Biomedical subjects

Pascal Girard

Publications and source records attributed to Pascal Girard.

7 recordsLinked to original sources

PubMed2007

Evaluation of uncertainty parameters estimated by different population PK software and methods.

The uncertainty associated with parameter estimations is essential for population model building, evaluation, and simulation. Summarized by the standard error (SE), its estimation is sometimes questionable. Herein, we evaluate SEs provided by different non linear mixed-effect estimation methods associated with their estimation performances. Methods based on maximum likelihood (FO and FOCE in NONMEM, nlme in Splus, and SAEM in MONOLIX) and Bayesian theory (WinBUGS) were evaluated on datasets obtained by simulations of a one-compartment PK model using 9 different designs. Bootstrap techniques were applied to FO, FOCE, and nlme. We compared SE estimations, parameter estimations, convergence, and computation time. Regarding SE estimations, methods provided concordant results for fixed effects. On random effects, SAEM and WinBUGS, tended respectively to under or over-estimate them. With sparse data, FO provided biased estimations of SE and discordant results between bootstrapped and original datasets. Regarding parameter estimations, FO showed a systematic bias on fixed and random effects. WinBUGS provided biased estimations, but only with sparse data. SAEM and WinBUGS converged systematically while FOCE failed in half of the cases. Applying bootstrap with FOCE yielded CPU times too large for routine application and bootstrap with nlme resulted in frequent crashes. In conclusion, FO provided bias on parameter estimations and on SE estimations of random effects. Methods like FOCE provided unbiased results but convergence was the biggest issue. Bootstrap did not improve SEs for FOCE methods, except when confidence interval of random effects is needed. WinBUGS gave consistent results but required long computation times. SAEM was in-between, showing few under-estimated SE but unbiased parameter estimations.

Bayes Theorem↗

PubMed2005

Clinical trial simulation: a tool for understanding study failures and preventing them.

Execution models describe protocol deviations from a specified study design. When a clinical trial is planned, it is generally supposed that it will be executed according to a specific protocol that defines all aspects of the experimental design, from its beginning to its completion. Adherence to the protocol will allow estimation of the treatment outcome (safety and efficacy) with sufficient statistical power, or at least that is what is assumed. In reality, however, deviations from the protocol may lead to failure of the study to achieve its stated aims. In anticipation of protocol deviations that contribute to inflated residual variability and decreased study statistical power, trial designers tend to overpower studies in a rather arbitrary way. It is difficult to estimate quantitatively the consequences of one protocol deviation on statistical study power and, a fortiori, it is almost impossible to do it for a combination of protocol deviations. One way to study the consequences of model deviations is by using modelling and simulation techniques, and more specifically longitudinal stochastic models that can describe individual behaviours. Thus, execution models are powerful tools for identifying weaknesses or limitations in a proposed study design, which may be anticipated, avoided or resolved in order to increase robustness of the study design prior to implementation of the actual clinical study. As such, they are an integral component of clinical trial simulation and an essential tool in clinical trial design.

Acquired Immunodeficiency Syndrome↗

PubMed2002

Clinical trial simulation using therapeutic effect modeling: application to ivabradine efficacy in patients with angina pectoris.

Ivabradine is a new bradycardic agent with a potential indication for stable angina pectoris. To investigate the best compromise between efficacy, safety, drug regimen, and number of patients to include in a phase III study, we conducted Monte Carlo simulations using a full therapeutic model. The binary clinical outcome, chest pain, was simulated using a physiologic model in which the coronary reserve was derived from the heart rate. Safety was defined as being heart rate dependent. Using real data to build a pharmacokinetic-pharmacodynamic model controlling drug effect (i.e., heart rate decrease), and resampling heart rate profiles from the database, 100 clinical trials (N = 200) were simulated for five oral doses (2.5, 5, 10, 20, and 40 mg QD or BID) of ivabradine. Only 25% of the simulated trials showed a significant effect of ivabradine with doses up to 10 mg QD, and 48 and 55% of the trials with doses of 10 mg BID and 20 mg QD, respectively, and more than 80% of the trials with a 40 mg daily dose. For safety, 4% of patients had at least one adverse event in the untreated group, and from 5 to 13% in the treated groups for the lowest to the highest dose, respectively. The number of subjects to include in a future trial to obtain a 15% decrease in chest pain under the assumption of a 68% base risk, is 239 subjects per group with 10 mg BID or 196 with 20 mg QD. These results illustrate how clinical trial simulations including a PK/PD model as well as a physiopathologic mechanistic model, describing the relationship between the intermediate and clinical endpoint, and the resampling of real patients from a large database can help in designing future phase III trials.

Angina Pectoris↗

PubMed2002

Bioequivalence evaluation of a fixed combination of chloroquine and proguanil in a capsule formulation versus a standard medication.

