A review of synergy concepts of nonlinear blending and dose-reduction profiles

John Peterson

Published in Frontiers of Bioscience, 2010, S2, 483–503

Abstract: This article presents a case-study review of synergy concepts of nonlinear blending and dose-reduction profiles. “Strong nonlinear blending” is a novel concept that provides a flexible paradigm for the assessment of combination drug synergy that is applicable to any shaped combination-drug dose-response surface; issues of varying relative potency, partial inhibitors, potentiation, or coalism pose no problems at all. Dose-reduction profiles are overlay plots created to show how much each drug can be reduced in amount and yet achieve the same efficacy as larger amounts of each drug used individually. This review applies these synergy concepts to two data sets from a previously published experiment. The previous publication had claimed a high degree of Loewe synergy for one of the data sets. However, a more penetrating analysis shows that with regard to strong nonlinear blending there is no reason to blend (for purposes of response enhancement) the two compounds studied. However, the dose-reduction profile plots show how Loewe synergy is present and provide further insight to the interaction of the two compounds (on the dose-concentration scale).

Effects of unstratified and centre-stratified randomization in multi-centre clinical trials

Vladimir Anisimov

Published in Pharmaceutical Statistics, 2010 (early view)

Abstract: This paper deals with the analysis of randomization effects in multi-centre clinical trials. The two randomization schemes most often used in clinical trials are considered: unstratified and centre-stratified block-permuted randomization. The prediction of the number of patients randomized to different treatment arms in different regions during the recruitment period accounting for the stochastic nature of the recruitment and effects of multiple centres is investigated.

A new analytic approach using a Poisson-gamma patient recruitment model (patients arrive at different centres according to Poisson processes with rates sampled from a gamma distributed population) and its further extensions is proposed. Closed-form expressions for corresponding distributions of the predicted number of the patients randomized in different regions are derived. In the case of two treatments, the properties of the total imbalance in the number of patients on treatment arms caused by using centre-stratified randomization are investigated and for a large number of centres a normal approximation of imbalance is proved. The impact of imbalance on the power of the study is considered. It is shown that the loss of statistical power is practically negligible and can be compensated by a minor increase in sample size. The influence of patient dropout is also investigated. The impact of randomization on predicted drug supply overage is discussed.

Incomplete and Enriched Data Analysis and Sensitivity Analysis

Geert Molenberghs (Discussant: James Roger)

Presented at DIA Statistics SIAC, VJC, January 13, 2010

Spatiotemporal regulation of the cough motor pattern 

Cheng Wang, Sourish Saha, Melanie Rose, Paul Davenport and Donald Bolser

Published in Cough, 2009, 5-12

Abstract: The purpose of this study was to identify the spatiotemporal determinants of the cough motor pattern. We speculated that the spatial and temporal characteristics of the cough motor pattern would be regulated separately. Electromyograms (EMG) of abdominal muscles (ABD, rectus abdominis or transversus abdominis), and parasternal muscles (PS) were recorded in anesthetized cats. Repetitive coughing was produced by mechanical stimulation of the lumen of the intrathoracic trachea. Cough inspiratory (CTI) and expiratory (CTE) durations were obtained from the PS EMG. The ABD EMG burst was confined to the early part of CTE and was followed by a quiescent period of varying duration. As such, CTE was divided into two segments with CTE1 defined as the duration of the ABD EMG burst and CTE2 defined as the period of little or no EMG activity in the ABD EMG. Total cough cycle duration (CTTOT) was strongly correlated with CTE2 (r2>0.8), weakly correlated with CTI (r2<0.3), and not correlated with CTE1 (r2<0.2). There was no significant relationship between CTI and CTE1 or CTE2. The magnitudes of inspiratory and expiratory motor drive during cough were only weakly correlated with each other (r2<0.36) and were not correlated with the duration of any phase of cough. The results support: a) separate regulation of CTI and CTE, b) two distinct subphases of CTE (CTE1 and CTE2), c) the duration of CTE2 is a primary determinant of CTTOT, and d) separate regulation of the magnitude and temporal features of the cough motor pattern.

