| 1. |
- Amilon, Carl, et al.
(författare)
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Population Pharmacodynamic Modeling of Eflornithine-Based Treatments Against Late-Stage Gambiense Human African Trypanosomiasis and Efficacy Predictions of L-eflornithine-Based Therapy
- 2022
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Ingår i: The AAPS journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 24:3
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Tidskriftsartikel (refereegranskat)abstract
- (Carl Amilon and Mikael Boberg contributed equally to this work) Eflornithine is a recommended treatment against late-stage gambiense human African trypanosomiasis, a neglected tropical disease. Standard dosing of eflornithine consists of repeated intravenous infusions of a racemic mixture of L- and D-eflornithine. Data from three clinical studies, (i) eflornithine intravenous monotherapy, (ii) nifurtimox-eflornithine combination therapy, and (iii) eflornithine oral monotherapy, were pooled and analyzed using a time-to-event pharmacodynamic modeling approach, supported by in vitro activity data of the individual enantiomers. Our aim was to assess (i) the efficacy of the eflornithine regimens in a time-to-event analysis and (ii) the feasibility of an L-eflornithine-based therapy integrating clinical and preclinical data. A pharmacodynamic time-to-event model was used to estimate the total dose of eflornithine, associated with 50% reduction in baseline hazard, when administered as monotherapy or in the nifurtimox-eflornithine combination therapy. The estimated total doses were 159, 60 and 291 g for intravenous eflornithine monotherapy, nifurtimox-eflornithine combination therapy and oral eflornithine monotherapy, respectively. Simulations suggested that L-eflornithine achieves a higher predicted median survival, compared to when racemate is administered, as treatment against late-stage gambiense human African trypanosomiasis. Our findings showed that oral L-eflornithine-based monotherapy would not result in adequate efficacy, even at high dose, and warrants further investigations to assess the potential of oral L-eflornithine-based treatment in combination with other treatments such as nifurtimox. An all-oral eflornithine-based regimen would provide easier access to treatment and reduce burden on patients and healthcare systems in gambiense human African trypanosomiasis endemic areas. Graphical abstract.
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| 2. |
- Aoki, Yasunori, et al.
(författare)
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Preconditioning of Nonlinear Mixed Effects Models for Stabilisation of Variance-Covariance Matrix Computations
- 2016
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 18:2, s. 505-518
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Tidskriftsartikel (refereegranskat)abstract
- As the importance of pharmacometric analysis increases, more and more complex mathematical models are introduced and computational error resulting from computational instability starts to become a bottleneck in the analysis. We propose a preconditioning method for non-linear mixed effects models used in pharmacometric analyses to stabilise the computation of the variance-covariance matrix. Roughly speaking, the method reparameterises the model with a linear combination of the original model parameters so that the Hessian matrix of the likelihood of the reparameterised model becomes close to an identity matrix. This approach will reduce the influence of computational error, for example rounding error, to the final computational result. We present numerical experiments demonstrating that the stabilisation of the computation using the proposed method can recover failed variance-covariance matrix computations, and reveal non-identifiability of the model parameters.
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| 3. |
- Arrington, Leticia, et al.
(författare)
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Comparison of Two Methods for Determining Item Characteristic Functions and Latent Variable Time-Course for Pharmacometric Item Response Models
- 2024
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Ingår i: AAPS Journal. - : Springer. - 1550-7416. ; 26
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Tidskriftsartikel (refereegranskat)abstract
- There are examples in the literature demonstrating different approaches to defining the item characteristic functions (ICF) and characterizing the latent variable time-course within a pharmacometrics item response theory (IRT) framework. One such method estimates both the ICF and latent variable time-course simultaneously, and another method establishes the ICF first then models the latent variable directly. To date, a direct comparison of the "simultaneous" and "sequential" methodologies described in this work has not yet been systematically investigated. Item parameters from a graded response IRT model developed from Parkinson's Progression Marker Initiative (PPMI) study data were used as simulation parameters. Each method was evaluated under the following conditions: (i) with and without drug effect and (ii) slow progression rate with smaller sample size and rapid progression rate with larger sample size. Overall, the methods performed similarly, with low bias and good precision for key parameters and hypothesis testing for drug effect. The ICF parameters were well determined when the model was correctly specified, with an increase in precision in the scenario with rapid progression. In terms of drug effect, both methods had large estimation bias for the slow progression rate; however, this bias can be considered small relative to overall progression rate. Both methods demonstrated type 1 error control and similar discrimination between model with and without drug effect. The simultaneous method was slightly more precise than the sequential method while the sequential method was more robust towards longitudinal model misspecification and offers practical advantages in model building.
