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New York, NY, United States

Forest Laboratories is an American pharmaceutical company headquartered in New York City. The company's research and development spending has grown rapidly in recent years and, as of 2007, approached almost a billion U.S. dollars a year, which put it on the list of the top 100 global corporations in R&D spending. Forest Laboratories is also known for licensing European pharmaceuticals for sale in the United States.The company also has offices in St. Louis, Cincinnati, Jersey City, Oakland, Dublin, Kent and Paris. Wikipedia.


Lu K.,Forest Laboratories
Statistics in Medicine | Year: 2014

Pattern-mixture models provide a general and flexible framework for sensitivity analyses of nonignorable missing data. The placebo-based pattern-mixture model (Little and Yau, Biometrics 1996; 52:1324-1333) treats missing data in a transparent and clinically interpretable manner and has been used as sensitivity analysis for monotone missing data in longitudinal studies. The standard multiple imputation approach (Rubin, Multiple Imputation for Nonresponse in Surveys, 1987) is often used to implement the placebo-based pattern-mixture model. We show that Rubin's variance estimate of the multiple imputation estimator of treatment effect can be overly conservative in this setting. As an alternative to multiple imputation, we derive an analytic expression of the treatment effect for the placebo-based pattern-mixture model and propose a posterior simulation or delta method for the inference about the treatment effect. Simulation studies demonstrate that the proposed methods provide consistent variance estimates and outperform the imputation methods in terms of power for the placebo-based pattern-mixture model. We illustrate the methods using data from a clinical study of major depressive disorders. © 2013 John Wiley & Sons, Ltd.


Lu K.,Forest Laboratories
Pharmaceutical Statistics | Year: 2014

Pattern-mixture models provide a general and flexible framework for sensitivity analyses of nonignorable missing data in longitudinal studies. The placebo-based pattern-mixture model handles missing data in a transparent and clinically interpretable manner. We extend this model to include a sensitivity parameter that characterizes the gradual departure of the missing data mechanism from being missing at random toward being missing not at random under the standard placebo-based pattern-mixture model. We derive the treatment effect implied by the extended model. We propose to utilize the primary analysis based on a mixed-effects model for repeated measures to draw inference about the treatment effect under the extended placebo-based pattern-mixture model. We use simulation studies to confirm the validity of the proposed method. We apply the proposed method to a clinical study of major depressive disorders. Copyright © 2013 John Wiley & Sons, Ltd. Copyright © 2013 John Wiley & Sons, Ltd.


Baseline adjustment is an important consideration in thorough QT/QTc studies for non-antiarrhythmic drugs. The time-matched baseline is often used in practice to adjust for the within-subject diurnal effects. More recently, the day-averaged baseline has been proposed in the literature to improve the efficiency of treatment comparisons for the primary and assay sensitivity hypotheses. We recommend an analysis of covariance (ANCOVA) model with change from the time-matched baseline as the response and both the time-matched baseline and the day-averaged baseline as the covariates. This model adjusts for the within-subject diurnal effects and at the same time is more efficient and robust than the ANCOVA models based on either the time-matched baseline alone or the day-averaged baseline alone. © 2012 John Wiley & Sons, Ltd.


Patent
Forest Laboratories | Date: 2015-02-25

The present invention relates to pharmaceutical compositions comprising roflumilast in combination with a corticosteroid and/or a leukotriene receptor antagonist. The invention also relates to the use of such compositions for the treatment of Chronic Obstructive Pulmonary Disorder (COPD).


The present invention relates to compounds and processes for preparing compounds of Formula (I), including compounds such as trans-7-oxo-6-(sulphooxy)-1,6-diazabicyclo[3,2,1]octane-2-carboxamide and salts thereof (e.g., NXL-104).

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