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At least 19 recordsLinked to original sources
PubMed2005

Impact of pharmacometrics on drug approval and labeling decisions: a survey of 42 new drug applications.

The value of quantitative thinking in drug development and regulatory review is increasingly being appreciated. Modeling and simulation of data pertaining to pharmacokinetic, pharmacodynamic, and disease progression is often referred to as the pharmacometrics analyses. The objective of the current report is to assess the role of pharmacometrics at the US Food and Drug Administration (FDA) in making drug approval and labeling decisions. The New Drug Applications (NDAs) submitted between 2000 and 2004 to the Cardio-renal, Oncology, and Neuropharmacology drug products divisions were surveyed. For those NDA reviews that included a pharmacometrics consultation, the clinical pharmacology scientists ranked the impact on the regulatory decision(s). Of about a total of 244 NDAs, 42 included a pharmacometrics component. Review of NDAs involved independent, quantitative evaluation by FDA pharmacometricians, even when such analysis was not conducted by the sponsor. Pharmacometric analyses were pivotal in regulatory decision making in more than half of the 42 NDAs. Of the 14 reviews that were pivotal to approval related decisions, 5 identified the need for additional trials, whereas 6 reduced the burden of conducting additional trials. Collaboration among the FDA clinical pharmacology, medical, and statistical reviewers and effective communication with the sponsors was critical for the impact to occur. The survey and the case studies emphasize the need for early interaction between the FDA and sponsors to plan the development more efficiently by appreciating the regulatory expectations better.

Data Collection↗
PubMedDate not supplied

Pharmacometrics: modelling and simulation tools to improve decision making in clinical drug development.

There is broad recognition within the pharmaceutical industry that the drug development process, especially the clinical part of it, needs considerable improvement to cope with rapid changes in research and health care environments. Modelling and simulation are mathematically founded techniques that have been used extensively and for a long time in other areas than the pharmaceutical industry (e.g. automobile, aerospace) to design and develop products more efficiently. Both modelling and simulation rely on the use of (mathematical and statistical) models which are essentially simplified descriptions of complex systems under investigation. It has been proposed to integrate pharmacokinetic (PK) and pharmacodynamic (PD) principles into drug development to make it more rational and efficient. There is evidence from a survey on 18 development projects that a PK/PD guided approach can contribute to streamline the drug development process. This approach extensively relies on PK/PD models describing the relationships among dose, concentration (and more generally exposure), and responses such as surrogate markers, efficacy measures, adverse events. Well documented empirical and physiologically based PK/PD models are becoming available more and more, and there are ongoing efforts to integrate models for disease progression and patient behavior (e.g. compliance) as well. Other types of models which are becoming increasingly important are population PK/PD models which, in addition to the characterization of PK and PD, involve relationships between covariates (i.e. patient characteristics such as age, body weight) and PK/PD parameters. Population models allow to assess and to quantify potential sources of variability in exposure and response in the target population, even under sparse sampling conditions. As will be shown for an anticancer agent, implications of significant covariate effects can be evaluated by computer simulations using the population PK/PD model. Stochastic simulation is widely used as a tool for evaluation of statistical methodology including for example the evaluation of performance of measures for bioequivalence assessment. Recently, it was suggested to expand the use of simulations in support of clinical drug development for predicting outcomes of planned trials. The methodological basis for this approach is provided by (population) PK/PD models together with random sampling techniques. Models for disease progression and behavioral features like compliance, drop-out rates, adverse event dependent dose reductions, etc. have to be added to population PK/PD models in order to mimic the real situation. It will be shown that computer simulation helps to evaluate consequences of design features on safety and efficacy assessment of the drug, enabling identification of statistically valid and practically realisable study designs. For both modelling and simulation a guidance on 'best practices' is currently worked out by a panel of experts comprising representatives from academia, regulatory bodies and industry, thereby providing a necessary condition that model-based analysis and simulation will further contribute to streamlining pharmaceutical drug development processes.

Clinical Trials as Topic↗
PubMedDate not supplied

Pharmacometric analysis of alpha1-adrenoceptor function in rat tail artery pretreated with lipopolysaccharides.

