Biomedical subjects

Kevin Lawson

Publications and source records attributed to Kevin Lawson.

5 recordsLinked to original sources

PubMed2004

Kinetic and cardiovascular comparison of immediate-release isradipine and sustained-release isradipine among non-treatment-seeking, cocaine-dependent individuals.

The authors sought to determine whether sustained-release (SR) isradipine provided comparable systemic availability to that of immediate-release (IR) isradipine in non-treatment-seeking, cocaine-dependent individuals. This information could be used to design a rational dosage regimen for additional isradipine clinical trials in the treatment of stimulant dependence and related neurovascular disorders. Eight male volunteers who met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for cocaine dependence participated in a randomized, double-blind, crossover study. Subjects received a 15-mg dose of an IR isradipine formulation and a 30-mg dose of an SR isradipine formulation, separated by a 2-day interval. Vital signs and blood sampling for isradipine serum levels were performed before and at 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 8, 10, 12, and 24 h after each isradipine dose administration. Neither the 15-mg dose of IR isradipine nor the 30-mg dose of SR isradipine produced significant adverse effects on cardiovascular parameters, but the IR formulation was more likely to produce marked short-term decreases in pressor response. Significant intersubject variability in serum concentrations and pharmacokinetic parameters occurred for both formulations. The relative bioavailability of the SR formulation was 55.5% of that of the IR formulation. Both formulations cumulatively may deliver about the same amount of drug, but IR isradipine achieves a higher peak concentration than SR isradipine. The more favorable cardiovascular profile of SR isradipine would, however, make it more appropriate as an investigational medication for the treatment of stimulant dependence and related neurovascular disorders.

Adult↗

PubMed2003

Oral topiramate for treatment of alcohol dependence: a randomised controlled trial.

BACKGROUND: Topiramate, a sulphamate fructopyranose derivative, might antagonise alcohol's rewarding effects associated with abuse liability by inhibiting mesocorticolimbic dopamine release via the contemporaneous facilitation of gamma-amino-butyric acid activity and inhibition of glutamate function. We aimed to see whether topiramate was more effective than placebo as a treatment for alcohol dependence. METHODS: We did a double-blind randomised controlled 12-week clinical trial comparing oral topiramate and placebo for treatment of 150 individuals with alcohol dependence. Of these 150 individuals, 75 were assigned to receive topiramate (escalating dose of 25-300 mg per day) and 75 had placebo as an adjunct to weekly standardised medication compliance management. Primary efficacy variables were: self-reported drinking (drinks per day, drinks per drinking day, percentage of heavy drinking days, percentage of days abstinent) and plasma gamma-glutamyl transferase, an objective index of alcohol consumption. The secondary efficacy variable was self-reported craving. FINDINGS: At study end, participants on topiramate, compared with those on placebo, had 2.88 (95% CI -4.50 to -1.27) fewer drinks per day (p=0.0006), 3.10 (-4.88 to -1.31) fewer drinks per drinking day (p=0.0009), 27.6% fewer heavy drinking days (p=0.0003), 26.2% more days abstinent (p=0.0003), and a log plasma gamma-glutamyl transferase ratio of 0.07 (-0.11 to -0.02) less (p=0.0046). Topiramate-induced differences in craving were also significantly greater than those of placebo, of similar magnitude to the self-reported drinking changes, and highly correlated with them. INTERPRETATION: Topiramate (up to 300 mg per day) is more efficacious than placebo as an adjunct to standardised medication compliance management in treatment of alcohol dependence.

Administration, Oral↗

PubMedDate not supplied

Comparison of ranking methods for virtual screening in lead-discovery programs.

This paper discusses the use of several rank-based virtual screening methods for prioritizing compounds in lead-discovery programs, given a training set for which both structural and bioactivity data are available. Structures from the NCI AIDS data set and from the Syngenta corporate database were represented by two types of fragment bit-string and by sets of high-level molecular features. These representations were processed using binary kernel discrimination, similarity searching, substructural analysis, support vector machine, and trend vector analysis, with the effectiveness of the methods being judged by the extent to which active test set molecules were clustered toward the top of the resultant rankings. The binary kernel discrimination approach yielded consistently superior rankings and would appear to have considerable potential for chemical screening applications.

Journal Article↗

PubMedDate not supplied

Clustering files of chemical structures using the fuzzy k-means clustering method.

This paper evaluates the use of the fuzzy k-means clustering method for the clustering of files of 2D chemical structures. Simulated property prediction experiments with the Starlist file of logP values demonstrate that use of the fuzzy k-means method can, in some cases, yield results that are superior to those obtained with the conventional k-means method and with Ward's clustering method. Clustering of several small sets of agrochemical compounds demonstrate the ability of the fuzzy k-means method to highlight multicluster membership and to identify outlier compounds, although the former can be difficult to interpret in some cases.

Journal Article↗

PubMedDate not supplied

Virtual screening using binary kernel discrimination: analysis of pesticide data.

This paper discusses the use of binary kernel discrimination (BKD) for identifying potential active compounds in lead-discovery programs. BKD was compared with established virtual screening methods in a series of experiments using pesticide data from the Syngenta corporate database. It was found to be superior to methods based on similarity searching and substructural analysis but inferior to a support vector machine. Similar conclusions resulted from application of the methods to a pesticide data set for which categorical activity data were available.

Algorithms↗