BackgroundHydroxyurea (HU) is the first approved pharmacological treatment of sickle cell anemia (SCA). The objectives of this study were to develop population pharmacokinetic(PK)-pharmacodynamic(PD) models for HU in order to characterize the exposure-efficacy relationships and their variability, compare two dosing regimens by simulations and develop some recommendations for monitoring the treatment.MethodsThe models were built using population modelling software NONMEM VII based on data from two clinical studies of SCA adult patients receiving 500-2000 mg of HU once daily. Fetal hemoglobin percentage (HbF%) and mean corpuscular volume (MCV) were used as biomarkers for response. A sequential modelling approach was applied. Models were evaluated using simulation-based techniques. Comparisons of two dosing regimens were performed by simulating 10000 patients in each arm during 12 months.ResultsThe PK profiles were described by a bicompartmental model. The median (and interindividual coefficient of variation (CV)) of clearance was 11.6 L/h (30%), the central volume was 45.3 L (35%). PK steady-state was reached in about 35 days. For a given dosing regimen, HU exposure varied approximately fivefold among patients. The dynamics of HbF% and MCV were described by turnover models with inhibition of elimination of response. In the studied range of drug exposures, the effect of HU on HbF% was at its maximum (median Imax was 0.57, CV was 27%); the effect on MCV was close to its maximum, with median value of 0.14 and CV of 49%. Simulations showed that 95% of the steady-state levels of HbF% and MCV need 26 months and 3 months to be reached, respectively. The CV of the steady-state value of HbF% was about 7 times larger than that of MCV. Simulations with two different dosing regimens showed that continuous dosing led to a stronger HbF% increase in some patients.ConclusionsThe high variability of response to HU was related in part to pharmacokinetics and to pharmacodynamics. The steady-state value of MCV at month 3 is not predictive of the HbF% value at month 26. Hence, HbF% level may be a better biomarker for monitoring HU treatment. Continuous dosing might be more advantageous in terms of HbF% for patients who have a strong response to HU.Trial RegistrationThe clinical studies whose data are analysed and reported in this work were not required to be registered in France at their time. Both studies were approved by local ethics committees (of Mondor Hospital and of Kremlin-Bicetre Hospital) and written informed consent was obtained from each patient.

Objective:To evaluate effects of siponimod on response to T-cell–dependent (influenza) and T-cell–independent (pneumococcal polysaccharide vaccine [PPV-23]) vaccinations in healthy participants.Methods:In this double-blind, placebo-controlled, parallel-group study, each participant underwent a 7-week treatment period and received intramuscular injections of influenza and PPV-23 vaccines (day 21). Participants were randomized to 4 treatment groups (N = 30 each) and received placebo or siponimod 2 mg once daily in concomitant, interrupted, or preceding fashion. Individual response to vaccination was defined by a ≥4-fold (influenza) antibody titer increase and by a ≥2-fold increase in serotype-specific immunoglobulin (Ig) G concentrations (PPV-23) on day 28 vs baseline. Responder rates were compared using noninferiority analysis.Results:Mean influenza titers were similar to placebo in the preceding and interrupted groups but lower in the concomitant group. The proportion of participants with influenza titers ≥40 four weeks after vaccination (seroprotection) was similar to placebo across all groups and antigens. In each treatment group, response criteria were met for 3 of 4 antigens including H1N1 and H3N2. A noninferior response was determined in the context of preceding treatment but not interrupted or concomitant treatment. Regarding PPV-23, approximately 90%–100% of participants exhibited a ≥2-fold increase in IgG concentrations vs baseline. Noninferior responder rates were determined for each siponimod treatment group.Conclusions:Siponimod treatment had no relevant effect on antibody response to PPV-23. European Medicines Agency response criteria were essentially met for influenza, but titers were lower on concomitant treatment. Overall, these data suggest that siponimod has limited effect on the efficacy of vaccinations with neoantigens.Classification of evidence:This study provides Class II evidence that in healthy persons, siponimod had limited effect on the immune response following influenza or pneumococcal vaccinations.

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Clinical outcomes are often described as events: death, stroke, epileptic seizure, multiple sclerosis lesions, recurrence of cancer, disease progression, pain, infection and bacterial/viral eradication, severe toxic adverse effect, resistance to treatment, etc. They may be quantified as time-to-event, counts of events per time interval (rates), their severity grade, or a combination of these. Such data are discrete and require specific modelling structures and methods. This article references the most common modelling approaches for categorical, count and time-to-event data, and reviews examples of such models applied in the analysis of pharmacodynamic data. Modelling is useful for identification of influential factors related to the clinical outcome, characterization and quantification of their impact, for making better informed predictions and clinical decisions, assessments of efficacy of therapeutic interventions, optimizing the individual treatments and drug development studies.