Heinz Schmidli

Safety, tolerability, and efficacy of everolimus in de novo liver transplant recipients: 12‐ and 36‐month results

Everolimus is a macrolide immunosuppressive agent with known consistent absorption. In this double‐blind study, we examined the safety and tolerability of everolimus vs. placebo in de novo liver transplant recipients. One hundred and nineteen liver allograft recipients were randomized to 1 of 4 groups: everolimus 0.5 mg bid, everolimus 1.0 mg bid, everolimus 2 mg bid, or placebo. Patients received oral cyclosporine to achieve a target trough level of 150‐400 ng/mL in combination with prednisone. Primary and secondary endpoints of safety, tolerability, and efficacy were determined at 12 months, and patients were followed through 36 months. There was a trend toward fewer treated acute rejections in the everolimus group than in the placebo group: everolimus 0.5 mg: 39.3%; everolimus 1.0 mg: 30.0%; everolimus 2 mg: 29.0%; placebo: 40.0% (P = not significant). Adverse events were higher in everolimus‐treated patients especially at the 4‐mg/day dose, but there was no difference in the incidence of thrombocytopenia or leukopenia between all groups and renal function as determined by serum creatinine, and creatinine clearance remained stable to 36 months in everolimus‐treated patients. Mean cholesterol and triglycerides increased from baseline in all treatment groups, and maximum levels were seen at 6 months. In conclusion, this study demonstrates that everolimus in combination with oral cyclosporine had an acceptable safety and tolerability profile, paving the way for additional studies in this transplant indication. Liver Transpl, 2006.

Advantages of Artificial Neural Networks (ANNs) as alternative modelling technique for data sets showing non-linear relationships using data from a galenical study on a solid dosage form

Artificial Neural Networks (ANN) methodology was used to assess experimental data from a tablet compression study showing highly non-linear relationships (i.e. measurements of ejection forces) and compared to classical modelling technique (i.e. Response Surface Methodology, RSM). These kinds of relationships are known to be difficult to model using classical methods. The aim of this investigation was to quantitatively describe the achieved degree of data fitting and predicting abilities of the developed models. The comparison between the ANN and RSM was carried out both graphically and numerically. For comparing the goodness of fit, all data were used, whereas for the goodness of prediction the data were split into a learning and a validation data set. Better results were achieved for the model using ANN methodology with regard to data fitting and predicting ability. All determined ejection properties were mainly influenced by the concentration of magnesium stearate and silica aerogel, whereas the other factors showed very much lower effects. Important relationships could be recognised from the ANN model only, whereas the RSM model ignored them. The ANN methodology represents a useful alternative to classical modelling techniques when applied to variable data sets presenting non-linear relationships.

Everolimus therapeutic concentration range defined from a prospective trial with reduced-exposure cyclosporine in de novo kidney transplantation.

Prospective therapeutic drug monitoring of everolimus was performed in a 1-year multicenter trial in 237 de novo kidney transplant patients. Trough blood levels, rejection episodes, and safety parameters were evaluated to define an appropriate therapeutic concentration range for everolimus in this setting. Patients were randomized to everolimus starting doses of 0.75 mg bid (n = 112) or 1.5 mg bid (n = 125). Doses were then individualized based on everolimus trough blood levels (C0) in an attempt to maintain troughs ≥3 ng/mL; no upper limit was specified. The regimen also contained corticosteroids and cyclosporine with an early dose reduction in months 2–3 posttransplant based on concentrations 2 hours postdose (C2). Cyclosporine C0 levels were also collected. Prospective therapeutic drug monitoring of everolimus C0 in patients starting at 0.75 mg bid led to dose adjustments in 52% of patients to an average long-term dose of 0.93 ± 0.36 mg bid. This gave median (10th to 90th percentile) C0 levels of 5.3 (3.4–7.9) ng/mL. In patients starting at 1.5 mg bid, 55% had dose adjustments leading to an average long-term dose of 1.24 ± 0.35 mg bid. This yielded C0 levels of 7.2 (4.4–11.6) ng/mL. Cyclosporine dosing began on average at 274 ± 78 mg bid, was down-titrated in months 2–3 from 181 ± 80 mg to 81 ± 33 mg bid, and stabilized at 70 ± 26 mg bid thereafter. This yielded median C2 levels of 1165 ng/mL in month 1, a down-titration with levels of 853 and 630 ng/mL in months 2 and 3, and a posttitration level of 472 ng/mL. The corresponding median cyclosporine C0 was 242 ng/mL initially and 70 ng/mL in the posttitration phase. In patients starting at 0.75 mg bid everolimus and an early down-titration of cyclosporine, everolimus C0 between 3 and 8 ng/mL was an effective and safe concentration range. Concentrations up to 12 ng/mL were tolerated over the first year posttransplant. This trial demonstrated that therapeutic monitoring of everolimus can be prospectively performed for dose individualization. Maintaining everolimus troughs in the range 3 to 8 ng/mL in the first posttransplant year with reduced-exposure cyclosporine is associated with good efficacy and safety profiles.

