| 1. |
- Karlsson, Kristin E, 1975-
(författare)
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Benefits of Pharmacometric Model-Based Design and Analysis of Clinical Trials
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Quantitative pharmacokinetic-pharmacodynamic and disease progression models are the core of the science of pharmacometrics which has been identified as one of the strategies that can make drug development more effective. To adequately develop and utilize these models one needs to carefully consider the nature of the data, choice of appropriate estimation methods, model evaluation strategies, and, most importantly, the intended use of the model. The general aim of this thesis was to investigate how the use of pharmacometric models can improve the design and analysis of clinical trials within drug development. The development of pharmacometric models for clinical assessment scales in stroke and graded severity events, in this thesis, show the benefit of describing data as close to its true nature as possible, as it increases the predictive abilities and allows for mechanistic interpretations of the models. Performance of three estimation methods implemented in the mixed-effects modeling software NONMEM; 1) Laplace, 2) SAEM, and 3) Importance sampling, applied when modeling repeated time-to-event data, was investigated. The two latter methods are to be preferred if less than approximately half of the individuals experience events. In addition, predictive performance of two validation procedures, internal and external validation, was explored, with internal validation being preferred in most cases. Model-based analysis was compared to conventional methods by the use of clinical trial simulations and the power to detect a drug effect was improved with a pharmacometric design and analysis. Throughout this thesis several examples have shown the possibility of significantly reducing sample sizes in clinical trials with a pharmacometric model-based analysis. This approach will reduce time and costs spent in the development of new drug therapies, but foremost reduce the number of healthy volunteers and patients exposed to experimental drugs.
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| 2. |
- Karlsson, Kristin E, et al.
(författare)
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Comparisons of Analysis Methods for Proof-of-Concept Trials
- 2013
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Ingår i: CPT. - : Wiley. - 2163-8306. ; 2, s. e23-
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Tidskriftsartikel (refereegranskat)abstract
- Drug development struggles with high costs and time consuming processes. Hence, a need for new strategies has been accentuated by many stakeholders in drug development. This study proposes the use of pharmacometric models to rationalize drug development. Two simulated examples, within the therapeutic areas of acute stroke and type 2 diabetes, are utilized to compare a pharmacometric model–based analysis to a t-test with respect to study power of proof-of-concept (POC) trials. In all investigated examples and scenarios, the conventional statistical analysis resulted in several fold larger study sizes to achieve 80% power. For a scenario with a parallel design of one placebo group and one active dose arm, the difference between the conventional and pharmacometric approach was 4.3- and 8.4-fold, for the stroke and diabetes example, respectively. Although the model-based power depend on the model assumptions, in these scenarios, the pharmacometric model–based approach was demonstrated to permit drastic streamlining of POC trials.
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| 3. |
- Karlsson, Kristin E., et al.
(författare)
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Modeling Disease Progression in Acute Stroke Using Clinical Assessment Scales
- 2010
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 12:4, s. 683-691
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Tidskriftsartikel (refereegranskat)abstract
- This article demonstrates techniques for describing and predicting disease progression in acute stroke by modeling scores measured using clinical assessment scales, accommodating dropout as an additional source of information. Scores assessed using the National Institutes of Health Stroke Scale and the Barthel Index in acute stroke patients were used to model the time course of disease progression. Simultaneous continuous and probabilistic models for describing the nature and magnitude of score changes were developed, and used to model the trajectory of disease progression using scale scores. The models described the observed data well, and exhibited good simulation properties. Applications include longitudinal analysis of stroke scale data, clinical trial simulation, and prognostic forecasting. Based upon experience in other areas, it is likely that application of this modeling methodology will enable reductions in the number of patients needed to carry out clinical studies of treatments for acute stroke.
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| 4. |
- Karlsson, Kristin E., et al.
