Translational approach from preclinical to clinical: comparison of dose finding methods of a new Bcl2 inhibitor using PK-PD modeling and interspecies extrapolation.

The attrition rate of anticancer drugs during the clinical development remains very high. Interspecies extrapolation of anticancer drug pharmacodynamics (PD) could help to bridge the gap between preclinical and clinical settings and to improve drug development. Indeed, when combined with a physiologically-based-pharmacokinetics (PBPK) approach, PD interspecies extrapolation could be a powerful tool for predicting drug behavior in clinical trials. The present study aimed to explore this field for anticipating the clinical efficacy of a new Bcl-2 inhibitor, S 55746, for which dose ranging studies in xenografted mice and clinical data from a phase 1 trial involving cancer patients were available. Different strategies based on empirical or more mechanistic assumptions (based on PBPK-PD modelling) were developped and compared: the Rocchetti approach (ROC); the Orthogonal Rocchetti approach (oROC), a variant of ROC based on an orthogonal regression; the Consistent across species approach, bringing out an efficacy parameter assumed to be consistent across species; and the Scaling species-specific parameters approach, assuming the concentration-efficacy link is the same in mice as in humans, after allometric scaling. Empirical approaches (ROC and oROC) gave similar predictive performances and seemed to overestimate the active S 55746 dose compared to mechanistic approaches, while strategies elaborated from semi-mechanistic concepts and PBPK-PD modelling did not seem to be invalidated by clinical efficacy data. Also, empirical methods only predict a single dose level for the subsequent clinical studies, whereas mechanism-based strategies are more informative about the dose response relationship, highlighting the potential interest of such approaches in drug development.

Prediction of Human Nonlinear Pharmacokinetics of a New Bcl-2 Inhibitor Using PBPK Modeling and Interspecies Extrapolation Strategy.

S 55746 ((S)-N-(4-hydroxyphenyl)-3-(6-(3-(morpholinomethyl)-1,2,3,4-tetrahydroisoquinoline-2-carbonyl)benzo[d][1,3]dioxol-5-yl)-N-phenyl-5,6,7,8-tetrahydroindolizine-1-carboxamide) is a new selective Bcl-2 (B-cell lymphoma 2) inhibitor developed by Servier Laboratories and used to restore apoptosis functions in cancer patients. The aim of this work was to develop a translational approach using physiologically based (PB) pharmacokinetic (PK) modeling for interspecies extrapolation to anticipate the nonlinear PK behavior of this new compound in patients. A PBPK mouse model was first built using a hybrid approach, defining scaling factors (determined from in vitro data) to correct in vitro clearance parameters and predicted Kp (partition coefficient) values. The qualification of the hybrid model using these empirically determined scaling factors was satisfactorily completed with rat and dog data, allowing extrapolation of the PBPK model to humans. Human PBPK simulations were then compared with clinical trial data from a phase 1 trial in which the drug was given orally and daily to cancer patients. Human PBPK predictions were within the 95% prediction interval for the eight dose levels, taking into account both the nonlinear dose and time dependencies occurring in S 55746 kinetics. Thus, the proposed PK interspecies extrapolation strategy, based on preclinical and in vitro information and physiologic assumptions, could be a useful tool for predicting human plasma concentrations at the early stage of drug development.

Efficacy of two vitamin E formulations in patients with abetalipoproteinemia and chylomicron retention disease.

