Biomedical subjects

Andrew Rusinko

Publications and source records attributed to Andrew Rusinko.

3 recordsLinked to original sources

PubMed2005

Ocular pharmacokinetics of moxifloxacin after topical treatment of animals and humans.

The ocular penetration and pharmacokinetics of moxifloxacin in comparison to other fluoroquinolones (ofloxacin, ciprofloxacin, gatifloxacin, norfloxacin, levofloxacin, and lomefloxacin) have been determined by in vitro and ex vivo techniques, as well as in animal and human studies. This article reviews the original pharmacokinetics work performed by Alcon and other studies reported in the ocular fluoroquinolone literature. The results consistently demonstrate higher maximum concentrations for moxifloxacin relative to the other fluoroquinolones in ocular tissues with levels well above its minimum inhibitory concentrations for relevant ocular pathogens. This superior performance is due to the unique structure of moxifloxacin that combines high lipophilicity for enhanced corneal penetration with high aqueous solubility at physiological pH. The latter property creates a high concentration gradient at the tear film/corneal epithelial interface providing a driving force for better ocular penetration for moxifloxacin. In addition, the higher concentration of moxifloxacin in VIGAMOX (i.e., 0.5% vs. 0.3%) allows more antibiotic to be available to ocular tissues. It is clear from the array of studies summarized in this report that moxifloxacin penetrates ocular tissues better (two- to three-fold) than gatifloxacin, ciprofloxacin, ofloxacin, or levofloxacin. This consistent, enhanced penetration of topical moxifloxacin offers powerful advantages for ophthalmic therapy.

Administration, Topical↗

PubMed2003

A novel and selective 5-HT2 receptor agonist with ocular hypotensive activity: (S)-(+)-1-(2-aminopropyl)-8,9-dihydropyrano[3,2-e]indole.

Serotonin 5-HT2 receptor agonists have recently been shown to be effective in lowering intraocular pressure in nonhuman primates and represent a potential new class of antiglaucoma agents. As part of an effort to identify new selective agonists at this receptor, we have found that (S)-(+)-1-(2-aminopropyl)-8,9-dihydropyrano[3,2-e]indole (AL-37350A, 11) has high affinity and selectivity (>1000-fold) for the 5-HT(2) receptor relative to other 5-HT receptors. More specifically, 11 is a potent agonist at the 5-HT2A receptor (EC50 = 28.6 nM, E(max) = 103%) that is comparable to serotonin. Evaluation of 11 in conscious ocular hypertensive cynomolgus monkeys showed this compound to be efficacious in reducing intraocular pressure (13.1 mmHg, -37%). Thus, 11 is a potent full agonist with selectivity for the 5-HT2 receptor and is anticipated to serve as a useful tool in exploring the role of the 5-HT2 receptor and its effector system in controlling intraocular pressure.

Administration, Topical↗

PubMed2002

Optimization of focused chemical libraries using recursive partitioning.

A number of methods currently exist for designing chemical libraries. General or universal libraries use a measurement of chemical diversity in their design and seek to cover as much of chemical space as possible in order to maximize the likelihood of discovering a novel lead class of active compounds. Focused chemical libraries are then synthesized to expand on this particular class and thoroughly explore the space about it. Rarely, however, is relevant biological data tightly incorporated in the design of focused libraries. Recursive partitioning is a statistical technique that is used to quickly build SAR models from high-throughput screening data sets and associated chemical descriptors. Using these models in a virtual screening mode significantly increases the probability of finding other active compounds. The predicted activity can be also be used as the fitness function for a genetic algorithm that is designed to select monomer subsets having a higher probability of being active. This dramatically reduces the number of compounds that need to be synthesized in focused libraries thus saving considerable time, effort and expense. This paper describes how recursive partitioning models are used to optimize the design of focused chemical libraries.

Chemistry, Pharmaceutical↗