(författare)
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Performance of three estimation methods in repeated time-to-event modeling
- 2011
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 13:1, s. 83-91
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Tidskriftsartikel (refereegranskat)abstract
- It is not uncommon that the outcome measurements, symptoms or side effects, of a clinical trial belong to the family of event type data, e.g., bleeding episodes or emesis events. Event data is often low in information content and the mixed-effects modeling software NONMEM has previously been shown to perform poorly with low information ordered categorical data. The aim of this investigation was to assess the performance of the Laplace method, the stochastic approximation expectation-maximization (SAEM) method, and the importance sampling method when modeling repeated time-to-event data. The Laplace method already existed, whereas the two latter methods have recently become available in NONMEM 7. A stochastic simulation and estimation study was performed to assess the performance of the three estimation methods when applied to a repeated time-to-event model with a constant hazard associated with an exponential interindividual variability. Various conditions were investigated, ranging from rare to frequent events and from low to high interindividual variability. The method performance was assessed by parameter bias and precision. Due to the lack of information content under conditions where very few events were observed, all three methods exhibit parameter bias and imprecision, however most pronounced by the Laplace method. The performance of the SAEM and importance sampling were generally higher than Laplace when the frequency of individuals with events was less than 43%, while at frequencies above that all methods were equal in performance.
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| 5. |
- Plan, Elodie L., et al.
(författare)
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Approaches to simultaneous analysis of frequency and severity of symptoms
- 2010
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Ingår i: Clinical Pharmacology and Therapeutics. - : Springer Science and Business Media LLC. - 0009-9236 .- 1532-6535. ; 88:2, s. 255-259
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Tidskriftsartikel (refereegranskat)abstract
- Mechanistic models that synthesize pharmacological and (patho) physiological process information provide a rich basis for the characterization of drug action. However, the underlying clinical data are often simplified in a manner that does not allow models to fully elucidate the structure of the drug effect. In this article, we describe data-simplification strategies that are in routine use to describe disease symptoms and compare them with a model developed for handling the true complexities of the data.
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| 6. |
- Plan, Elodie L, et al.
(författare)
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Transient Lower Esophageal Sphincter Relaxations PKPD Modeling : Count Model and Repeated Time-To-Event Model
- 2011
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Ingår i: Journal of Pharmacology and Experimental Therapeutics. - : American Society for Pharmacology & Experimental Therapeutics (ASPET). - 0022-3565 .- 1521-0103.
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Tidskriftsartikel (refereegranskat)abstract
- Transient lower esophageal sphincter relaxation (TLESR) is the major mechanism for gastro-esophageal reflux. Characterization of candidate compounds for reduction of TLESRs are traditionally done through summary exposure and response measures and would benefit from model-based analyses of exposure-TLESR events relationships. PKPD modeling approaches treating TLESR either as count data or as repeated time-to-event (RTTE) data were developed and compared in terms of ability to characterize system and drug characteristics. Vehicle data comprising 294 TLESR events were collected from 9 dogs. Compound (WIN55251-2) data containing 66 TLESR events, as well as plasma concentrations, were obtained from 4 dogs. Each experiment lasted for 45min and was initiated with a meal. Counts in equispaced 5-min intervals and 1-min intervals were modeled based on a Poisson probability distribution model. TLESR events were analyzed with the RTTE model. PK was connected to PD models with a 1-compartment model. Vehicle data were described by a baseline and a surge function; the surge peak was determined around 9.69min by all approaches and its width of 5min (1-min count and RTTE) or 10min (5-min count). TLESRs inhibition by WIN55251-2 was described by an Imax model, with an IC50 of on average 2.39nmol.L-1. Modeling approaches utilizing count or RTTE data linked to a dynamic PKPD representation of exposure is superior to using summary PK and PD measures. Differences in terms of predictions and power to detect a significant drug effect are illustrated with a simulation-based investigation, and a range of diagnostics for such modeling approaches is presented.
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| 7. |
- Szamota-Leandersson, Karolina, et al.