Abetalipoproteinemia (ABL) and chylomicron retention disease (CMRD) are extremely rare recessive forms of hypobetalipoproteinemia characterized by intestinal lipid malabsorption and severe vitamin E deficiency. Vitamin E is often supplemented in the form of fat-soluble vitamin E acetate, but fat malabsorption considerably limits correction of the deficiency. In this crossover study, we administered two different forms of vitamin E, tocofersolan (a water-soluble derivative of RRR-α-tocopherol) and α-tocopherol acetate, to three patients with ABL and four patients with CMRD. The aims of this study were to evaluate the intestinal absorption characteristics of tocofersolan versus α-tocopherol acetate by measuring the plasma concentrations of α-tocopherol over time after a single oral load and to compare efficacy by evaluating the ability of each formulation to restore vitamin E storage after 4 months of treatment. In patients with ABL, tocofersolan and α-tocopherol acetate bioavailabilities were extremely low (2.8% and 3.1%, respectively). In contrast, bioavailabilities were higher in patients with CMRD (tocofersolan, 24.7%; α-tocopherol acetate, 11.4%). Plasma concentrations of α-tocopherol at 4 months were not significantly different by formulation type in ABL or CMRD. This study provides new insights about vitamin E status in ABL and CMRD and suggests the potential of different formulations as treatment options.

Tumor Growth Inhibition Modelling Based on Receptor Occupancy and Biomarker Activity of a New Bcl-2 Inhibitor in Mice.

The Bcl-2 inhibitor S 55746 ((S)-N-(4-hydroxyphenyl)-3-(6-(3-(morpholinomethyl)-1,2,3,4-tetrahydroisoquinoline-2-carbonyl)benzo[d][1,3]dioxol-5-yl)-N-phenyl-5,6,7,8-tetrahydroindolizine-1-carboxamide) is able to restore apoptosis functions impaired by tumorigenesis in mice. Data from pharmacokinetic (PK), biomarker, and tumor growth studies in a xenograft mouse model were considered for population modeling. The aim of the modeling exercise was to link the kinetics of the drug to the biomarker and tumor-size time profiles to better understand its dose-effect relationship. The PK, caspase kinetics, and tumor dynamics were successfully characterized by the proposed pharmacokinetic-pharmacodynamic model. The nonlinear plasma PK was best described by a two-compartment disposition model with both saturable absorption and elimination. Caspase was activated above the effective drug-concentration threshold (CTHRE ), at which near-maximal activity was reached. Increasing the dose did not increase the activation but better sustained it. Tumor growth followed a biphasic pattern, with caspase having an all-or-none inhibiting effect, consistent with the bistability property of the caspase pathway. For tumor eradication, the CTHRE in plasma was 2876 ng ml-1, and the relative caspase activity threshold (CaspTHRE) was 46.5. There was a strong relationship between the time spent above these thresholds and tumor growth inhibition. Tumor growth was inhibited by 50% when CaspTHRE was exceeded 13.8% of the time and when CTHRE was exceeded 8.1% of the time per dosing. This semimechanistic approach, based on experimental mice data and in vitro parameters, provides an interesting tool to quantify or simulate antitumor effects and, eventually, to plan phase 1 studies.

Delayed methotrexate elimination: Incidence, interaction with antacid drugs, and clinical consequences?

The aim of this retrospective cohort study was to investigate the incidence of delayed methotrexate elimination in patients treated with high-dose methotrexate (≥1 g/m2 ) for haematological malignancy and to identify the impact of interacting drugs, especially proton-pump inhibitors (PPIs) and ranitidine. All patients treated with high-dose methotrexate over a 6 year period in the haematology department of the Lyon Sud University Hospital (Hospices Civils de Lyon, France) were included. Potential risk factors for delayed methotrexate elimination were tested in a generalized linear model by univariate analysis: patient age, gender, methotrexate dose, administration of PPI or ranitidine, and concomitant nephrotoxic drugs. A total of 412 cycles of methotrexate were administered to 179 patients. Proton-pump inhibitors were co-administered with methotrexate in 127 cycles and ranitidine in 192 cycles. Ninety-three cycles included no antacid drugs. A total of 918 plasma methotrexate assays were performed. Methotrexate concentrations were checked at 24 hours in 92% of cycles. Delayed methotrexate elimination was observed in 20.9% of cycles. A total of 63 cycles with delayed methotrexate elimination were only identified on plasma methotrexate measures at 72 hours: ie, plasma methotrexate was in the normal range at 24 and 48 hour post injection. Use of PPI/ranitidine or no antacid drugs did not increase risk of delayed elimination, with respectively delayed methotrexate elimination in 20.5%, 21.9%, and 19.4% of cycles (P = .89). Impaired baseline creatinine clearance showed significant association in univariate analysis. Fifteen patients showed grade 1 acute kidney injury, 1 grade 2, 2 grade 3, and none grade 4. For half of these cases, delayed methotrexate elimination was observed and the 2 grade 3 events appeared in patients treated with PPIs. This retrospective study suggests that there is no association between concomitant use of proton-pump inhibitors (pantoprazole and esomeprazole) or ranitidine and delayed methotrexate elimination.