Comparison of Designs for Response Surface Models with Random Block Effects

Sourish Saha and André Khuri

Published in Journal of Quality Technology and Quantitative Management, 2009, 6 (3), 219–234

Abstract: The purpose of this article is to compare designs for response surface models with a random block effect. To assess the quality of prediction associated with a given design, the scaled prediction variance is considered as a design criterion. The proposed approach is based on using quantiles of this design criterion on concentric surfaces within the experimental region. The dependence of these quantiles on the unknown value of the ratio of two variance components, namely, the ones for the block effect and the experimental error, is depicted by plotting the so-called quantile dispersion graphs (QDGs). These plots provide a clear assessment of the quality of prediction associated with a given design. A numerical example is presented to illustrate the proposed methodology.

A Bayesian Design Space Approach To Robustness and System Suitability for Pharmaceutical Assays and Other Processes

John Peterson and Mohammad Yahyah

Published in Statistics in Biopharmaceutical Research, 2009, 1 (4), 441–449

Abstract: The ICH Q2 (R1) Guidance on Validation of Analytical Procedures states that a robustness assessment for an analytical method should provide “an indication of its reliability during normal usage.” The concept of “design space” as specified in the ICH Q8 Guidance may be used to create a zone of reliable robustness for an analytical method or pharmaceutical process. A Bayesian approach to design space as outlined by Peterson (2004) accounts for model parameter uncertainty, correlation among the quality responses at each fixed operating condition, and method response multiplicity. Two examples are provided to illustrate the application of a Bayesian design space to assessing reliability/robustness. One example is about assessing the ability of an HPLC analytical method to meet system suitability criteria and the other deals with a crystallization process for an active pharmaceutical ingredient.

A Bayesian Reliability Approach to Multiple Response Optimization with Seemingly Unrelated Regression Models

John Peterson, Guillermo Miró-Quesada and Enrique del Castillo

Published in Journal of Quality Technology and Quantitative Management, 2009, 6 (4), 353–369

Abstract: This paper presents a Bayesian predictive approach to multiresponse optimization experiments. It generalizes the work of Peterson [33] in two ways that make it more flexible for use in applications. First, a multivariate posterior predictive distribution of seemingly unrelated regression models is used to determine optimum factor levels by assessing the reliability of a desired multivariate response. It is shown that it is possible for optimal mean response surfaces to appear satisfactory yet be associated with unsatisfactory overall process reliabilities. Second, the use of a multivariate normal distribution for the vector of regression error terms is generalized to that of the (heavier tailed) multivariate t-distribution. This provides a Bayesian sensitivity analysis with regard to moderate outliers. The effect of adding design points is also considered through a preposterior analysis. The advantages of this approach are illustrated with two real examples.

What Your ICH Q8 Design Space Needs: A Multivariate Predictive Distribution

John Peterson

Published in Pharmaceutical Manufacturing, 2009

Abstract: The ICH Q8 core definition of design space is by now somewhat familiar: “The multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality” [1]. This definition is ripe for interpretation. The phrase “multidimensional combination and interaction” underscores the need to utilize multivariate analysis and factorial design of experiments (DoE), while the words “input variables (e.g., material attributes) and process parameters” remind us of the importance of measuring the right variables.

However, in presentations and articles discussing design space, not much focus has been given to the key phrase, “assurance of quality”. This does not seem justified, given that guidance documents such as ICH Q8, Q9, Q10, PAT, etc. are inundated with the words “risk” and “risk-based.” For any ICH Q8 design space constructed, surely the core definition of design space begs the question, “How much assurance?” [2]. How do we know if we have a “good” design space if we do not have a method for quantifying “How much assurance?” in a scientifically coherent manner?

The Impact of the Pneumococcal Conjugate Vaccine on Antimicrobial Resistance in the United States Since 1996: Evidence for a Significant Rebound by 2007 in Many Classes of Antibiotics

Robertino Mera, Linda Miller, Heather Amrine-Madsen, and Daniel F. Sahm

Published in Microbial Drug Resistance, 2009, 15 (4), 261-268

Abstract:

Background: The impact of the introduction of the pneumococcal conjugate vaccine over antimicrobial resistance has not been well established. The present study models the changes in resistance over time for all major classes of antibiotics.