(författare)
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Correlated development of a (2x2) reconstruction and acharge accumulation layer on the InAs(111)-Bi surface
- 2011
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Ingår i: Surface Science. - : Elsevier BV. - 0039-6028 .- 1879-2758. ; 605:1-2, s. 12-17
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Tidskriftsartikel (refereegranskat)abstract
- We have studied the formation of a Bi induced (2x2) reconstruction on the InAs(111)Bsurface. In connection to the development of the (2x2) reconstruction, a two dimensionalcharge accumulation layer located in the bottom of the InAs conduction band appears as seenthrough a photoemission structure at the Fermi level. Not well ordered Bi layers do not inducea charge accumulation. The Bi induced reconstruction reduces the polarisation of the pristinesurface and changes the initial charge distribution. InAsBi alloying occurs below the surfacewhere Bi act as charge donor leading to the charge accumulation layer.
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| 8. |
- Ahn, Jae Eun, et al.
(författare)
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Modeling longitudinal daily seizure frequency data from pregabalin add-on treatment
- 2012
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Ingår i: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 52:6, s. 880-892
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of this study was to describe longitudinal daily seizure count data with respect to the effects of time and pregabalin add-on therapy. Models were developed in step-wise manner: base model, time effect model, and time and drug effect (final) model, using a negative binomial distribution with Markovian features. Mean daily seizure count (λ) was estimated to be 0.385 (RSE 3.09%) and was further increased depending on the seizure count on the previous day. An overdispersion parameter (OVDP), representing extra-Poisson variation, was estimated to be 0.330 (RSE 11.7%). Inter-individual variances on λ and OVDP were 84.7% and 210%, respectively. Over time, λ tended to increase exponentially with a rate constant of 0.272 year-1 (RSE 26.8%). A mixture model was applied to classify responders/non-responders to pregabalin treatment. Within the responders, λ decreased exponentially with respect to dose with a constant of 0.00108 mg-1 (RSE 11.9%). The estimated responder rate was 66% (RSE 27.6%). Simulation-based diagnostics showed the model reasonably reproduced the characteristics of observed data. Highly variable daily seizure frequency was successfully characterized incorporating baseline characteristics, time effect, and the effect of pregabalin with classification of responders/non-responders, all of which are necessary to adequately assess the efficacy of antiepileptic drugs.
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| 9. |
- Alic, N., et al.
(författare)
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Joint Statistics and MLSD in Filtered Incoherent High-Speed Fiber-Optic Communications
- 2010
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Ingår i: Journal of Lightwave Technology. - 0733-8724 .- 1558-2213. ; 28:10, s. 1564-1572
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, signal statistics and their utilization for detection in narrowly filtered equalized high-speed fiber-optic communications are investigated experimentally. Tradeoffs between log-likelihood metric applications and oversampling are covered in detail. It is, for the first time, demonstrated that performance loss in bandwidth-limited systems can be nearly fully recovered (to within 0.5 dB) by taking advantage of band-width-limitation-induced noise correlations and oversampling.
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| 10. |
- Baverel, Paul G., et al.
