Model-Based Selection and Recommendation for Subcutaneous Abatacept Dose in Patients With Polyarticular Juvenile Idiopathic Arthritis.

The selective T-cell costimulation modulator abatacept is approved for treatment of adult rheumatoid arthritis (RA) and polyarticular juvenile idiopathic arthritis (pJIA; 6-17 years [intravenous] and 2-17 years [subcutaneous]). An extrapolation approach was taken to determine subcutaneous weight-tiered doses of abatacept to evaluate in patients with pJIA. Population pharmacokinetic (PPK) and exposure-response (E-R) analyses were conducted to determine whether the weight-tiered subcutaneous regimen provides near-maximal efficacy and is therapeutically comparable to the intravenous regimen in patients with pJIA aged 2-17 years. Combined study data from intravenous or subcutaneous abatacept were used to assess clinically relevant exposure outcomes. The PPK model was developed with data from 13 phase 2/3 studies in RA and pJIA; the E-R model for the American College of Rheumatology pediatric scores (JIA-ACR 30/50/70/100 responses) in month 4 was developed with data from 2 phase 3 pJIA studies. Predefined covariates were investigated in both analyses. PPK model-predicted exposures were steady-state peak, trough (Cminss ), and time-averaged concentrations. Abatacept PK was characterized by a linear 2-compartment model (zero-order intravenous infusion, first-order subcutaneous absorption, first-order elimination); body weight was the only clinically relevant covariate. Cminss was the best exposure predictor for the JIA-ACR response: log odds for response increased in proportion to log-transformed Cminss ; JIA-ACR30 approached a plateau when Cminss ≥ 10 µg/mL. The PPK and E-R analyses demonstrated that the weight-tiered subcutaneous and intravenous abatacept dosing regimens provide near-maximal efficacy and are clinically comparable across children with pJIA who are > 2 years old.

Pharmacokinetic-pharmacodynamic (dipeptidyl peptidase-4 inhibition) model to support dose rationale in diabetes patients, including those with renal impairment, for once-weekly administered omarigliptin.

AIMS: To characterize the population pharmacokinetics (PK) and pharmacodynamics (PD) of the once-weekly dipeptidyl peptidase-4 (DPP-4) inhibitor omarigliptin in healthy subjects and patients with type 2 diabetes mellitus, and use these models to support the dosing recommendation for patient labelling including patients with renal impairment. METHODS: PK and PD were assessed from a total of 9827 omarigliptin concentrations collected from 1387 healthy subjects and patients participating in Phase 1, 2 and 3 studies examining single- or multiple-dose weekly administration of omarigliptin at doses ranging from 0.25 to 400 mg. Population PK and PD analyses were performed using nonlinear mixed effect modelling. RESULTS: A semi-mechanistic 2-compartment model with linear unbound clearance and concentration-dependent binding of omarigliptin to the DPP-4 enzyme in both the central and peripheral compartments adequately described omarigliptin PK. Key covariates on omarigliptin PK included reduced unbound clearance with renal impairment. A direct effect sigmoid maximum inhibitory efficacy model adequately described the relationship between omarigliptin plasma concentrations and DPP-4 inhibition. These models supported the current Japan label instructions that the approved omarigliptin 25-mg once-weekly dose be halved in patients with severe renal impairment and in those with end-stage renal disease. Also, if patients missed a dose, the next dose of omarigliptin should be taken as soon as remembered up to and including the day before the next scheduled dose. No other clinically important covariates were identified. CONCLUSION: The models in the present analysis adequately described PK and PD characteristics of omarigliptin and supported the dosing and administration section of the omarigliptin label.

Population Pharmacokinetics and Exposure-Response Analyses of Eslicarbazepine Acetate Efficacy and Safety in Monotherapy of Partial-Onset Seizures.

