Ring flexibility within tricyclic antidepressant drugs

The internal flexibility of the central seven-membered ring of a series of tricyclic antidepressant drugs (TCAs), imipramine {l}, amitriptyline {2}, doxepin {3}, and dothiepin {4}, has been investigated by H-1 and C-13 nuclear magnetic (NMR) techniques. Two dynamic processes were examined: ring inversion and bridge flexing. H-1 NMR lineshape analysis was used to obtain ring inversion barriers for 2-4. These studies yielded energy barriers of 14.3, 16.7, and 15.7 +/- 0.6 kcal/mol for the hydrochloride salts of doxepin, dothiepin, and amitriptyline, respectively. The barriers for the corresponding free bases were lower by 0.6 kcal/mol on average. (CT1)-C-13 relaxation measurements were used to determine the degree of bridge flexing associated with the central seven-membered ring for all four compounds. By fitting the T-1 data to a two-state jump model, lifetimes and amplitudes of rapid bridge flexing motions were determined. The results show that imipramine has the fastest rate of bridge flexing, followed by amitriptyline, doxepin, and dothiepin. The pharmacological profiles of the TCAs are complex and they interact with many receptor sites, resulting in numerous side effects and a general lack of understanding of their precise mode of action in different anxiety-related disorders. They all have similar three-dimensional structures, which makes it difficult to rationalize their differing relative potency in different assays/clinical settings. However, the clear finding here that there are significantly different degrees of internal mobility suggests that molecular dynamics should be an additional factor considered when trying to understand the mode of action of this clinically important family of molecules. (C) 2001 Wiley-Liss, Inc. and the American Pharmaceutical Association J Pharm Sci 90:713-721, 2001.

Single patient (n-of-1) trials with binary treatment preference

The use of a fully parametric Bayesian method for analysing single patient trials based on the notion of treatment 'preference' is described. This Bayesian hierarchical modelling approach allows for full parameter uncertainty, use of prior information and the modelling of individual and patient sub-group structures. It provides updated probabilistic results for individual patients, and groups of patients with the same medical condition, as they are sequentially enrolled into individualized trials using the same medication alternatives. Two clinically interpretable criteria for determining a patient's response are detailed and illustrated using data from a previously published paper under two different prior information scenarios. Copyright (C) 2005 John Wiley & Sons, Ltd.