(författare)
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Two bootstrapping routines for obtaining imprecision estimates for nonparametric parameter distributions in nonlinear mixed effects models
- 2011
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 38:1, s. 63-82
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Tidskriftsartikel (refereegranskat)abstract
- When parameter estimates are used in predictions or decisions, it is important to consider the magnitude of imprecision associated with the estimation. Such imprecision estimates are, however, presently lacking for nonparametric algorithms intended for nonlinear mixed effects models. The objective of this study was to develop resampling-based methods for estimating imprecision in nonparametric distribution (NPD) estimates obtained in NONMEM. A one-compartment PK model was used to simulate datasets for which the random effect of clearance conformed to a (i) normal (ii) bimodal and (iii) heavy-tailed underlying distributional shapes. Re-estimation was conducted assuming normality under FOCE, and NPDs were estimated sequential to this step. Imprecision in the NPD was then estimated by means of two different resampling procedures. The first (full) method relies on bootstrap sampling from the raw data and a re-estimation of both the preceding parametric (FOCE) and the nonparametric step. The second (simplified) method relies on bootstrap sampling of individual nonparametric probability distributions. Nonparametric 95% confidence intervals (95% CIs) were obtained and mean errors (MEs) of the 95% CI width were computed. Standard errors (SEs) of nonparametric population estimates were obtained using the simplified method and evaluated through 100 stochastic simulations followed by estimations (SSEs). Both methods were successfully implemented to provide imprecision estimates for NPDs. The imprecision estimates adequately reflected the reference imprecision in all distributional cases and regardless of the numbers of individuals in the original data. Relative MEs of the 95% CI width of CL marginal density when original data contained 200 individuals were equal to: (i) -22 and -12%, (ii) -22 and -9%, (iii) -13 and -5% for the full and simplified (n = 100), respectively. SEs derived from the simplified method were consistent with the ones obtained from 100 SSEs. In conclusion, two novel bootstrapping methods intended for nonparametric estimation methods are proposed. In addition of providing information about the precision of nonparametric parameter estimates, they can serve as diagnostic tools for the detection of misspecified parameter distributions.
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| 11. |
- Bergmann, T K, et al.
(författare)
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Impact of CYP2C8*3 on paclitaxel clearance: a population pharmacokinetic and pharmacogenomic study in 93 patients with ovarian cancer
- 2011
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Ingår i: PHARMACOGENOMICS JOURNAL. - : Nature Publishing Group. - 1470-269X .- 1473-1150. ; 11:2, s. 113-120
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Tidskriftsartikel (refereegranskat)abstract
- The primary purpose of this study was to evaluate the effect of CYP2C8*3 and three genetic ABCB1 variants on the elimination of paclitaxel. We studied 93 Caucasian women with ovarian cancer treated with paclitaxel and carboplatin. Using sparse sampling and nonlinear mixed effects modeling, the individual clearance of unbound paclitaxel was estimated from total plasma paclitaxel and Cremophor EL. The geometric mean of clearance was 385 l h(-1) (range 176-726 l h(-1)). Carriers of CYP2C8*3 had 11% lower clearance than non-carriers, P = 0.03. This has not been shown before in similar studies; the explanation is probably the advantage of using both unbound paclitaxel clearance and a population of patients of same gender. No significant association was found for the ABCB1 variants C1236T, G2677T/A and C3435T. Secondarily, other candidate single-nucleotide polymorphisms were explored with possible associations found for CYP2C8*4 (P = 0.04) and ABCC1 g.7356253C andgt; G (P = 0.04).
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| 12. |
- Bergstrand, Martin, 1977-, et al.
(författare)
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A semi-mechanistic modeling strategy for characterization of regional absorption properties and prospective prediction of plasma concentrations following administration of new modified release formulations
- 2012
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Ingår i: Pharmaceutical research. - : Springer Science+Business Media B.V.. - 0724-8741 .- 1573-904X. ; 29:2, s. 574-584
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE To outline and test a new modeling approach for prospective predictions of absorption from newly developed modified release formulations based on in vivo studies of gastro intestinal (GI) transit, drug release and regional absorption for the investigational drug AZD0837. METHODS This work was a natural extension to the companion article "A semi-mechanistic model to link in vitro and in vivo drug release for modified release formulations". The drug release model governed the amount of substance released in distinct GI regions over time. GI distribution of released drug substance, region specific rate and extent of absorption and the influence of food intake were estimated. The model was informed by magnetic marker monitoring data and data from an intubation study with local administration in colon. RESULTS Distinctly different absorption properties were characterized for different GI regions. Bioavailability over the gut-wall was estimated to be high in duodenum (70%) compared to the small intestine (25%). Colon was primarily characterized by a very slow rate of absorption. CONCLUSIONS The established model was largely successful in predicting plasma concentration following administration of three newly developed formulations for which no clinical data had been applied during model building.