The inhibitory effect of lipopolysaccharides (LPS) on contraction evoked by alpha-adrenergic stimulation is quite well-known, but molecular mechanism of this inhibition is unclear. In the present study, an interaction between alpha-adrenoceptor response and LPS in rat tail artery was investigated using chemical stimulation. In the presence of LPS noradrenaline and phenylephrine, concentration-response curves were shifted to the right with a change in maximal responses. The K(A) and K(B) values calculated in the presence and absence of LPS did not differ significantly. The results strongly suggest that LPS did not change the affinity of alpha-adrenoceptors. Changes in the plot showing relationship between agonist-evoked responses and receptor occupancy in the presence of LPS and reduction of K(A)/ED50 value suggest reduction of alpha-adrenoceptor reserve. In the experiments performed on arteries without endothelium, the inhibitory effect of LPS was still present. In the presence of atropine, antazoline and indomethacin, the reduction of alpha-adrenoceptor reserve was noted, but in the presence of N-omega-nitro-L-arginine methyl ester (L-NAME), the inhibitory effect of LPS was not significant. Moreover, in LPS-pretreated arteries, in the presence of L-NAME, the increase in the receptor reserve was observed. It suggests that inhibitory effect of LPS is partially reversible. The results strongly indicate that in early endotoxemia, main inhibitory effect of LPS is connected with releasing nitric oxide and decreasing coupling between alpha1-adrenoceptor and signal induction.

Adrenergic alpha-Agonists↗
PubMedDate not supplied

Physiological antagonism of angiotensin II and lipopolysaccharides in early endotoxemia: pharmacometric analysis.

The inhibitory effect of lipopolysaccharides (LPS) on alpha-adrenergic contraction is quite well known, but molecular mechanism of this inhibition is unclear. In the present study, the interaction between alpha-adrenoceptor and vasopressin receptor response, and LPS in rat tail artery was investigated using chemical stimulation. In the presence of LPS, noradrenaline, phenylephrine and arginine-vasopressin, concentration-response curves (CRCs) were shifted to the right with the change in maximal responses. The K(A) and K(B) values calculated in the presence and absence of LPS did not differ significantly. The results strongly suggest that LPS did not change the receptors affinity. The changes in the relationship between receptor occupancy and response to an agonist in the presence of LPS and reduction of K(A)/ED(50) value suggest reduction of receptor reserve. In the presence of angiotensin II (Ang II), CRCs were shifted to the right with significant increase in receptor reserve. Moreover, this effect was still present in LPS-pretreated arteries. The receptor reserve reduced by LPS significantly increased in the presence of Ang II. It suggests that inhibitory effect of LPS is partially reversible. The results strongly suggest that in early endotoxemia, inhibitory effect of LPS may by partially reverted by an increase in activity of renin-angiotensin-aldosterone system.

Angiotensin II↗
PubMedDate not supplied

Pharmacometric analysis of the effect of furosemide on suramin pharmacokinetics.

STUDY OBJECTIVE: To characterize the effects of furosemide on the pharmacokinetics of suramin, a renally eliminated investigational antineoplastic agent. DESIGN: Retrospective population pharmacokinetic analysis. SETTING: Government biomedical research facility. PATIENTS: Twenty-six men with hormone-refractory prostate cancer and one with adrenocortical carcinoma. INTERVENTIONS: Patients received suramin by continuous or intermittent infusion with and without concomitant furosemide. MEASUREMENTS AND MAIN RESULTS: Optimum suramin regimens were achieved by adaptive feedback control, and pharmacokinetic data were collected both in the presence and absence of furosemide. Suramin concentrations were determined by high-performance liquid chromatography (coefficient of variation < 8%). Suramin concentrations were fit to a three-compartment linear model with six coefficients and two rate inputs, which allowed furosemide to affect suramin pharmacokinetics. Individual and population parameter estimates were determined using the iterative two-stage approach. Concomitant furosemide was associated with a median decrease in total body clearance of suramin by 36% (range 0-63%, p < 0.0001). No other parameter was significantly altered, and there was no trend for change in any pharmacokinetic value with time. Suramin plasma concentrations were simulated with and without prolonged furosemide therapy in 26 patients for 12 weeks. The average suramin concentration increased by greater than 33% in 12 patients; 2 patients had a greater than 67% increase in this extreme case model. CONCLUSION: Coadministration of furosemide with suramin can cause an increase in suramin concentrations; however, due to suramin's long half-life, its rate of accumulation is very slow. Nonetheless, in individuals receiving suramin by nonadaptive control, appropriate precautions should be taken when prolonged furosemide therapy is begun.

Adrenal Cortex Neoplasms↗
PubMed2005

PsN-Toolkit--a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM.