Therapeutic drug monitoring for everolimus in heart transplant recipients based on exposure-effect modeling.

Everolimus, a proliferation signal inhibitor, is an immunosuppressant that targets the primary causes of progressive allograft dysfunction, thus improving the long‐term outcome after heart transplantation. The present study investigated whether therapeutic drug monitoring (TDM) of everolimus would benefit heart transplant patients. Data from a twelve‐month phase III trial comparing everolimus (1.5 or 3 mg daily) with azathioprine were used to evaluate everolimus pharmacokinetics, exposure‐efficacy/safety and TDM prognostic simulations. Everolimus trough levels were stable in the first year post‐transplant and averaged 5.2 ± 3.8 and 9.4 ± 6.3 ng/mL in patients treated with 1.5 and 3 mg/day, respectively. Cyclosporine trough levels were similar in all treatment groups. Biopsy‐proven acute rejection (BPAR) was reduced with everolimus trough levels ≥3 ng/mL. Intravascular ultrasound (IVUS) analysis showed evidence of reduced vasculopathy at 12 months with increasing everolimus exposure. Unlike cyclosporine, increasing everolimus exposure was not related to a higher rate of renal dysfunction. The TDM simulation, which was based on two everolimus dose adjustments and an initial starting dose of 1.5 mg/day, showed that the simulated BPAR rate (with TDM) was 21% versus 26% in the group with fixed dosing. Therefore, TDM in heart transplantation could optimize immunosuppressive efficacy and reduce treatment‐related toxicity.

Therapeutic drug monitoring for everolimus in kidney transplantation using 12-month exposure, efficacy, and safety data.

Abstract:  The aims of the current study were to determine whether therapeutic drug monitoring (TDM) might benefit kidney transplant recipients receiving everolimus, and to establish dosage recommendations when everolimus is used in combination with cyclosporine and corticosteroids. The analysis was based on data from 779 patients enrolled in two 12‐month trials. Everolimus trough concentrations ≥3 ng/mL were associated with a reduced incidence in biopsy‐proven acute rejection (BPAR) in the first month (p = 0.0001) and the first 6 months (p = 0.0001), and reduced graft loss compared with lower concentrations (4% vs. 20%, respectively). By contrast, cyclosporine in the standard concentration range had no impact on BPAR within the same timeframes. Most patients receiving everolimus 1.5 or 3 mg/d achieved trough concentrations above the therapeutic threshold of 3 ng/mL, regardless of reductions in cyclosporine dose. TDM simulation showed that just two dose adjustments would achieve median everolimus trough values ≥3 ng/mL in 95% of patients during the first 6 months.

Rivastigmine exposure provided by a transdermal patch versus capsules.

ABSTRACT Objectives: The rivastigmine transdermal patch is the first transdermal treatment for Alzheimers disease (AD) and dementia associated with Parkinsons disease. The objective of this study was to evaluate the pharmacokinetics of rivastigmine following transdermal delivery by a patch versus oral delivery with conventional capsules in a population of AD patients. Methods: Both non-compartmental and compartmental analyses were performed on the same database showing relatively large inter-patient variations in pharmacokinetic parameters (up to 73% for the capsule group). The compartmental analysis provided model-based predictions of pharmacokinetic parameters, with the aim of comparing the two modes of administration when adjusting for confounding factors such as patient body weight and gender. Results: According to both non-compartmental and compartmental analyses, the patch provided significantly lower peak rivastigmine plasma concentrations (Cmax) and slower times to Cmax (tmax), compared with capsules. However, drug exposure (area under the curve; AUC) was not significantly different between the 4.6 mg/24 hour (5 cm2) patch and 3 mg BID (6 mg/day) capsule doses, or between the 9.5 mg/24 hour (10 cm2) patch and 6 mg BID (12 mg/day) capsule doses, according to both analyses. This suggests comparable exposure from these two rivastigmine delivery systems. Conclusion: The analyses were consistent with previous reports of a markedly less fluctuating, more continuous drug delivery with the rivastigmine patch. This characteristic delivery profile is associated with similar efficacy yet improved tolerability, compared with capsules.

The effects of a flexible visual acuity-driven ranibizumab treatment regimen in age-related macular degeneration: outcomes of a drug and disease model.