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| 13. |
- Bergstrand, Martin, 1977-, et al.
(författare)
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A Semi-mechanistic Modeling Strategy to Link In Vitro and In Vivo Drug Release for Modified Release Formulations
- 2012
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Ingår i: Pharmaceutical research. - : Springer Science and Business Media LLC. - 0724-8741 .- 1573-904X. ; 29:3, s. 695-706
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: To develop a semi-mechanistic model linking in vitro to in vivo drug release. METHODS: A nonlinear mixed-effects model describing the in vitro drug release for 6 hydrophilic matrix based modified release formulations across different experimental conditions (pH, rotation speed and ionic strength) was developed. It was applied to in vivo observations of drug release and tablet gastro intestinal (GI) position assessed with magnetic marker monitoring (MMM). By combining the MMM observations with literature information on pH and ionic strength along the GI tract, the mechanical stress in different parts of the GI tract could be estimated in units equivalent to rotation speed in the in vitro USP 2 apparatus. RESULTS: The mechanical stress in the upper and lower stomach was estimated to 94 and 134 rpm, respectively. For the small intestine and colon the estimates of mechanical stress was 93 and 38 rpm. Predictions of in vivo drug release including between subject/tablet variability was made for other newly developed formulations based on the drug release model and a model describing tablet GI transit. CONCLUSION: The paper outlines a modeling approach for predicting in vivo behavior from standard in vitro experiments and support formulation development and quality control.
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| 14. |
- Bergstrand, Martin, 1977-
(författare)
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Application of Mixed-Effect Modeling to Improve Mechanistic Understanding and Predictability of Oral Absorption
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Several sophisticated techniques to study in vivo GI transit and regional absorption of pharmaceuticals are available and increasingly used. Examples of such methods are Magnetic Marker Monitoring (MMM) and local drug administration with remotely operated capsules. Another approach is the paracetamol and sulfapyridine double marker method which utilizes observed plasma concentrations of the two substances as markers for GI transit. Common for all of these methods is that they generate multiple types of observations e.g. tablet GI position, drug release and plasma concentrations of one or more substances. This thesis is based on the hypothesis that application of mechanistic nonlinear mixed-effect models could facilitate a better understanding of the interrelationship between such variables and result improved predictions of the processes involved in oral absorption. Mechanistic modeling approaches have been developed for application to data from MMM studies, paracetamol and sulfapyridine double marker studies and for linking in vitro and in vivo drug release. Models for integrating information about tablet GI transit, in vivo drug release and drug plasma concentrations measured in MMM studies was outlined and utilized to describe drug release and absorption properties along the GI tract for felodipine and the investigational drug AZD0837. A mechanistic link between in vitro and in vivo drug release was established by estimation of the mechanical stress in different regions of the GI tract in a unit equivalent to rotation speed in the in vitro experimental setup. The effect of atropine and erythromycin on gastric emptying and small intestinal transit was characterized with a semi-mechanistic model applied to double marker studies in fed and fasting dogs. The work with modeling of in vivo drug absorption has highlighted the need for, and led to, further development of mixed-effect modeling methodology with respect to model diagnostics and the handling of censored observations.
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| 15. |
- Bergstrand, Martin, et al.