Pharmacokinetic interactions in mice between irinotecan and MBL-II-141, an ABCG2 inhibitor.

PURPOSE: The chromone derivative MBL-II-141, specifically designed to inhibit ABCG2, was previously demonstrated to combine strong inhibition potency, low toxicity and good efficiency in reversing resistance to irinotecan in a xenografted mouse model. Here, the pharmacokinetic interactions in mice between irinotecan, its active metabolite SN-38 and MBL-II-141 were characterized quantitatively in the blood and in the brain. METHODS: Compartmental models were used to fit the data. Goodness-of-fit was assessed by simulation-based diagnostic tools. RESULTS: Irinotecan increased the MBL-II-141 apparent clearance and Vss 1.5-fold, probably by increasing the MBL-II-141 unbound fraction. MBL-II-141 decreased the total apparent clearance of irinotecan by 23%, by decreasing its biliary clearance. MBL-II-141 increased 3-fold the brain accumulation of irinotecan, as a result of the rise of systemic exposure combined with the inhibition of ABCG2-mediated efflux at the blood-brain barrier. Finally, SN-38 exposure was increased by 1.16-fold under treatment with MBL-II-141, owing to the higher irinotecan exposure with increased metabolism towards the formation of SN-38. CONCLUSIONS: These results may help to anticipate the pharmacokinetic interactions between MBL-II-141 and other ABCG2 substrates. The irinotecan-MBL-II-141 interaction is also expected to occur in humans. Copyright © 2017 John Wiley & Sons, Ltd.

Revisiting dosing regimen using PK/PD modeling: the MODEL1 phase I/II trial of docetaxel plus epirubicin in metastatic breast cancer patients.

The MODEL1 trial is the first model-driven phase I/II dose-escalation study of densified docetaxel plus epirubicin administration in metastatic breast cancer patients, a regimen previously known to induce unacceptable life-threatening toxicities. The primary objective was to determine the maximum tolerated dose of this densified regimen. Study of the efficacy was a secondary objective. Her2-negative, hormone-resistant metastatic breast cancer patients were treated with escalating doses of docetaxel plus epirubicin every 2 weeks for six cycles with granulocyte colony stimulating factor support. A total of 16 patients were treated with total doses ranging from 85 to 110 mg of docetaxel plus epirubicin per cycle. Dose escalation was controlled by a non-hematological toxicity model. Dose densification was guided by a model of neutrophil kinetics, able to optimize docetaxel plus epirubicin dosing with respect to pre-defined acceptable levels of hematological toxicity while ensuring maximal efficacy. The densified treatment was safe since hematological toxicity was much lower compared to previous findings, and other adverse events were consistent with those observed with this regimen. The maximal tolerated dose was 100 mg given every 2 weeks. The response rate was 45 %; median progression-free survival was 10.4 months, whereas 54.6 months of median overall survival was achieved. The optimized docetaxel plus epirubicin dosing regimen led to fewer toxicities associated with higher efficacy as compared with standard or empirical densified dosing. This study suggests that model-driven dosage adjustment can lead to improved efficacy-toxicity balance in patients with cancer when several anticancer drugs are combined.

Meta-analysis of Magnetic Marker Monitoring Data to Characterize the Movement of Single Unit Dosage Forms Though the Gastrointestinal Tract Under Fed and Fasting Conditions.