PURPOSE Differences in treatment responses to ranibizumab injections observed within trials involving monthly (MARINA and ANCHOR studies) and quarterly (PIER study) treatment suggest that an individualized treatment regimen may be effective in neovascular age-related macular degeneration. In the present study, a drug and disease model was used to evaluate the impact of an individualized, flexible treatment regimen on disease progression. METHODS For visual acuity (VA), a model was developed on the 12-month data from ANCHOR, MARINA, and PIER. Data from untreated patients were used to model patient-specific disease progression in terms of VA loss. Data from treated patients from the period after the three initial injections were used to model the effect of predicted ranibizumab vitreous concentration on VA loss. The model was checked by comparing simulations of VA outcomes after monthly and quarterly injections during this period with trial data. A flexible VA-guided regimen (after the three initial injections) in which treatment is initiated by loss of >5 letters from best previously observed VA scores was simulated. RESULTS Simulated monthly and quarterly VA-guided regimens showed good agreement with trial data. Simulation of VA-driven individualized treatment suggests that this regimen, on average, sustains the initial gains in VA seen in clinical trials at month 3. The model predicted that, on average, to maintain initial VA gains, an estimated 5.1 ranibizumab injections are needed during the 9 months after the three initial monthly injections, which amounts to a total of 8.1 injections during the first year. CONCLUSIONS A flexible, individualized VA-guided regimen after the three initial injections may sustain vision improvement with ranibizumab and could improve cost-effectiveness and convenience and reduce drug administration-associated risks.

Comparison of artificial neural networks (ANN) with classical modelling techniques using different experimental designs and data from a galenical study on a solid dosage form

Artificial Neural Networks (ANN) methodology was used to analyse experimental data from a tabletting study and compared both graphically and numerically to classical modelling techniques (i.e. Response surface methodology, RSM). The aim of this investigation was to describe quantitatively the degree of data fitting achieved and the robustness of the developed models using two types of experimental design (i.e. a statistical, highly organised design and a randomised design). To compare goodness of fit, the R(2) coefficient was used, whereas for the robustness of the models the R(2) coefficient of an independent validation data set was computed. Comparable results were achieved for both ANN and RSM methodology when using the statistical plan. However, the robustness of the models when developed based on a randomised plan was clearly better for the ANN methodology. Based on the results of this study, it appears that the ANN methodology is much less sensitive to the organisational level of a trial design and is therefore better adapted to the data analysis of the results of historical or poorly organised trials. All tablet properties determined were largely influenced by the dwell time during compression as well as by concentration of silica aerogel and magnesium stearate, whereas the other factors showed very much weaker effects.

Application of Artificial Neural Networks (ANN) in the Development of Solid Dosage Forms

The application of ANN in pharmaceutical development has been assessed using theoretical as well as typical pharmaceutical technology examples. The aim was to quantitatively describe the achieved data fitting and predicting abilities of the models developed with a view to using ANN in the development of solid dosage forms. The comparison between the ANN and a traditional statistical (i.e., response surface methodology, RSM) modeling technique was carried out using the squared correlation coefficient R2. Using a highly nonlinear arbitrary function the ANN models showed better fitting (R2 = 0.931 vs. R2 = 0.424) as well as predicting (R2 = 0.810 vs. R2 = 0.547) abilities. Experimental data from a tablet compression study were fitted using two types of ANN models (i.e., multilayer perceptrons and a hybrid network composed of a self-organising feature map joined to a multilayer perception). The achieved data fitting was comparable for the three methods (MLP R2 = 0.911, SOFM-MLP R2 = 0.850, and RSM R2 = 0.897). ANN methodology represents a promising modeling technique when applied to pharmaceutical technology data sets.

Basic concepts of artificial neural networks (ANN) modeling in the application to pharmaceutical development.

Artificial neural networks (ANN) methodology is a new modeling method that has not been broadly applied to pharmaceutical sciences up to now. The aim of this paper is to give a detailed description of the associating networks as well as a description of less well-known networks (i.e., feature-extracting and nonadaptive networks) and their scope of application in pharmaceutical sciences. The descriptions include the historical origin and the basic concepts behind the computing. ANN are based on the attempt to model the neural networks of the brain. Learning algorithms for associating ANN use mathematical procedures usually derived from the gradient descent method whereas feature-extracting ANN map multidimensional input data sets onto two-dimensional spaces. Nonadaptive ANN map data sets and are able to reconstruct their patterns when presented with corrupted or noisy samples. Associating networks can typically be applied in the pharmaceutical field as an alternative to traditional response surface methodology, feature-extracting networks as alternative to principal component analysis, and nonadaptive networks for image recognition. Based on these abilities, the potential application fields of the ANN methodology in the pharmaceutical sciences is broad, ranging from clinical pharmacy through biopharmacy, drug and dosage form design, to interpretation of analytical data. The few applications presented in the pharmaceutical technology area seem promising and should be investigated in more detail.