Eslicarbazepine acetate (ESL) is a once-daily oral antiepileptic drug (AED) indicated for partial-onset seizures (POS). ESL pharmacokinetics (PK) and exposure-response analyses were supported by 2 phase 3 conversion to ESL (1200, 1600 mg) monotherapy studies. The PK model development included 10 phase 1-2 studies (ESL 600-1200 mg daily). Seizure diaries were completed daily; subjects exited if seizures worsened. Exposure-response models were developed for time to study exit, probability of seizure freedom, time to first occurrence of dizziness, headache, and nausea; serum sodium levels were explored. A 1-compartment model with first-order absorption/elimination described ESL PK. Clearance and distribution volume were significantly related to body weight and sex. Higher eslicarbazepine minimum concentration (Cmin ) and use of 1 baseline AED were associated with significantly lower risk of study exit, whereas eslicarbazepine Cmin was a significant predictor of seizure freedom during the last 4 weeks of monotherapy. Eslicarbazepine exposure and the time to first occurrence of adverse events were not related. A shallow negative relationship described the relationship between change from baseline in serum sodium level and eslicarbazepine exposure. Eslicarbazepine apparent clearance and distribution volume estimates were similar to those reported for ESL adjunctive therapy. Dose adjustment based on body weight was not required. The time to study exit and probability of seizure freedom during the last 4 weeks of monotherapy were weakly related to eslicarbazepine exposure. Because the first occurrence of adverse events or hyponatremia were also not significantly related to eslicarbazepine exposure, dose adjustment using plasma eslicarbazepine concentrations is not supported.

Prediction of efficacy for conversion from adjunctive therapy to monotherapy with eslicarbazepine acetate 800 mg once daily for partial-onset epilepsy.

PURPOSE: Eslicarbazepine acetate (ESL) is a once-daily (QD) oral antiepileptic drug (AED) indicated for partial-onset seizures (POS). Clinical studies of gradual conversion to ESL 1,200 and 1,600 mg QD monotherapies were previously conducted in patients with POS who were not well-controlled by 1 or 2 AEDs. This report describes modeling and simulation of plasma eslicarbazepine (primary active metabolite of ESL) concentrations and time to monotherapy study exit to predict efficacy for conversion to ESL monotherapy at a lower dose of 800 mg, as an option for patients requiring or not tolerating higher doses since this regimen is effective in adjunctive therapy for POS. PATIENTS AND METHODS: A previously developed population pharmacokinetic model for ESL monotherapy was used to predict minimum plasma eslicarbazepine concentration (Cmin) in 1,500 virtual patients taking 1 (n=1,000) or 2 (n=500) AEDs at baseline, treated with ESL 400 mg QD for 1 week, followed by 800 mg QD for 17 weeks (similar to ESL monotherapy trials where the other AEDs were withdrawn during the first 6 weeks following titration to the randomized ESL dose). Model-predicted Cmin as a time-varying covariate and number of baseline AEDs were used to determine the weekly probability of each patient meeting exit criteria (65.3% threshold) indicative of worsening seizure control in 500 simulated ESL monotherapy trials. A previously developed extended Cox proportional hazards exposure-response model was used to relate time-varying eslicarbazepine exposure to the time to study exit. RESULTS: For virtual patients receiving ESL monotherapy (800 mg QD), the 95% upper prediction limit for exit rate at 112 days of 34.9% in patients taking 1 AED at baseline was well below the 65.3% threshold from historical control trials, while the estimate for patients taking 2 AEDs (70.6%) was slightly above the historical control threshold. CONCLUSION: This model-based assessment supports conversion to ESL 800 mg QD monotherapy for POS in adults taking 1 AED. For patients taking 2 concomitant AEDs, however, prescribers should consider maintenance doses of 1,200 or 1,600 mg ESL QD to reduce the likelihood of seizure worsening if conversion to ESL monotherapy is contemplated.

Pharmacokinetics and Exposure-Response Relationships of Dasotraline in the Treatment of Attention-Deficit/Hyperactivity Disorder in Adults.

BACKGROUND AND OBJECTIVES: Dasotraline is a novel inhibitor of dopamine and norepinephrine reuptake currently being investigated in clinical studies for the treatment of attention-deficit/hyperactivity disorder (ADHD). Uniquely, relative to current ADHD medications, dasotraline has a slow absorption and long elimination half-life. Here we relate the pharmacokinetics and pharmacodynamics of dasotraline to reduction in ADHD symptoms based on simulated clinical trial outcomes. METHODS: Dasotraline pharmacokinetics were analyzed by population pharmacokinetic methodologies using data collected from 395 subjects after single or multiple oral dose administrations ranging from 0.2 to 36 mg (three phase I studies and one phase II ADHD study). Population pharmacokinetic and pharmacodynamic models related individual dasotraline exposures to norepinephrine metabolite 3,4-dihydroxyphenylglycol (DHPG) concentrations, ADHD symptoms, and study discontinuation (probability of dropout). RESULTS: Dasotraline pharmacokinetics were described by a one-compartment model with dual (linear plus nonlinear) elimination. In an ADHD population treated with dasotraline 4 or 8 mg/day, dasotraline was characterized by a mean apparent half-life of 47 h and plasma concentrations reached steady-state by 10 days of dosing. A population pharmacokinetic and pharmacodynamic model of DHPG indicated clinically significant norepinephrine transporter inhibition was achieved as a function of time-matched dasotraline concentrations. Dasotraline exposure reduced ADHD symptoms in a sigmoid E max time-course model. Clinical trial simulations described the effects of dose, duration, and sample size on clinical outcomes. CONCLUSION: These results related dasotraline pharmacokinetics to pharmacological activity in ADHD, and support the novel concept that maintaining constant, steady-state dopamine and norepinephrine reuptake inhibition throughout a 24-h dosing interval is a novel pharmacological approach to the management of ADHD symptoms. Clinicaltrials.gov identifier: NCT01692782.

