Lack of interaction between tolcapone and tolbutamide in healthy volunteers

Human Family 1-4 cytochrome P450 enzymes involved in the metabolic activation of xenobiotic and physiological chemicals: an update

This is an overview of the metabolic activation of drugs, natural products, physiological compounds, and general chemicals by the catalytic activity of cytochrome P450 enzymes belonging to Families 1-4. The data were collected from > 5152 references. The total number of data entries of reactions catalyzed by P450s Families 1-4 was 7696 of which 1121 (~ 15%) were defined as bioactivation reactions of different degrees. The data were divided into groups of General Chemicals, Drugs, Natural Products, and Physiological Compounds, presented in tabular form. The metabolism and bioactivation of selected examples of each group are discussed. In most of the cases, the metabolites are directly toxic chemicals reacting with cell macromolecules, but in some cases the metabolites formed are not direct toxicants but participate as substrates in succeeding metabolic reactions (e.g., conjugation reactions), the products of which are final toxicants. We identified a high level of activation for three groups of compounds (General Chemicals, Drugs, and Natural Products) yielding activated metabolites and the generally low participation of Physiological Compounds in bioactivation reactions. In the group of General Chemicals, P450 enzymes 1A1, 1A2, and 1B1 dominate in the formation of activated metabolites. Drugs are mostly activated by the enzyme P450 3A4, and Natural Products by P450s 1A2, 2E1, and 3A4. Physiological Compounds showed no clearly dominant enzyme, but the highest numbers of activations are attributed to P450 1A, 1B1, and 3A enzymes. The results thus show, perhaps not surprisingly, that Physiological Compounds are infrequent substrates in bioactivation reactions catalyzed by P450 enzyme Families 1-4, with the exception of estrogens and arachidonic acid. The results thus provide information on the enzymes that activate specific groups of chemicals to toxic metabolites.

Sulfonylurea compounds uncouple the glucose dependence of the insulinotropic effect of glucagon-like peptide 1

Glucagon-like peptide (GLP)-1 mimetics have been reported to cause hypoglycemia when combined with sulfonylureas. This study investigated the impact of tolbutamide on the glucose dependence of the GLP-1-mediated effects on insulin, glucagon, and somatostatin secretion in the in situ perfused rat pancreas. At 3 mmol/l glucose, GLP-1 alone did not augment insulin secretion, whereas tolbutamide alone caused a rapid increase in insulin secretion. However, when GLP-1 and tolbutamide were administered simultaneously, insulin secretion increased significantly to 43.7 +/- 6.2 pmol/min (means +/- SE), exceeding the sum of the responses to GLP-1 (2.0 +/- 0.6 pmol/min; P = 0.019) and tolbutamide (11.3 +/- 3.8; P = 0.005) alone by a factor of 3.3. At 11 mmol/l glucose, co-infusion of GLP-1 and tolbutamide augmented insulin secretion to 141.7 +/- 10.3 vs. 115.36 +/- 14.1 (GLP-1) and 42.5 +/- 7.3 pmol/min (tolbutamide). Interestingly, increases in somatostatin secretion, both by glucose and GLP-1, were consistently paralleled by suppression of glucagon release. In conclusion, we demonstrate uncoupling of GLP-1 from its glucose dependence by tolbutamide. This uncoupling probably explains the tendency of GLP-1 to provoke hypoglycemia in combination with sulfonylureas. The results suggest that closure of ATP-sensitive K(+) channels by glucose might be involved in the glucose dependence of GLP-1's insulinotropic effect and that somatostatin acts as a paracrine regulator of glucagon release.

Tolcapone: a review of its use in the management of Parkinson's disease

Tolcapone (Tasmar) is a selective, reversible inhibitor of peripheral and central catechol-O-methyltransferase (COMT). Results of well designed studies indicate that oral tolcapone is an effective adjunct to levodopa plus a peripheral dopa-decarboxylase inhibitor (DDCI) in patients with fluctuating Parkinson's disease. Tolcapone significantly improves levodopa-induced motor fluctuations and significantly reduces levodopa requirements. The drug is generally well tolerated, with the most commonly occurring adverse events being dopaminergic related. Thus, tolcapone is a useful option in patients with fluctuating Parkinson's disease who are receiving levodopa/DDCI and are not responding to, or are not candidates for, other adjunctive treatments.

AN EVALUATION OF THE IN VITRO METABOLISM DATA FOR PREDICTING THE CLEARANCE AND DRUG-DRUG INTERACTION POTENTIAL OF CYP2C9 SUBSTRATES

In the early drug discovery process, metabolic stability and cytochrome P450 inhibition are often used as an early selection tool to identify useful compounds for further development. The reliability of the data in this process is therefore crucial. In the present study, in vitro enzyme kinetic data were used to predict the in vivo clearance and drug-drug interaction potential of four well known CYP2C9 substrates (tolbutamide, fluvastatin, ibuprofen and diclofenac) that are frequently used as benchmark substances in screening programs. Quantitative predictions of hepatic clearance using the well stirred prediction model and CL(int) calculated from enzyme kinetic measurements were not useful. Including and excluding protein binding resulted in under- and overestimation, respectively, of in vivo clearance. The only predicted in vivo clearance that fell into the range of reported measured values was for fluvastatin when protein binding was not included. In an open, randomized, seven-armed, crossover study in healthy volunteers, tolbutamide, ibuprofen, and fluvastatin were investigated as inhibitors of the metabolism of diclofenac, and vice versa. None of the combinations was found to interact with each other in vivo. The in vitro drug-drug interaction potential was investigated by K(i) determinations of the same combinations. In contrast to clearance predictions, the interaction potential in vivo was best predicted when plasma protein binding was included in the various models used. This study points to the uncertainty in calculating in vivo kinetics from in vitro enzyme kinetic data. The in vitro metabolic screening can thus be questioned as a compound selection tool without a proven in vitro-in vivo correlation.

Summary of information on human CYP enzymes: human P450 metabolism data

This chapter is an update of the data on substrates, reactions, inducers, and inhibitors of human CYP enzymes published previously by Rendic and DiCarlo (1), now covering selection of the literature through 2001 in the reference section. The data are presented in a tabular form (Table 1) to provide a framework for predicting and interpreting the new P450 metabolic data. The data are formatted in an Excel format as most suitable for off-line searching and management of the Web-database. The data are presented as stated by the author(s) and in the case when several references are cited the data are presented according to the latest published information. The searchable database is available either as an Excel file (for information contact the author), or as a Web-searchable database (Human P450 Metabolism Database, www.gentest.com) enabling the readers easy and quick approach to the latest updates on human CYP metabolic reactions.