(författare)
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Characterization of an in vivo concentration-effect relationship for piperaquine in malaria chemoprevention
- 2014
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Ingår i: Science Translational Medicine. - : American Association for the Advancement of Science (AAAS). - 1946-6234 .- 1946-6242. ; 6:260, s. 260ra147-
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Tidskriftsartikel (refereegranskat)abstract
- A randomized, placebo-controlled trial conducted on the northwest border of Thailand compared malaria chemoprevention with monthly or bimonthly standard 3-day treatment regimens of dihydroartemisinin-piperaquine. Healthy adult male subjects (N = 1000) were followed weekly during 9 months of treatment. Using nonlinear mixed-effects modeling, the concentration-effect relationship for the malaria-preventive effect of piperaquine was best characterized with a sigmoidal E-max relationship, where plasma concentrations of 6.7 ng/ml [relative standard error (RSE), 23%] and 20 ng/ml were found to reduce the hazard of acquiring a malaria infection by 50% [that is, median inhibitory concentration (IC50)] and 95% (IC95), respectively. Simulations of monthly dosing, based on the final model and published pharmacokinetic data, suggested that the incidence of malaria infections over 1 year could be reduced by 70% with a recently suggested dosing regimen compared to the current manufacturer's recommendations for small children (8 to 12 kg). This model provides a rational framework for piperaquine dose optimization in different patient groups.
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| 16. |
- 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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| 17. |
- Bizzotto, Roberto, et al.
(författare)
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Multinomial logistic estimation of Markov-chain models for modeling sleep architecture in primary insomnia patients
- 2010
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 37:2, s. 137-155
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Tidskriftsartikel (refereegranskat)abstract
- Hypnotic drug development calls for a better understanding of sleep physiology in order to improve and differentiate novel medicines for the treatment of sleep disorders. On this basis, a proper evaluation of polysomnographic data collected in clinical trials conducted to explore clinical efficacy of novel hypnotic compounds should include the assessment of sleep architecture and its drug-induced changes. This work presents a non-linear mixed-effect Markov-chain model based on multinomial logistic functions which characterize the time course of transition probabilities between sleep stages in insomniac patients treated with placebo. Polysomnography measurements were obtained from patients during one night treatment. A population approach was used to describe the time course of sleep stages (awake stage, stage 1, stage 2, slow-wave sleep and REM sleep) using a Markov-chain model. The relationship between time and individual transition probabilities between sleep stages was modelled through piecewise linear multinomial logistic functions. The identification of the model produced a good adherence of mean post-hoc estimates to the observed transition frequencies. Parameters were generally well estimated in terms of CV, shrinkage and distribution of empirical Bayes estimates around the typical values. The posterior predictive check analysis showed good consistency between model-predicted and observed sleep parameters. In conclusion, the Markov-chain model based on multinomial logistic functions provided an accurate description of the time course of sleep stages together with an assessment of the probabilities of transition between different stages.
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| 18. |
- 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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| 19. |
- Björnsson, Marcus A., et al.
(författare)
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A two-compartment effect site model describes the bispectral index after different rates of propofol infusion
- 2010
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 37:3, s. 243-255
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Tidskriftsartikel (refereegranskat)abstract
- Different estimates of the rate constant for the effect site distribution (k(e0)) of propofol, depending on the rate and duration of administration, have been reported. This analysis aimed at finding a more general pharmacodynamic model that could be used when the rate of administration is changed during the treatment. In a cross-over study, 21 healthy volunteers were randomised to receive a 1 min infusion of 2 mg/kg of propofol at one occasion, and a 1 min infusion of 2 mg/kg of propofol immediately followed by a 29 min infusion of 12 mg kg(-1) h(-1) of propofol at another occasion. Arterial plasma concentrations of propofol were collected up to 4 h after dosing, and BIS was collected before start of infusion and until the subjects were fully awake. The population pharmacokinetic-pharmacodynamic analysis was performed using NONMEM VI. A four-compartment PK model with time-dependent elimination and distribution described the arterial propofol concentrations, and was used as input to the pharmacodynamic model. A standard effect compartment model could not accurately describe the delay in the effects of propofol for both regimens, whereas a two-compartment effect site model significantly improved the predictions. The two-compartment effect site model included a central and a peripheral effect site compartment, possibly representing a distribution within the brain, where the decrease in BIS was linked to the central effect site compartment concentrations through a sigmoidal E-max model.