Bendamustine pharmacokinetic profile and exposure-response relationships in patients with indolent non-Hodgkin's lymphoma.

PURPOSE: The pharmacokinetic profiles of bendamustine and active metabolites were defined in patients with rituximab-refractory, relapsed indolent B-cell non-Hodgkin's lymphoma, and supported understanding of exposure-response relationships for efficacy and safety. METHODS: Bendamustine was administered as a 60-min 120 mg/m(2) intravenous infusion on days 1 and 2 of six 21-day cycles. Pharmacokinetic models were developed, with covariate assessment. Correlations between bendamustine exposure and responder status or occurrence of neutropenia, thrombocytopenia, fatigue, nausea, and vomiting were examined. RESULTS: Following a single dose of bendamustine HCl, concentrations declined in a triphasic manner, with rapid distribution, intermediate, and slow terminal phases. The intermediate t (1/2) (40 min) was considered the pharmacologically relevant (beta elimination) t (1/2) since the initial phases accounted for 99% of the AUC. Age, sex, mild/moderate renal, or mild liver impairment did not alter pharmacokinetics. Metabolite concentrations were low relative to parent. No correlation was observed between exposure and safety or efficacy measures because of the limited range of exposures after 120 mg/m(2) administration, except bendamustine C (max) was a significant (P value = 0.013) predictor of the probability of nausea in patients, most of whom were pretreated with antiemetics. CONCLUSIONS: The BSA-based dosing regimen for bendamustine achieved the targeted exposure and was associated with a high incidence of therapeutic response. Given the short t (1/2) and low concentrations of bendamustine observed by 12 h after dosing, the single-dose profile for bendamustine described by these analyses is expected to be representative of the multiple-dose profile. The occurrence of nausea was significantly related to bendamustine exposure, with the probability of nausea increasing as bendamustine C (max) increases.

Application of patient population-derived pharmacokinetic-pharmacodynamic relationships to tigecycline breakpoint determination for staphylococci and streptococci.

Correctly determined susceptibility breakpoints are important to both the individual patient and to society at large. A previously derived patient population pharmacokinetic model and Monte Carlo simulation (9999 patients) were used to create a likelihood distribution of tigecycline exposure, as measured by the area under the concentration-time curve at 24 h (AUC(24)). Each resultant AUC(24) value was paired with a clinically relevant fixed MIC value ranging from 0.12 to 2 mg/L. For each AUC(24)-MIC pair, the probability of microbiologic response was calculated using an exposure-response relationship, which was derived from patients with complicated skin and skin structure infections that involved Staphylococcus aureus or streptococci or both. The median probability of microbiologic success was 94% or greater for MIC values up to and including 0.25 mg/L. The median probability of microbiologic success was 66% or less for MIC values of 0.5 mg/L or greater. These data support a susceptibility breakpoint of 0.25 mg/L for S. aureus and streptococci.

Use of a clinically derived exposure-response relationship to evaluate potential tigecycline-Enterobacteriaceae susceptibility breakpoints.

Potential tigecycline-Enterobacteriaceae susceptibility breakpoints were evaluated using 2 approaches, which differed in the nature of the probabilities assessed by MIC value. Using a previously derived tigecycline population pharmacokinetic model and Monte Carlo simulation, a probability density function of steady-state area under the concentration-time curve for 24 h (AUC(SS(0-24))) values for 9999 patients was generated. AUC(SS(0-24)) values were divided by clinically relevant fixed MIC values to derive AUC(SS(0-24))/MIC ratios, which were used to calculate the clinical response expectation by MIC value based upon a logistic regression model for efficacy (1st approach). For the 2nd approach, the probability of pharmacokinetic-pharmacodynamic (PK-PD) target attainment was calculated as the proportion of patients with AUC(SS(0-24))/MIC ratios greater than the threshold value of 6.96, the PK-PD target associated with optimal clinical response. Probabilities of clinical response and PK-PD target attainment were poorly correlated at MIC values >0.25 mg/L. For instance, the median probability of clinical success was 0.76, whereas the probability of PK-PD target attainment was 0.27 at an MIC value of 1 mg/L, suggesting that the probability of PK-PD target attainment metrics underestimates the clinical performance of tigecycline at higher MIC values.