PsN-Toolkit is a collection of statistical tools for pharmacometric data analysis using the non-linear mixed effect modeling software NONMEM. The toolkit is object oriented and written in the programming language Perl using the programming library Perl-speaks-NONMEM (PsN). Five methods: the Bootstrap, the Jackknife, Log-likelihood Profiling, Case-deletion Diagnostics and Stepwise Covariate Model building are included as separate classes and may be used in user-written Perl scripts or through stand-alone command line applications. The tools are designed with the ability to cooperate and with an emphasis on common structures for workflow and result handling. Parallel execution of independent tool sections is supported on shared memory multiprocessor (SMP) computers, Mosix/openMosix clusters and distributed computing environments following the NorduGrid standard. In conclusion, PsN-Toolkit makes it easier to use the Bootstrap, the Jackknife, Log-likelihood Profiling, Case-deletion Diagnostics and Stepwise Covariate Model building in pharmacometric data analysis.

Cluster Analysis↗
PubMed2006

Model-based drug development: the road to quantitative pharmacology.

High development costs and low success rates in bringing new medicines to the market demand more efficient and effective approaches. Identified by the FDA as a valuable prognostic tool for fulfilling such a demand, model-based drug development is a mathematical and statistical approach that constructs, validates, and utilizes disease models, drug exposure-response models, and pharmacometric models to facilitate drug development. Quantitative pharmacology is a discipline that learns and confirms the key characteristics of new molecular entities in a quantitative manner, with goal of providing explicit, reproducible, and predictive evidence for optimizing drug development plans and enabling critical decision making. Model-based drug development serves as an integral part of quantitative pharmacology. This work reviews the general concept, basic elements, and evolving role of model-based drug development in quantitative pharmacology. Two case studies are presented to illustrate how the model-based drug development approach can facilitate knowledge management and decision making during drug development. The case studies also highlight the organizational learning that comes through implementation of quantitative pharmacology as a discipline. Finally, the prospects of quantitative pharmacology as an emerging discipline are discussed. Advances in this discipline will require continued collaboration between academia, industry and regulatory agencies.

Adult↗
PubMed2006

Mixture models and subpopulation classification: a pharmacokinetic simulation study and application to metoprolol CYP2D6 phenotype.

Mixture models are applied in population pharmacometrics to characterize underlying population distributions that are not adequately approximated by a single normal or lognormal distribution. In addition to obtaining individualized maximum a posteriori Bayesian post hoc parameter estimates, the subpopulation to which an individual was classified can be determined. However, the accuracy of the classification of subjects to subpopulations is not well studied. We investigated the impact of several factors on the accuracy of classification in mixture models applied to pharmacokinetics using a simulation strategy. The availability of actual subject data allowed us to evaluate mixture model classification in a potentially common application, namely, the classification of clearance into poor metabolizer (PM) or extensive metabolizer (EM) subgroups with the known phenotype status in subjects receiving metoprolol. The factors explored in the simulation study were the magnitude of difference between the clearances in two subpopulations, the between subject variability in clearance, the mixing-fraction, and the population sample size. Populations were simulated at various levels of the above factors and analyzed with a mixture model using NONMEM. The population pharmacokinetics of metoprolol were modeled with the EM/PM phenotype as a known covariate, and without the phenotype covariate using a mixture model. Within the range of scenarios studied, the proportion of subjects classified into the correct subpopulation was high. The simulation-estimation study suggests that a greater separation between two subpopulations, a smaller variability in the parameter distribution, a larger sample size, and a smaller size subpopulation tend to be associated with a greater accuracy of subpopulation classification when a mixture model is applied to pharmacokinetic data. In a population pharmacokinetic analysis of metoprolol, a drug that undergoes polymorphic metabolism, it was possible to correctly identify phenotype status using a mixture model.

Administration, Oral↗
PubMed1998

Pharmacodynamics of variable patient compliance: implications for pharmaceutical value.

Pharmaceutical value, a multidimensional factor that includes proven efficacy, is now crucial to market success. A key parameter of value is reliability in use, determined by the several sources of variance in drug response, e.g. the Harter-Peck model, based on linear pharmacometrics of theophylline, whose dose-response has an estimated 80% coefficient of variation, due mainly to variable pharmacokinetics and non-compliance. The main forms of non-compliance are multiday intervals between doses, the impact of which is difficult to assess because too little is known of the time-course of drug actions after dosing stops ('off-responses'). Omeprazole, the best-selling drug, is an exception, and its off-response data reveal markedly non-linear pharmacodynamics that appear to filter most of the variance that a linear model passes, projecting a big gain in reliability. The impact of variable compliance is attenuated by 'forgiveness', the post-dose duration of effective action (4-5 days for omeprazole) minus its recommended dosing interval.

Journal Article↗
PubMed1993

The role of receptor binding in drug discovery.