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| 20. |
- Bogason, Alex, et al.
(författare)
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Inverse relationship between leukaemic cell burden and plasma concentrations of daunorubicin in patients with acute myeloidleukaemia
- 2011
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Ingår i: British Journal of Clinical Pharmacology. - : Wiley. - 0306-5251 .- 1365-2125. ; 71:4, s. 514-521
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Tidskriftsartikel (refereegranskat)abstract
- center dot In vitro studies show that daunorubicin (DNR) cytotoxicity decreases with increasing cell density because of a high cellular uptake and depletion of drug in the medium. center dot It is not known whether such an effect also occurs in vivo. WHAT THIS STUDY ADDS center dot We have shown that a large leukaemic cell burden lowers the plasma concentration of DNR in patients with acute myeloid leukaemia. center dot Our analysis supports that a large leukaemic cell burden increases the central volume of distribution for DNR. center dot Our study indicates that a dose adjustment of DNR may be of importance in acute myeloid leukaemia patients with high white blood cell counts. AIMS It has been shown that the cellular uptake and cytotoxicity of anthracyclines decrease with increasing cell density in vitro, an event termed 'the inocculum effect'. It is not known whether such an effect occurs in vivo. In this study the relationships between white blood cell (WBC) count, plasma and cellular concentrations of daunorubicin (DNR) in patients with acute myeloid leukaemia were investigated. METHODS Plasma and mononuclear blood cells were isolated from peripheral blood from 40 patients with acute myeloid leukaemia at end of infusion (time 1 h), 5 and 24 h following the first DNR infusion. DNR concentrations were determined by high-pressure liquid chromatography and related to the WBC count at diagnosis. A population pharmacokinetic model was used to estimate the correlations between baseline WBC count, volume of distribution and clearance of DNR. RESULTS A clear but weak inverse relationship between the baseline WBC count and plasma concentrations of DNR (r2 = 0.11, P < 0.05) at time 1 was found. Furthermore, a clear relationship between baseline WBC count and DNR central volume of distribution using population pharmacokinetic modelling (dOFV 4.77, P < 0.05) was also noted. Analysis of plasma DNR and the metabolite daunorubicinol (DOL) concentrations in patients with a high WBC count support that the low DNR/DOL concentrations are due a distribution effect. CONCLUSION This study shows that the leukaemic cell burden influences the plasma concentrations of anthracyclines. Further studies are needed to explore if patients with high a WBC count may require higher doses of anthracyclines.
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| 21. |
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| 22. |
- Chigutsa, Emmanuel, et al.
(författare)
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A Time-to-Event Pharmacodynamic Model Describing Treatment Response in Patients with Pulmonary Tuberculosis Using Days to Positivity in Automated Liquid Mycobacterial Culture
- 2013
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Ingår i: Antimicrobial Agents and Chemotherapy. - 0066-4804 .- 1098-6596. ; 57:2, s. 789-795
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Tidskriftsartikel (refereegranskat)abstract
- Days to positivity in automated liquid mycobacterial culture have been shown to correlate with mycobacterial load and have been proposed as a useful biomarker for treatment responses in tuberculosis. However, there is currently no quantitative method or model to analyze the change in days to positivity with time on treatment. The objectives of this study were to describe the decline in numbers of mycobacteria in sputum collected once weekly for 8 weeks from patients on treatment for tuberculosis using days to positivity in liquid culture. One hundred forty-four patients with smear-positive pulmonary tuberculosis were recruited from a tuberculosis clinic in Cape Town, South Africa. A nonlinear mixed-effects repeated-time-to-event modeling approach was used to analyze the time-to-positivity data. A biexponential model described the decline in the estimated number of bacteria in patients' sputum samples, while a logistic model with a lag time described the growth of the bacteria in liquid culture. At baseline, the estimated number of rapidly killed bacteria is typically 41 times higher than that of those that are killed slowly. The time to kill half of the rapidly killed bacteria was about 1.8 days, while it was 39 days for slowly killed bacteria. Patients with lung cavitation had higher bacterial loads than patients without lung cavitation. The model successfully described the increase in days to positivity as treatment progressed, differentiating between bacteria that are killed rapidly and those that are killed slowly. Our model can be used to analyze similar data from studies testing new drug regimens.