PURPOSE: To develop a model predicting movement of non-disintegrating single unit dosage forms (or "tablet") through the gastrointestinal tract and characterizing the effect of food intake, based on Magnetic Marker Monitoring data, allowing real-time location of a magnetically labeled formulation. METHODS: Five studies including 30 individuals in 94 occasions under 3 food status were considered. The mean residence time (MRT) of the tablet and the effect of food intake in proximal (PS) and distal stomach (DS), small intestine (SI), ascending (AC), transverse (TC) and descending colon (DC) were estimated using a Markov model for probabilities of movement. RESULTS: Under fasting conditions, tablet MRTs were 9.4 min in PS, 10.4 in DS, 246 in SI, 545 in AC, 135 in TC, and 286 in DC. A meal taken simultaneous to tablet intake prolonged tablet MRT to 99 min in PS and to 232 in DS; probability of gastric emptying increased of 89% each hour from 2.25 h after meal. The effect of a gastroileac reflex, caused by a secondary meal, accelerated the transit from terminal SI to AC. CONCLUSION: This model-based knowledge can be used as a part of mechanism-based models for drug absorption, applied for bottom-up predictions and/or top-down estimation.

Validation of the Predictive Value of Modeled Human Chorionic Gonadotrophin Residual Production in Low-Risk Gestational Trophoblastic Neoplasia Patients Treated in NRG Oncology/Gynecologic Oncology Group-174 Phase III Trial.

OBJECTIVES: In low-risk gestational trophoblastic neoplasia, chemotherapy effect is monitored and adjusted with serum human chorionic gonadotrophin (hCG) levels. Mathematical modeling of hCG kinetics may allow prediction of methotrexate (MTX) resistance, with production parameter "hCGres." This approach was evaluated using the GOG-174 (NRG Oncology/Gynecologic Oncology Group-174) trial database, in which weekly MTX (arm 1) was compared with dactinomycin (arm 2). METHODS: Database (210 patients, including 78 with resistance) was split into 2 sets. A 126-patient training set was initially used to estimate model parameters. Patient hCG kinetics from days 7 to 45 were fit to: [hCG(time)] = hCG7 * exp(-k * time) + hCGres, where hCGres is residual hCG tumor production, hCG7 is the initial hCG level, and k is the elimination rate constant. Receiver operating characteristic (ROC) analyses defined putative hCGRes predictor of resistance. An 84-patient test set was used to assess prediction validity. RESULTS: The hCGres was predictive of outcome in both arms, with no impact of treatment arm on unexplained variability of kinetic parameter estimates. The best hCGres cutoffs to discriminate resistant versus sensitive patients were 7.7 and 74.0 IU/L in arms 1 and 2, respectively. By combining them, 2 predictive groups were defined (ROC area under the curve, 0.82; sensitivity, 93.8%; specificity, 70.5%). The predictive value of hCGres-based groups regarding resistance was reproducible in test set (ROC area under the curve, 0.81; sensitivity, 88.9%; specificity, 73.1%). Both hCGres and treatment arm were associated with resistance by logistic regression analysis. CONCLUSIONS: The early predictive value of the modeled kinetic parameter hCGres regarding resistance seems promising in the GOG-174 study. This is the second positive evaluation of this approach. Prospective validation is warranted.

Comparing probabilistic and descriptive analyses of time-dose-toxicity relationship for determining no-observed-adverse-effect level in drug development.

The no-observed-adverse-effect level (NOAEL) of a drug defined from animal studies is important for inferring a maximal safe dose in human. However, several issues are associated with its concept, determination and application. It is confined to the actual doses used in the study; becomes lower with increasing sample size or dose levels; and reflects the risk level seen in the experiment rather than what may be relevant for human. We explored a pharmacometric approach in an attempt to address these issues. We first used simulation to examine the behaviour of the NOAEL values as determined by current common practice; and then fitted the probability of toxicity as a function of treatment duration and dose to data collected from all applicable toxicology studies of a test compound. Our investigation was in the context of an irreversible toxicity that is detected at the end of the study. Simulations illustrated NOAEL's dependency on experimental factors such as dose and sample size, as well as the underlying uncertainty. Modelling the probability as a continuous function of treatment duration and dose simultaneously to data from multiple studies allowed the estimation of the dose, along with its confidence interval, for a maximal risk level that might be deemed as acceptable for human. The model-based data integration also reconciled between-study inconsistency and explicitly provided maximised estimation confidence. Such alternative NOAEL determination method should be explored for its more efficient data use, more quantifiable insight to toxic doses, and the potential for more relevant animal-to-human translation.