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| 4. |
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| 5. |
- Backhaus, Thomas, 1967
(författare)
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Environmental Risk Assessment of Pharmaceutical Mixtures: Demands, Gaps, and Possible Bridges
- 2016
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Ingår i: Aaps Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 18:4, s. 804-813
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Tidskriftsartikel (refereegranskat)abstract
- The ecotoxicological risk of pharmaceutical mixtures typically exceeds the risk of each individual compound, which calls specific attention to the fact that monitoring surveys routinely find complex pharmaceutical mixtures in various environmental compartments. However, although the body of evidence on the ecotoxicology of pharmaceutical mixtures is quite consistent, the current guidelines for the environmental risk assessment of pharmaceuticals often do not explicitly address mixture effects. Data availability and acceptable methods often limit such assessments. A tiered approach that begins with summing up individual risk quotients, i.e., the ratio between the predicted or measured environmental concentration and the predicted no effect concentration (PNEC) is therefore suggested in this paper, in order to improve the realism of the environmental risk assessment of pharmaceuticals. Additionally, the use of a mixture-specific assessment factor, as well as the classical mixture toxicity concepts of concentration addition and independent action is explored. Finally, specific attention is given to the exposure-based waiving of environmental risk assessments, as currently implemented in screening or pre-screening phases (tier 0 in Europe, categorical exclusion in the USA), since even low, individually non-toxic concentrations might combine to produce substantial mixture effects.
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| 6. |
- Bender, Brendan, et al.
(författare)
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A Mechanistic Pharmacokinetic Model Elucidating the Disposition of Trastuzumab Emtansine (T-DM1), an Antibody-Drug Conjugate (ADC) for Treatment of Metastatic Breast Cancer
- 2014
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 16:5, s. 994-1008
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Tidskriftsartikel (refereegranskat)abstract
- Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate (ADC) therapeutic for treatment of human epidermal growth factor receptor 2 (HER2)-positive cancers. The T-DM1 dose product contains a mixture of drug-to-antibody ratio (DAR) moieties whereby the small molecule DM1 is chemically conjugated to trastuzumab antibody. The pharmacokinetics (PK) underlying this system and other ADCs are complex and have not been elucidated. Accordingly, we have developed two PK modeling approaches from preclinical data to conceptualize and understand T-DM1 PK, to quantify rates of DM1 deconjugation, and to elucidate the link between trastuzumab, T-DM1, and DAR measurements. Preclinical data included PK studies in rats (n = 34) and cynomolgus monkeys (n = 18) at doses ranging from 0.3 to 30 mg/kg and in vitro plasma stability. T-DM1 and total trastuzumab (TT) plasma concentrations were measured by enzyme-linked immunosorbent assay. Individual DAR moieties were measured by affinity capture liquid chromatography-mass spectrophotometry. Two PK modeling approaches were developed for T-DM1 using NONMEM 7.2 software: a mechanistic model fit simultaneously to TT and DAR concentrations and a reduced model fit simultaneously to TT and T-DM1 concentrations. DAR moieties were well described with a three-compartmental model and DM1 deconjugation in the central compartment. DM1 deconjugated fastest from the more highly loaded trastuzumab molecules (i.e., DAR moieties that are a parts per thousand yen3 DM1 per trastuzumab). T-DM1 clearance (CL) was 2-fold faster than TT CL due to deconjugation. The two modeling approaches provide flexibility based on available analytical measurements for T-DM1 and a framework for designing ADC studies and PK-pharmacodynamic modeling of ADC efficacy- and toxicity-related endpoints.
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| 7. |
- Bergstrand, Martin, et al.
(författare)
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Handling data below the limit of quantification in mixed effect models.
