highest grade for these two organs. Some investigators have attributed this phenomenon to the difference in the bioavailability of inolimomab or the pathophysiology of acute GvHD depending on organ involvement.
With this analysis, we highlighted and modelled a pharmacokinetic-pharmacodynamic relationship between the cumulated AUC of inolimomab and the skin, liver and intestinal tract scores. The modelling of the data allowed us to describe observations as well as to predict an overall response at the end of treatment for this population using IBMTR scores. This approach, which was validated for its objective, allowed us to better understand the treatment effect over time and represents the first step towards optimising the dosage for future patients. However, it does still present some limitations due, in particular, to the limited number of patients. Further trials are needed to improve clinical use of these models.
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The authors wish to thank OPi SA, Limonest, France, for providing the pharmacokinetic and pharmacodynamic samples, and for reviewing and approving the manuscript. The funding of this study was provided by OPi SA and the Faculté de Médecine Lyon Sud at the Université de Lyon, Lyon, France. I. Darlavoix and C. Vermot-Desroches are employees of OPi SA. C. Dartois is supported by the Institut de Recherches Internationales Servier. P. Girard is supported by INSERM, France. The other authors have no conflicts of interest that are directly relevant to the content of this study.