Multiparameter Phase I trials: a tool for model-based development of targeted agent combinations--example of EVESOR trial.

Optimal development of targeted drug combinations is one of the future challenges to be addressed. Computerization and mathematical models able to describe biological phenomena and to simulate the effects of changes in experimental conditions may help find solutions to this issue. We propose the concept of 'multiparameter trials', where biological, radiological and clinical data required for modeling purpose are collected and illustrated by the ongoing academic EVESOR trial. The objective of the model-based work would be the determination of the optimized doses and dosing schedules of everolimus and sorafenib, offering the maximization of the predicted modeled benefit/toxicity ratio in patients with solid tumors. It may embody the 'proof of concept' of model-based drug development of anticancer agent combinations.

Dynamic modeling in ovarian cancer: an original approach linking early changes in modeled longitudinal CA-125 kinetics and survival to help decisions in early drug development.

OBJECTIVE: Early prediction of the expected benefit of treatment in recurrent ovarian cancer (ROC) patients may help in drug development decisions. The actual value of 50% CA-125 decrease is being reconsidered. The main objective of the present study was to quantify the links between longitudinal assessments of CA-125 kinetics and progression-free survival (PFS) in treated recurrent ovarian cancer (ROC) patients. METHODS: The CALYPSO randomized phase III trial database comparing two platinum-based regimens in ROC patients was randomly split into a "learning dataset" and a "validation dataset". A parametric survival model was developed to associate longitudinal modeled CA-125 changes (ΔCA125), predictive factors, and PFS. The predictive performance of the model was evaluated with simulations. RESULTS: The PFS of 534 ROC patients were properly characterized by a parametric mathematical model. The modeled ΔCA125 from baseline to week 6 was a better predictor of PFS than the modeled fractional change in tumor size. Simulations confirmed the model's predictive performance. CONCLUSIONS: We present the first parametric survival model quantifying the relationship between PFS and longitudinal CA-125 kinetics in treated ROC patients. The model enabled calculation of the increase in ΔCA125 required to observe a predetermined benefit in PFS to compare therapeutic strategies in populations. Therefore, ΔCA125 may be a predictive marker of the expected gain in PFS and an early predictive tool in drug development decisions.

Solid oral forms availability in children: a cost saving investigation.

AIM: To assess the suitability and potential cost savings, from both the hospital and community perspective, of prescribed oral liquid medicine substitution with acceptable solid forms for children over 2 years. METHOD: Oral liquid medicines dispensed from a paediatric hospital (UK) in 1 week were assessed by screening for existence of the solid form alternative and evaluating the acceptability of the available solid form, firstly related to the prescribed dose and secondly to acceptable size depending on the child's age. Costs were calculated based on providing treatment for 28 days or prescribed duration for short term treatments. RESULTS: Over 90% (440/476) of liquid formulations were available as a marketed solid form. Considering dosage acceptability (maximum of 10% deviation from prescribed dosage or 0% for narrow therapeutic range drugs, maximum tablet divisions into quarters) 80% of liquids could be substituted with a solid form. The main limitation for liquid substitution would be solid form size. However, two-thirds of prescribed liquids could have been substituted with a suitable solid form for dosage and size, with estimated savings being of £5K and £8K in 1 week, respectively based on hospital and community costs, corresponding to a projected annual saving of £238K and £410K (single institution). CONCLUSION: Whilst not all children over 2 years will be able to swallow tablets, drug cost savings if oral liquid formulations were substituted with suitable solid dosage forms would be considerable. Given the numerous advantages of solid forms compared with liquids, this study may provide a theoretical basis for investing in supporting children to swallow tablets/capsules.