To assess the bioequivalence between a test capsule with a fixed combination of chloroquine (CAS 54-05-7) and proguanil (CAS 500-92-5), and chloroquine and proguanil administered as separate tablets, an open two-sequence, two-period cross-over randomized study was performed in twelve healthy volunteers who received a single oral dose of 100 mg chloroquine and 200 mg proguanil either in the form of one capsule or the reference tablets. Biological samples (plasma, whole blood and erythrocytes) were collected up to 43 days after drug administration. The parent drugs and their main metabolites were analyzed using high performance liquid chromatography assay. Bioequivalence was assessed for whole blood and plasma AUC and Cmax of chloroquine, proguanil, cycloguanil and 4-chlorophenylbiguanide. Bioequivalence in erythrocytes was also established except for Cmax of chloroquine. While the differences for Cmax of chloroquine in erythrocytes may be related to technical problems during the erythrocyte sampling procedure (contamination with leukocytes), bioequivalence can be concluded from the plasma concentration data. Therefore, the use of a single capsule instead of one chloroquine tablet and two proguanil tablets daily can be proposed in order to increase the prophylactic compliance without decreasing the prophylactic efficacy.

Adult↗

PubMed2002

Shape discrimination deficits during reversible deactivation of area V4 in the macaque monkey.

The role of area V4 in the primate extrastriate cortex has received much attention in recent years. However, the deficit specificity following area V4 ablations has been difficult to determine due to the ablations including area V4 and additional adjacent areas, deficit attenuation and the numerous variations in the results of different research teams. In order to address these issues, we examined the role of area V4 during reversible deactivation of the lower visual field representation within this area while macaque monkeys performed simple pattern discriminations and their eye position was monitored. Specifically, the monkeys were trained to perform a match-to-sample task with the sample stimulus placed within or outside the visual field quadrant represented within the deactivated region of area V4. The sample and match stimuli had the same salience (same size or luminance). Using this approach, we identified significant simple shape discrimination deficits during deactivation of area V4 that did not attenuate with time. Deficits were also identified when the discriminanda were the same figure viewed at different orientations (rotated shapes). In contrast, no deficits were identified during simple hue discriminations. Furthermore, no saccadic eye movement deficits were identified during deactivation of area V4. Therefore, we conclude that deactivation of area V4 yields specific deficits on simple and rotated shape discriminations. These results show that area V4 is an important step in shape and form processing along the ventral visual stream leading to the inferotemporal cortex.

Animals↗

PubMed2002

Physiologically based model of acute ischemic stroke.

In the treatment of acute ischemic stroke most of the clinical trials have failed, contrasting with promising results in the preclinical stages. This continuing discrepancy suggests some misconceptions in the understanding of acute ischemic stroke. One possible method for identifying the shortcomings of present-day approaches is to integrate all the available knowledge into a single mathematical model and to subject that model to challenges via simulations with available experimental data. As a first stage, then, the authors developed a simplified model, defining the structure and the different parameters that represent the phenomena that occur during the hyperacute phase of ischemic stroke. First, the different critical points of the evolution of ischemic stroke, based on the available evidence on the pathophysiology of stroke, were identified. Those key steps were then related to the quantitative data obtained by magnetic resonance imaging and positron emission tomography scan. These two techniques allow the measurement of diverse key markers of cerebral metabolism: cerebral blood flow (CBF), oxygen extraction factor, cerebral metabolism rate of oxygen, and the apparent diffusion coefficient of water, among others. Those markers were organized together through mathematical equations, and changed over time in order to describe the evolution of an acute ischemic stroke. At each time during the evolution of stroke those parameters are summarized in a parameter called survival delay. This parameter made possible the definition of three different states for tissues-functional, infarcted, salvageable-as end point. Once the model was designed, simulations were performed to explore its internal validity. Simulation results were consistent with the reality of acute ischemic stroke and did not reveal any major drawbacks in the use of the model. The more rapid the decrease in CBF, the larger is the final infarcted area. The model also allowed for the characterization of two types of tissue in the penumbra: tissues with an initial metabolic impairment and tissues altered owing to the closeness of the ischemic area. The results of this experiment were consistent with what is known of acute ischemic stroke. The model integrated different markers of acute ischemic stroke into a single entity in order to mimic acute ischemic stroke, and has been shown to have a reasonable degree of internal validity.

Animals↗

PubMedDate not supplied

Clinical trial simulation in drug development.

The simulation of therapeutic models and clinical trial simulation have recently attracted attention as emerging techniques for developing new active molecules and the exploration of possible clinical trial results. Such approaches have benefited from fundamental progress in the development of 'in silico' models, as well as progress in nonlinear mixed-effect pharmacokinetic-pharmacodynamic models. Mixing the two approaches allows simulation of 'virtual' patients, who receive virtual treatments or placebo. These have various uses, such as proof of concept, decision analysis or experimental design optimisation. Also, the effect of departures from protocol on clinical trial results can easily be evaluated by the use of simulation. This technique is now implemented by the pharmaceutical industry for optimising phase II and III experimental designs when a good biomarker or a clinical outcome model is available, but the use of an in silico therapeutic model as a proof of concept is only just beginning. In order to see such methodologies used more widely in drug development, multidisciplinary efforts need to be initiated, new modelling and simulation tools developed, and sound modelling and simulation practice documents need to be adopted. A reduction in the number of failed clinical development projects, the number of negative phase II and III clinical trials, or in just their cost and duration, are among the expected benefits of modelling and simulation in clinical drug development.

Clinical Trials as Topic↗