Radioligand receptor binding has been used extensively to identify and characterize a host of receptors and enzymes targeting virtually every therapeutic area. Many drug discovery programs have been based on the utilization of radioligand receptor binding technology to identify lead compounds which interact with receptors likely to be important in neuronal, immunological, gastrointestinal, and cardiovascular function/dysfunction. There are several obvious advantages to using in vitro receptor binding as a first level screen when compared to in vivo pharmacometric screens. Scientifically, the structure activity data generated in binding assays is a direct reflection of the ligand/receptor interaction minus the complications which result from secondary events, bioavailability, and pharmacodynamic issues. Technically, the binding studies require only a small amount of test compound (< or = 1 mg), while whole animal studies routinely need gram quantities. Similarly, only a small amount of tissue is required, compared with the cost of purchase and maintenance of live animals for in vivo screening. Supply and labor costs are drastically reduced due to the limited volume and test tube based technology of receptor binding. For these reasons receptor binding assays have been utilized with considerable success to discover site specific lead compounds in virtually every therapeutic area.

Animals↗
PubMed1976

Neuromuscular sensitivity to tubocurarine. A comparison of 10 parameters.

The pharmacometrics of neuromuscular block by tubocurarine was studied. Ten parameters were compared for the sensitivity, the scatter and the linearity of response at three levels of block in 11 cats. The fourth twitch of the train-of-four is the most sensitive parameter, followed in order of decreasing sensitivity by the train-of-four fade, the faded tetanus, the tetanus, the single twitch, the post-tetanic twitch and the tetanic fade. At the level of 50% block of the single twitch, all other parameters differ significantly (P less than 0.05) from the single twitch in sensitivity. With the exception of the tetanic fade, all parameters examined correlate with the single twitch (r xy = 0.42-0.77). This permits limited translation of results among various parameters. In cats the scatter of results is least for the most sensitive parameter, and vice versa. We conclude that the train-of-four is the most sensitive parameter, and that the single twitch is valid for an over-all estimation of the neuromuscular block induced by tubocurarine.

Animals↗
PubMed1993

Multiple dose pharmacokinetics and concentration effect relationship of the orally active renin inhibitor remikiren (Ro 42-5892) in hypertensive patients.

1 Three double-blind, randomized, placebo controlled, multiple oral dose studies in patients with mild to moderate hypertension were performed to study tolerability, pharmacodynamics and pharmacokinetics of remikiren. Doses of 100-800 mg remikiren or placebo were given over 8 days to altogether 144 patient volunteers. In some cases (n = 46) single i.v. doses of 100 mg were administered 4 h after the last oral dose. Plasma remikiren concentrations, plasma renin activity and immunoreactive renin concentrations were measured. Pharmacokinetic parameters were estimated using model independent techniques and the concentration-effect relationship was evaluated using population pharmacometric methods. 2 In most patients no distinct absorption and disposition phase could be identified, since plasma concentrations fluctuated widely over a period of approximately 10 h. Peak plasma concentrations (Cmax) were achieved within 0.25-2 h postdose. Mean Cmax values (on the first and last day of oral treatment) were in the magnitude of 4-6 ng ml(-1) (200 mg), 23-27 ng ml(-1) (300 mg), 65-83 ng ml(-1) (600 mg) and 47-48 ng ml(-1) (800 mg). Cmax and AUC0-t values were clearly different for different doses within single studies. Intersubject variability in pharmacokinetic parameters was much higher than intrasubject variability. No drug accumulation in plasma was apparent. 3 Inhibition of the angiotensin I production rate correlated well with plasma drug concentrations according to the Emax-model. An IC50 value of 0.5 ng ml(-1) (0.8 nM) was estimated. No correlation between blood pressure changes on the last day of oral treatment and either plasma remikiren concentrations or plasma renin inhibition was found.

Administration, Oral↗
PubMed2004

Quality assurance program for clinical measurement of antiretrovirals: AIDS clinical trials group proficiency testing program for pediatric and adult pharmacology laboratories.