Identification of the primary mechanism of action of an insulin secretagogue from meal test data in healthy volunteers based on an integrated glucose-insulin model.

The integrated glucose-insulin (IGI) model is a previously developed semi-mechanistic model that incorporates control mechanisms for the regulation of glucose production, insulin secretion, and glucose uptake. It has been shown to adequately describe insulin and glucose profiles in both type 2 diabetics and healthy volunteers following various glucose tolerance tests. The aim of this study was to investigate the ability of the IGI model to correctly identify the primary mechanism of action of glibenclamide (Gb), based on meal tolerance test (MTT) data in healthy volunteers. IGI models with different mechanism of drug action were applied to data from eight healthy volunteers participating in a randomized crossover study with five single-dose tests (placebo and four drug arms). The study participants were given 3.5 mg of Gb, intravenously or orally, or 3.5 mg of the two main metabolites M1 and M2 intravenously, 0.5 h prior to a standardized breakfast with energy content of 1800 kJ. Simultaneous analysis of all data by nonlinear mixed effect modeling was performed using NONMEM(®). Drug effects that increased insulin secretion resulted in the best model fit, thus identifying the primary mechanism of action of Gb and metabolites as insulin secretagogues. The model also quantified the combined effect of Gb, M1 and M2 to have a fourfold maximal increase on endogenous insulin secretion, with an EC(50) of 169.1 ng mL(-1) for Gb, 151.4 ng mL(-1) for M1 and 267.1 ng mL(-1) for M2. The semi-mechanistic IGI model was successfully applied to MTT data and identified the primary mechanism of action for Gb, quantifying its effects on glucose and insulin time profiles.

Model-based design of rituximab dosage optimization in follicular non-Hodgkin's lymphoma.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: The concentration-effect relationship of rituximab in follicular lymphoma (FL) was previously described using pharmacokinetic-pharmacodynamic (PK-PD) modelling. The influence of genetic polymorphism of FCGR3A on rituximab efficacy in FL patients was included in this PK-PD model. Previous studies suggest that increasing the dose of rituximab and/or the number of infusions may lead to a better clinical response in FL. WHAT THIS STUDY ADDS: The previously validated PK-PD model can be used to design an optimized rituximab dose regimen in FL patients. Clinical trial simulation shows the potential clinical benefits of changes in rituximab dose. Optimization of the rituximab dose regimen cannot compensate for the lower response of FCGR3A-158F carriers compared with that of FCGR3A-158VV patients. AIMS Rituximab has dramatically improved the survival of patients with non-Hodgkin's lymphoma (NHL). However, studies have suggested that the dose regimen currently used (i.e. 375 mg m(-2) ) could be optimized. The aims of this study were to quantify the benefits of the new dose regimen for rituximab in follicular NHL (FL) patients using a previously validated PK-PD model and to design clinical trials investigating optimization of rituximab dosage. METHODS: A PK-PD model was used to predict progression-free survival (PFS) of FL patients treated by rituximab alone in asymptomatic FL, and those treated by rituximab combined with chemotherapy (R-CHOP) in relapsed/resistant FL. This model accounts for the influence of a polymorphism in FCGR3A, the gene encoding the FcγRIIIa receptor, on clinical efficacy. Several induction and maintenance dose regimens using rituximab alone or in combination with conventional chemotherapy (CHOP) were tested. The benefits of rituximab dose adjustment for F carriers were investigated. The numbers of subjects required for the design of two-armed clinical trials were calculated using model-predicted PFS at a power of 80%. RESULTS: The model predicted a potential benefit of 1500 mg m(-2) maintenance doses of rituximab for both rituximab monotherapy and R-CHOP. The model shows that the PFS of FCGR3A-F carriers remains lower than that of homozygous FCGR3A-VV patients, even with markedly increased rituximab doses. CONCLUSION: Our results suggest a benefit of increasing doses of rituximab in FL, both during induction and maintenance. These results need to be confirmed in controlled clinical trials.