Semimechanistic pharmacokinetic/pharmacodynamic model for hepatoprotective effect of dexamethasone on transient transaminitis after trabectedin (ET-743) treatment.

PURPOSE: Reversible transient elevations in transaminases have been observed after trabectedin administration. A semimechanistic pharmacokinetic and pharmacodynamic (PKPD) model was developed to evaluate the time course of alanine aminotransferase (ALT) elevation, tolerance development, and the hepatoprotective effect of dexamethasone on trabectedin-induced transient transaminitis following different dosing schedules in cancer patients. PATIENTS AND METHODS: Trabectedin was administered to 711 patients as monotherapy (dose range: 0.024-1.8 mg/m(2)) as 1-, 3-, or 24-h infusions every 21 days; 1- or 3-h infusions on days 1, 8, and 15 every 28 days; or 1-h infusions daily for five consecutive days every 21 days. Population PKPD modeling was performed with covariate evaluation [dexamethasone use (469/711 pt), ECOG performance status scores (89.7% pts or=3 toxicity by 13 and 39% following two and four cycles of therapy, respectively. CONCLUSIONS: A PKPD model quantifying the hepatoprotective effect of dexamethasone on transient and reversible transaminitis following trabectedin treatment has been developed. The model predicts that co-administration of dexamethasone and the suggested dose reduction strategy based on the serum concentration of liver enzymes will enhance the safe use of trabectedin in the clinic.

Pharmacokinetic-pharmacodynamic relationships describing the efficacy of oritavancin in patients with Staphylococcus aureus bacteremia.

Bloodstream infections due to antimicrobial-resistant Staphylococcus aureus occur with increasing frequency and represent an important cause of morbidity and mortality. To date, the evaluation of pharmacokinetic-pharmacodynamic relationships for efficacy among patients with bacteremia has been limited. The objectives of these analyses were to evaluate relationships between microbiological and clinical responses for patients with S. aureus bacteremia and exposures for oritavancin, a novel bactericidal glycopeptide in development. Bayesian oritavancin exposure predictions, following treatment with 5, 6.5, 8, or 10 mg/kg of body weight/day, were derived using a validated population pharmacokinetic model for 55 patients with S. aureus bacteremia. Using classification and regression tree analysis, a breakpoint of the percentage of the dosing interval duration for which free-drug concentrations were above the MIC (free-drug % time > MIC) of 22% was identified for microbiological response; the probabilities of success greater than or equal to and less than this value were 93% and 76%, respectively. Using logistic regression, a relationship was found between microbiological response and free-drug % time > MIC (odds ratio = 4.42, P = 0.09, and odds ratio = 8.84, P = 0.05, when one patient, a medical outlier, was excluded). A similar relationship was found for clinical response. These results will be valuable in supporting dose selection of oritavancin for patients with S. aureus bacteremia.

Challenges in the transition to model-based development.

Practitioners of the art and science of pharmacometrics are well aware of the considerable effort required to successfully complete modeling and simulation activities for drug development programs. This is particularly true because of the current, ad hoc implementation wherein modeling and simulation activities are piggybacked onto traditional development programs. This effort, coupled with the failure to explicitly design development programs around modeling and simulation, will continue to be an important obstacle to the successful transition to model-based drug development. Challenges with timely data availability, high data discard rates, delays in completing modeling and simulation activities, and resistance of development teams to the use of modeling and simulation in decision making are all symptoms of an immature process capability for performing modeling and simulation. A process that will fulfill the promise of model-based development will require the development and deployment of three critical elements. The first is the infrastructure--the data definitions and assembly processes that will allow efficient pooling of data across trials and development programs. The second is the process itself--developing guidelines for deciding when and where modeling and simulation should be applied and the criteria for assessing performance and impact. The third element concerns the organization and culture--the establishment of truly integrated, multidisciplinary, and multiorganizational development teams trained in the use of modeling and simulation in decision-making. Creating these capabilities, infrastructure, and incentivizations are critical to realizing the full value of modeling and simulation in drug development.