An Experimental Model of Prostatic Inflammation for Drug Discovery

There is increasing evidence to support a significant role for chronic non-bacterial, prostatic inflammation in the development of human voiding dysfunction and prostate cancer. Their increased prevalence with age suggests that the decrease of testosterone concentration and/or the ratio of testosterone-to-estradiol in serum may have a role in their development. The main objective of this study was to explore prostatic inflammation and its relationship with voiding dysfunction and prostate carcinogenesis by developing an experimental model. A novel selective estrogen receptor modulator (SERM), fispemifene, was tested for the prevention and treatment of prostatic inflammation in this model. Combined treatment of adult Noble rats with testosterone and estradiol for 3 to 6 weeks induced gradually developing prostatic inflammation in the dorsolateral prostatic lobes. Inflammatory cells, mainly T-lymphocytes, were first seen around capillaries. Thereafter, the lymphocytes migrated into the stroma and into periglandular space. When the treatment time was extended to 13 weeks, the number of inflamed acini increased. Urodynamical recordings indicated voiding dysfunction. When the animals had an above normal testosterone and estradiol concentrations but still had a decreased testosterone-to-estradiol ratio in serum, they developed obstructive voiding. Furthermore, they developed precancerous lesions and prostate cancers in the ducts of the dorsolateral prostatic lobes. Interestingly, inflammatory infiltrates were observed adjacent to precancerous lesions but not in the adjacency of adenocarcinomas suggesting that inflammation has a role in the early stages of prostate carcinogenesis. Fispemifene, a novel SERM tested in this experimental model, showed anti-inflammatory action by attenuating the number of inflamed acini in the dorsolateral prostate. Fispemifene exhibited also antiestrogenic properties by decreasing expression of estrogen-induced biomarkers in the acinar epithelium. These findings suggest that SERMs could be considered as a new therapeutic possibility in the prevention and in the treatment of chronic prostatic inflammation

Drug loading of mesoporous silicon particles

Porous silicon (PSi) is a promising material to be utilized in drug delivery formulations. The release rate of the drug compound can be controlled by changing the pore properties and surface chemistry of PSi. The loading of a poorly soluble drug into mesoporous silicon particles enhances its dissolution in the body. The drug loading is based on adsorption. The attainable maximum loaded amount depends on the properties of the drug compound and the PSi material, and on the process conditions. The loading solvent also essentially affects the adsorption process. The loading of indomethacin into PSi particles with varying surface modification was studied. Solvent mixtures were applied in the loading, and the loaded samples were analyzed with thermal analysis methods. The best degree of loading was obtained using a mixture of dichloromethane and methanol. The drug loads varied from 7.7 w-% to 26.8 w-%. A disturbing factor in the loading experiments was the tendency of indomethacin to form solvates with the solvents applied. In addition, the physical form and stability of indomethacin loaded in PSi and silica particles were studied using Raman spectroscopy. In the case of silica, the presence of crystalline drug as well as the polymorph form can be detected, but the method proved to be not applicable for PSi particles.

Study of ligand-based virtual screening tools in computer-aided drug design

Virtual screening is a central technique in drug discovery today. Millions of molecules can be tested in silico with the aim to only select the most promising and test them experimentally. The topic of this thesis is ligand-based virtual screening tools which take existing active molecules as starting point for finding new drug candidates. One goal of this thesis was to build a model that gives the probability that two molecules are biologically similar as function of one or more chemical similarity scores. Another important goal was to evaluate how well different ligand-based virtual screening tools are able to distinguish active molecules from inactives. One more criterion set for the virtual screening tools was their applicability in scaffold-hopping, i.e. finding new active chemotypes. In the first part of the work, a link was defined between the abstract chemical similarity score given by a screening tool and the probability that the two molecules are biologically similar. These results help to decide objectively which virtual screening hits to test experimentally. The work also resulted in a new type of data fusion method when using two or more tools. In the second part, five ligand-based virtual screening tools were evaluated and their performance was found to be generally poor. Three reasons for this were proposed: false negatives in the benchmark sets, active molecules that do not share the binding mode, and activity cliffs. In the third part of the study, a novel visualization and quantification method is presented for evaluation of the scaffold-hopping ability of virtual screening tools.