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| 23. |
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| 24. |
- Dahl, Svein G., et al.
(författare)
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Incorporating Physiological and Biochemical Mechanisms into Pharmacokinetic-Pharmacodynamic Models : A Conceptual Framework
- 2010
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Ingår i: Basic & Clinical Pharmacology & Toxicology. - : Wiley. - 1742-7835 .- 1742-7843. ; 106:1, s. 2-12
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Forskningsöversikt (refereegranskat)abstract
- The aim of this conceptual framework paper is to contribute to the further development of the modelling of effects of drugs or toxic agents by an approach which is based on the underlying physiology and pathology of the biological processes. In general, modelling of data has the purpose (1) to describe experimental data, (2a) to reduce the amount of data resulting from an experiment, e.g. a clinical trial and (2b) to obtain the most relevant parameters, (3) to test hypotheses and (4) to make predictions within the boundaries of experimental conditions, e.g. range of doses tested (interpolation) and out of the boundaries of the experimental conditions, e.g. to extrapolate from animal data to the situation in man. Describing the drug/xenobiotic-target interaction and the chain of biological events following the interaction is the first step to build a biologically based model. This is an approach to represent the underlying biological mechanisms in qualitative and also quantitative terms thus being inherently connected in many aspects to systems biology. As the systems biology models may contain variables in the order of hundreds connected with differential equations, it is obvious that it is in most cases not possible to assign values to the variables resulting from experimental data. Reduction techniques may be used to create a manageable model which, however, captures the biologically meaningful events in qualitative and quantitative terms. Until now, some success has been obtained by applying empirical pharmacokinetic/pharmacodynamic models which describe direct and indirect relationships between the xenobiotic molecule and the effect, including tolerance. Some of the models may have physiological components built in the structure of the model and use parameter estimates from published data. In recent years, some progress toward semi-mechanistic models has been made, examples being chemotherapy-induced myelosuppression and glucose-endogenous insulin-antidiabetic drug interactions. We see a way forward by employing approaches to bridge the gap between systems biology and physiologically based kinetic and dynamic models. To be useful for decision making, the 'bridging' model should have a well founded mechanistic basis, but being reduced to the extent that its parameters can be deduced from experimental data, however capturing the biological/clinical essential details so that meaningful predictions and extrapolations can be made.
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| 25. |
- Delattre, Maud, et al.
(författare)
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Analysis of exposure-response of CI-945 in patients with epilepsy : application of novel mixed hidden Markov modeling methodology
- 2012
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 39:3, s. 263-271
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Tidskriftsartikel (refereegranskat)abstract
- We propose to describe exposure-response relationship of an antiepileptic agent, using mixed hidden Markov modeling methodology, to reveal additional insights in the mode of the drug action which the novel approach offers. Daily seizure frequency data from six clinical studies including patients who received gabapentin were available for the analysis. In the model, seizure frequencies are governed by underlying unobserved disease activity states. Individual neighbouring states are dependent, like in reality and they exhibit their own dynamics with patients transitioning between low and high disease states, according to a set of transition probabilities. Our methodology enables estimation of unobserved disease dynamics and daily seizure frequencies in all disease states. Additional modes of drug action are achievable: gabapentin may influence both daily seizure frequencies and disease state dynamics. Gabapentin significantly reduced seizure frequencies in both disease activity states; however it did not significatively affect disease dynamics. Mixed hidden Markov modeling is able to mimic dynamics of seizure frequencies very well. It offers novel insights into understanding disease dynamics in epilepsy and gabapentin mode of action.
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