Chemotherapeutic errors in hospitalised cancer patients: attributable damage and extra costs.

BACKGROUND: In spite of increasing efforts to enhance patient safety, medication errors in hospitalised patients are still relatively common, but with potentially severe consequences. This study aimed to assess antineoplastic medication errors in both affected patients and intercepted cases in terms of frequency, severity for patients, and costs. METHODS: A 1-year prospective study was conducted in order to identify the medication errors that occurred during chemotherapy treatment of cancer patients at a French university hospital. The severity and potential consequences of intercepted errors were independently assessed by two physicians. A cost analysis was performed using a simulation of potential hospital stays, with estimations based on the costs of diagnosis-related groups. RESULTS: Among the 6, 607 antineoplastic prescriptions, 341 (5.2%) contained at least one error, corresponding to a total of 449 medication errors. However, most errors (n = 436) were intercepted before medication was administered to the patients. Prescription errors represented 91% of errors, followed by pharmaceutical (8%) and administration errors (1%). According to an independent estimation, 13.4% of avoided errors would have resulted in temporary injury and 2.6% in permanent damage, while 2.6% would have compromised the vital prognosis of the patient, with four to eight deaths thus being avoided. Overall, 13 medication errors reached the patient without causing damage, although two patients required enhanced monitoring. If the intercepted errors had not been discovered, they would have resulted in 216 additional days of hospitalisation and cost an estimated annual total of 92,907€, comprising 69,248€ (74%) in hospital stays and 23,658€ (26%) in additional drugs. CONCLUSION: Our findings point to the very small number of chemotherapy errors that actually reach patients, although problems in the chemotherapy ordering process are frequent, with the potential for being dangerous and costly.

Therapeutic Drug Monitoring Strategies for Envarsus in De Novo Kidney Transplant Patients Using Population Modelling and Simulations.

INTRODUCTION: Tacrolimus, the cornerstone of transplantation immunosuppression, is a narrow therapeutic index drug with a low and highly variable bioavailability. Therapeutic drug monitoring based on trough level assessment is mandatory in order to target a personalised exposure and avoid both rejection and toxicity. Population pharmacokinetic (POPPK) models might be a useful tool for improving early attainment of target range by guiding initial doses until steady state is reached and trough levels can be reliably used as surrogate marker of exposure. Here we present the first POPPK for predicting the initial doses of the once-daily prolonged release tacrolimus Envarsus (LCPT) in adult kidney recipients. METHODS: The model was developed exploiting the data from a recent pharmacokinetic randomised clinical study, in which 69 de novo kidney recipients, 33 of whom treated with LCPT, underwent an intensive blood sampling strategy for tacrolimus including four complete pharmacokinetic profiles. RESULTS: The complex and prolonged absorption of LCPT is well described by the three-phase model that incorporates body weight and CYP3A5 genotype as significant covariates accounting for a great proportion of the inter-patient variability: in particular, CYP3A5*1/*3 expressors had a 66% higher LCPT clearance. We have then generated by simulation a personalised dosing strategy based on the model that could improve the early attainment of therapeutic trough levels by almost doubling the proportion of patients within target range (69.3% compared to 36.1% with the standard body weight-based approach) on post-transplantation day 4 and significantly reduce the proportion of overexposed patients at risk of toxicity. CONCLUSIONS: A POPPK model was successfully developed for LCPT in de novo kidney recipients. The model could guide a personalised dosing strategy early after transplantation. For the model to be translated into clinical practice, its beneficial impact of earlier attainment of therapeutic trough levels should be demonstrated on hard clinical outcomes in further studies.

Prognostic value of modeled PSA clearance on biochemical relapse free survival after radical prostatectomy.