Methods: Susceptibility data on a total of 129,652 isolates from The Surveillance Network
surveillance database during the period 1996–2007 were available for analysis, as well as age, specimen source, inpatient or outpatient location, and census region. Cubic splines in a logistic regression mixed model were used to model changes of the resistance rates over time in the United States, taking into account risk factors, so that separate adjusted curves were modeled for each antibiotic.

Results: Yearly resistance prevalence to most antibiotics had been increasing in the period 1996–2001. Adjusted prevalence rates in a multivariate model declined in the period 2001–2004 for penicillin, erythromycin, amoxicillin=clavulanate, trimethoprim=sulfamethoxazole, tetracycline, ceftriaxone, and multidrug. These same antibiotics showed a significant rebound for the period 2004–2007, with the largest overall increase for erythromycin, followed by amoxicillin=clavulanate, tetracycline, multidrug, penicillin, trimethoprim=sulfamethoxazole, and ceftriaxone. Changes in both decline and rebound were more marked for children <5 years old and for otitis media isolates.

Conclusion: The indirect effect of the pneumococcal conjugate vaccine introduction on yearly resistance prevalence for several antibacterials as well as for multidrug resistance is one of blunting of a prior sustained increase, with a significant but short-lived decrease in resistance rates, and a significant rebound in adjusted rates for the period 2004–2007.

The identification of a novel PDE4 inhibitor, EPPA-1, with improved therapeutic index using pica feeding in rats as a measure of emetogenicity

T. Gregg Davis, John J. Peterson, Jen-Pyng Kou, Elizabeth A. Capper-Spudich, Doug Ball, Anthony T. Nials, Joanne Wiseman, Yemisi E. Solanke, Fiona S. Lucas, Richard A. Williamson, Livia Ferrari, Paul Wren, Richard G. Knowles, Mary S. Barnette, and Patricia L. Podolin

Published in Journal of Pharmacology and Experimental Therapeutics, 2009, 330 (3), 922–931

Abstract: Clinical utility of phosphodiesterase 4 (PDE4) inhibitors as anti-inflammatory agents has, to date, been limited by adverse effects including nausea and emesis, making accurate assessment of emetic versus anti-inflammatory potencies critical to the development of inhibitors with improved therapeutic indices. In the present study we determined the in vitro and in vivo anti-inflammatory potencies of the first-generation PDE4 inhibitor, rolipram, the second-generation inhibitors, roflumilast and cilomilast, and a novel third generation inhibitor, 1-ethyl-5-{5-[(4-methyl-1-piperazinyl)methyl]-1,3,4-oxadiazol-2-yl}-N-(tetrahydro-2H-pyran-4-yl)-1H-pyrazolo[3,4-b]pyridin-4-amine (EPPA-1). The rank-order potency against lipopolysaccharide (LPS)-induced tumor necrosis factor-α production by human peripheral blood mononuclear cells was roflumilast (IC50 = 5 nM) > EPPA-1 (38) > rolipram (269) > cilomilast (389), and against LPS-induced pulmonary neutrophilia in the rat was EPPA-1 (D50 = 0.042 mg/kg) > roflumilast (0.24) > rolipram (3.34) > cilomilast (4.54). Pica, the consumption of non-nutritive substances in response to gastrointestinal stress, was used as a surrogate measure for emesis, giving a rank-order potency of rolipram (D50 = 0.495 mg/kg) > roflumilast (1.6) > cilomilast (6.4) > EPPA-1 (24.3). The low and high emetogenic activities of EPPA-1 and rolipram, respectively, detected in the pica model were confirmed in a second surrogate model of emesis, reversal of α2-adrenoceptor-mediated anesthesia in the mouse. The rank order of therapeutic indices derived in the rat [(pica D50)/(neutrophilia D50)] was EPPA-1 (578) > roflumilast (6.4) > cilomilast (1.4) > rolipram (0.15), consistent with the rank order derived in the ferret [(emesis D50)/(neutrophilia D50)]. These data validate rat pica feeding as a surrogate for PDE4 inhibitor-induced emesis in higher species, and identify EPPA-1 as a novel PDE4 inhibitor with an improved therapeutic index.