Clinical trials designed to compare antiretroviral regimens, investigate therapeutic drug monitoring, or measure pharmacometrics often include protease inhibitors (PIs), nonnucleoside reverse transcriptase inhibitors (NNRTIs), and nucleoside reverse transcriptase inhibitors, requiring the measurement of these antiretrovirals in plasma. Within the adult and pediatric AIDS Clinical Trials Group (ACTG), a network of Pharmacology Support Laboratories (PSLs) is a component of the group laboratory infrastructure and conducts these types of pharmacologic assays. The adult ACTG has developed a comprehensive quality assurance program for the conduct of clinical pharmacology protocols, one component of which is the antiretroviral proficiency testing (PT) program that has been implemented between the adult and pediatric pharmacology laboratories of the ACTG. PT testing samples were prepared and distributed in July 2001, February 2002, and July 2002. High, medium, and low concentrations of PIs (indinavir, saquinavir, amprenavir, lopinavir, ritonavir, and nelfinavir) and NNRTIs (nevirapine and efavirenz) were added to drug-free EDTA plasma and distributed, on dry ice, to eight ACTG PSLs. One testing laboratory used liquid chromatography-tandem mass spectrometry, and seven used high-performance liquid chromatography-UV analysis. A result was considered acceptable if it was within 20% deviation of the assigned concentration. For all concentrations of PIs evaluated, 96% of samples tested (430 of 448 measurements) met the acceptance criteria. For both NNRTIs, 100% of samples tested (140 of 140 measurements) met the acceptance criteria. In conclusion, the PT program results presented demonstrate excellent interlaboratory agreement for all antiretrovirals tested and provide support for the merger of plasma concentration data among laboratories for large clinical trials.

Acquired Immunodeficiency Syndrome↗
PubMed2005

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.

Animals↗
PubMed2005

It's time.

Statistical inference involves taking the results of models and knowledge about probability to make decisions about the relationship in question. This commentary explains the usefulness of statistical inference to the drug development process, as well as some common pitfalls. It also examines reasons why statistical inference does not seem to be fully integrated into pharmacometric modeling. An example is shown that demonstrates the inferential advantages of mechanistic models. Both statisticians and pharmacometricians ought to take note of these advantages and integrate their efforts in order to maximize the decision-making potential of clinical research.

Analysis of Variance↗
PubMed1999

Population pharmacokinetics. A regulatory perspective.

The application of population approaches to drug development is recommended in several US Food and Drug Administration (FDA) guidance documents. Population pharmacokinetic (and pharmacodynamic) techniques enable identification of the sources of inter- and intra-individual variability that impinge upon drug safety and efficacy. This article briefly discusses the 2-stage approach to the estimation of population pharmacokinetic parameters, which requires serial multiple measurements on each participant, and comprehensively reviews the nonlinear mixed-effects modelling approach, which can be applied in situations where extensive sampling is not done on all or any of the participants. Certain preliminary information, such as the compartment model used in describing the pharmacokinetics of the drug, is required for a population pharmacokinetic study. The practical design considerations of the location of sampling times, number of samples/participants and the need to sample an individual more than once should be borne in mind. Simulation may be useful for choosing the study design that will best meet study objectives. The objectives of the population pharmacokinetic study can be secondary to the objectives of the primary clinical study (in which case an add-on population pharmacokinetic protocol may be needed) or primary (when a stand-alone protocol is required). Having protocols for population pharmacokinetic studies is an integral part of 'good pharmacometric practice'. Real-time data assembly and analysis permit an ongoing evaluation of site compliance with the study protocol and provide the opportunity to correct violations of study procedures. Adequate policies and procedures should be in place for study blind maintenance. Real-time data assembly creates the opportunity for detecting and correcting errors in concentration-time data, drug administration history and covariate data. Population pharmacokinetic analyses may be undertaken in 3 interwoven steps: exploratory data analysis, model development and model validation (i.e. predictive performance). Documentation for regulatory purposes should include a complete inventory of key runs in the analyses undertaken (with flow diagrams if possible), accompanied by articulation of objectives, assumptions and hypotheses. Use of diagnostic analyses of goodness of fit as evidence of reliability of results is advised. Finally, the use of stability testing or model validation may be warranted to support label claims. The opinions expressed in this article were revised by incorporating comments from various sources and published by the FDA as 'Guidance for Industry: Population Pharmacokinetics' (see the FDA home page http:/(/)www.fda.gov for further information).

Data Interpretation, Statistical↗
PubMed1987

Pharmacologic role of rubidium in psychiatric research.

Rubidium appears to exert several biologic and pharmacologic effects that are similar if not identical to those of many of the classic antidepressant drugs. This mineral element, if given orally as rubidium chloride, appears to be nontoxic and therapeutically effective in several types of depressive disorders. Currently, however, it is unclear whether or not rubidium will serve as an invaluable pharmacologic agent of a direct clinical nature. Further pharmacometric studies and clinical evaluations are needed to elucidate its mechanism of action and to ascertain its future therapeutic role as an antidepressant drug in clinical psychiatry.

Antidepressive Agents↗