PURPOSES: Using population kinetic approach, we modeled PSA decline equations in patients with prostate cancer after radical prostatectomy (RP). We looked for relationships between early PSA decrease profile, characterized by PSA clearance (CL(PSA)) or half-life (HL(PSA)), and the 2-year biochemical relapse free survival (bRFS). PATIENTS AND METHODS: We performed a retrospective study on 55 patients treated with RP and with at least 2 PSA measurements in the post-operative month. A population kinetic model was investigated with NONMEM. The prognostic factors regarding bRFS were assessed using univariate and multivariate analyses. RESULTS: The best model describing the PSA post-operative decrease was bi-compartmental and fit patient data well. Median CL(PSA) was 0.034 (terciles were 0.023 and 0.048). The significant prognostic factors associated with a better bRFS with univariate analysis were lower CL(PSA) terciles (2-year bRFS = 100% vs. 85.1% vs. 66.7% if CL(PSA) < 0.023, 0.023 or= 0.0480, P = 0.006) as well as initial PSA < 7 ng/ml, pT2 stage (vs. pT3), pN0 (vs. pN1) and low main Gleason score (3/5 vs. 4/5). Among these factors, CL(PSA) was the only independent prognostic factor with multivariate analysis regarding bRFS (HR = 0.92, 95%CI = [0.86-0.98], P = 0.0088). CONCLUSION: CL(PSA) determined with 4 PSA concentrations in the first month following the RP may predict the biochemical relapse risk of prostate cancer patients, thus enabling early identification of high-risk patients requiring adjuvant treatment. A prospective validation of these results is required.

Development of a drug-disease simulation model for rituximab in follicular non-Hodgkin's lymphoma.

AIM: Rituximab has dramatically improved the survival of patients with non-Hodgkin's lymphomas (NHL), but the dosing regimen currently used should be optimized. However, the concentration-effect relationship of rituximab has never been described by pharmacokinetic-pharmacodynamic (PK-PD) modelling, precluding the simulation of new dosing regimens. The aim of this study was to develop a PK-PD model of rituximab in relapsed/resistant follicular NHL (FL). METHODS: A model describing the relationship between rituximab concentrations and progression-free survival (PFS) was developed using data extracted from the pivotal study, which evaluated 151 relapsed/resistant FL patients. The influence of FCGR3A genetic polymorphism on the efficacy of rituximab was quantified using data from 87 relapsed/resistant FL patients. The predictive performance of the model was analysed using two independent datasets: a study that evaluated rituximab combined with chemotherapy [rituximab, cyclophosphamide, vincristine, adriamycin and prednisone (R-CHOP)] in 334 relapsed/resistant FL patients and a study that evaluated rituximab monotherapy in 47 asymptomatic FL patients with known FCGR3A genotype. RESULTS: For R-CHOP, observed and model-predicted PFS (90% confidence interval) at 24 months were 0.50 and 0.48 (0.40, 0.56), respectively, for the observation arm, and 0.62 and 0.59 (0.50, 0.65), respectively, for the rituximab maintenance arm. For rituximab monotherapy, observed and predicted PFS at 24 months were 0.67 and 0.63, respectively, for FCGR3A-V/V patients, and 0.41 and 0.36 (0.25, 0.49), respectively, for FCGR3A-F carriers. CONCLUSIONS: Our model provides a satisfactory prediction of PFS at 24 months. It can be used to simulate new dosing regimens of rituximab in populations of FL patients and should improve the design of future clinical trials.

Time-to-Event Modeling of Left- or Right-Censored Toxicity Data in Nonclinical Drug Toxicology.

A time-to-event (TTE) model has been developed to characterize a histopathology toxicity that can only be detected at the time of animal sacrifice. The model of choice was a hazard model with a Weibull distribution and dose was a significant covariate. The diagnostic plots showed a satisfactory fit of the data, despite the high degree of left and right censoring. Comparison to a probabilistic logit model shows similar performance in describing the data with a slight underestimation of survival by the Logit model. However, the TTE model was found to be more predictive in extrapolating toxicity risk beyond the observation range of a truncated dataset. The diagnostic and comparison outcomes would suggest using the TTE approach as a first choice for characterizing short and long-term risk from nonclinical toxicity studies. However, further investigations are needed to explore the domain of application of this kind of approach in drug safety assessment.