- 2009
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 11:2, s. 371-380
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of this study is to investigate the impact of observations below the limit of quantification (BQL) occurring in three distinctly different ways and assess the best method for prevention of bias in parameter estimates and for illustrating model fit using visual predictive checks (VPCs). Three typical ways in which BQL can occur in a model was investigated with simulations from three different models and different levels of the limit of quantification (LOQ). Model A was used to represent a case with BQL observations in an absorption phase of a PK model whereas model B represented a case with BQL observations in the elimination phase. The third model, C, an indirect response model illustrated a case where the variable of interest in some cases decreases below the LOQ before returning towards baseline. Different approaches for handling of BQL data were compared with estimation of the full dataset for 100 simulated datasets following models A, B, and C. An improved standard for VPCs was suggested to better evaluate simulation properties both for data above and below LOQ. Omission of BQL data was associated with substantial bias in parameter estimates for all tested models even for seemingly small amounts of censored data. Best performance was seen when the likelihood of being below LOQ was incorporated into the model. In the tested examples this method generated overall unbiased parameter estimates. Results following substitution of BQL observations with LOQ/2 were in some cases shown to introduce bias and were always suboptimal to the best method. The new standard VPCs was found to identify model misfit more clearly than VPCs of data above LOQ only.
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| 8. |
- Bergstrand, Martin, 1977-, et al.
(författare)
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Prediction-Corrected Visual Predictive Checks for Diagnosing Nonlinear Mixed-Effects Models
- 2011
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 13:2, s. 143-151
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Tidskriftsartikel (refereegranskat)abstract
- Informative diagnostic tools are vital to the development of useful mixed-effects models. The Visual Predictive Check (VPC) is a popular tool for evaluating the performance of population PK and PKPD models. Ideally, a VPC will diagnose both the fixed and random effects in a mixed-effects model. In many cases, this can be done by comparing different percentiles of the observed data to percentiles of simulated data, generally grouped together within bins of an independent variable. However, the diagnostic value of a VPC can be hampered by binning across a large variability in dose and/or influential covariates. VPCs can also be misleading if applied to data following adaptive designs such as dose adjustments. The prediction-corrected VPC (pcVPC) offers a solution to these problems while retaining the visual interpretation of the traditional VPC. In a pcVPC, the variability coming from binning across independent variables is removed by normalizing the observed and simulated dependent variable based on the typical population prediction for the median independent variable in the bin. The principal benefit with the pcVPC has been explored by application to both simulated and real examples of PK and PKPD models. The investigated examples demonstrate that pcVPCs have an enhanced ability to diagnose model misspecification especially with respect to random effects models in a range of situations. The pcVPC was in contrast to traditional VPCs shown to be readily applicable to data from studies with a priori and/or a posteriori dose adaptations.
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| 9. |
- Bergström, Christel A. S., et al.
(författare)
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Lipophilicity in Drug Development : Too Much or Not Enough?
- 2016
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 18:5, s. 1095-1100
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Tidskriftsartikel (refereegranskat)abstract
- A round table discussion was held during the AAPS Annual Meeting on October 27, 2015, with the somewhat provocative topic of whether we need more or less lipophilic compounds in drug development. The session was attended by more than 250 participants, and the feedback was very positive as this round table became a forum for the exchange of ideas from scientists within the academia and industry. Most importantly, the discussion highlighted the difference in approaches to compound selection and development strategies in various companies and organizations. As moderators of this session, we are writing this report to highlight the points and counterpoints made at the session and to bring the importance of the dialogue and debate to the forefront of discussions on how to select the best drug development candidates to enable efficient delivery and, hence, treatment of diseases.
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| 10. |
- Bizzotto, Roberto, et al.
(författare)
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Multinomial Logistic Functions in Markov Chain Models of Sleep Architecture : Internal and External Validation and Covariate Analysis
- 2011
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 13:3, s. 445-463
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Tidskriftsartikel (refereegranskat)abstract
- Mixed-effect Markov chain models have been recently proposed to characterize the time course of transition probabilities between sleep stages in insomniac patients. The most recent one, based on multinomial logistic functions, was used as a base to develop a final model combining the strengths of the existing ones. This final model was validated on placebo data applying also new diagnostic methods and then used for the inclusion of potential age, gender, and BMI effects. Internal validation was performed through simplified posterior predictive check (sPPC), visual predictive check (VPC) for categorical data, and new visual methods based on stochastic simulation and estimation and called visual estimation check (VEC). External validation mainly relied on the evaluation of the objective function value and sPPC. Covariate effects were identified through stepwise covariate modeling within NONMEM VI. New model features were introduced in the model, providing significant sPPC improvements. Outcomes from VPC, VEC, and external validation were generally very good. Age, gender, and BMI were found to be statistically significant covariates, but their inclusion did not improve substantially the model's predictive performance. In summary, an improved model for sleep internal architecture has been developed and suitably validated in insomniac patients treated with placebo. Thereafter, covariate effects have been included into the final model.
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