To gain a better understanding of the metabolic properties between the open acid and lactone form of HMG-CoA reductase inhibitors (statins), the paper focused primarily on characterizing the metabolic properties of statins. We compared the metabolism of the acid and lactone forms of several statins, including atrovastatin, simvastatin, cerivastatin fluvastatin, pitavastatin and rosuvastatin with respect to metabolic clearance, CYP enzymes involved and drug-drug interactions. A remarkable increase in metabolic clearance was noted for all lactones compared with all acids except for pitavastatin lactone. The metabolic clearances of the atrovastatin, simvastatin, cerivastatin, fluvastatin and rosuvastatin lactones were 73-, 70-, 30-, 7- and 64-fold higher, respectively, than those of the corresponding acids. CYP2Cs were critically involved in the metabolism of cerivastatin, fluvastatin and pitavastatin acids. In contrast, CYP2Cs were not involved in the metabolism of the corresponding lactones and CYP3A4 was mainly involved. Moreover, a substantial difference in the metabolic inhibition of statins was found between acids and lactones. Overall, the study demonstrates that CYP-mediated metabolism of lactones is also a common metabolic pathway for statins and that the CYP3A4-mediated metabolism of the lactone forms clearly will need to be taken into account in assessing mechanistic aspects of drug-drug interaction involving statins.
1. Pitavastatin is a potent competitive inhibitor of HMG-CoA reductase little metabolized in hepatic microsomes. Pitavastatin lactone, which can be converted back to the unchanged form, is the major metabolite of pitavastatin in humans. To clarify the mechanism of the lactonization of pitavastatin and the metabolic properties of the lactone, we performed experiments in vitro. 2. On addition of UDP-glucuronic acid, human hepatic microsomes produced pitavastatin lactone and an unknown metabolite (UM-2). UM-2 was converted to its unchanged form by enzymatic hydrolysis and to a lactone form non-enzymatically. Using several human UGT-expressing microsomes, UGT1A3 and UGT2B7 were principally responsible for glucuronidation of pitavastatin leading to lactonization. 3. No marked difference in intrinsic clearance between pitavastatin and its lactone form was detected in human hepatic microsomes. 4. Pitavastatin lactone showed no inhibitory effects on CYP2C9- and CYP3A4-mediated metabolism of model substrates in contrast to other HMG-CoA reductase inhibitors. 5. The mechanism of pitavastatin lactone formation has been clarified, in that glucuronidation by UGT occurs first followed by lactonization via an elimination reaction. It was also found that pitavastatin lactone demonstrates no drug-drug interactions.
The purpose of this study was to gain a better understanding of the transport mechanism of pitavastatin, a novel synthetic HMG-CoA reductase inhibitor. Experiments were performed using oocytes of Xenopus laevis expressing several solute carrier (SLC) transporters and recombinant membrane vesicles expressing several human ABC transporters. The acid form of pitavastatin was shown to be a substrate for human OATP1, OATP2, OATP8, OAT3 and NTCP, and for rat Oatp1 and Oatp4 with relatively low K(m) values. In contrast, these SLC transporters were not involved in the uptake of the lactone form. A significant stimulatory effect was exhibited by pitavastatin lactone, while the acid form did not exhibit ATPase hydrolysis of P-glycoprotein. In the case of breast cancer resistant protein (BCRP), the acid form of pitavastatin is a substrate, whereas the lactone form is not. Taking these results into consideration, several SLC and ABC transporters were identified as critical to the distribution and excretion of pitavastatin in the body. This study showed, for the first time, that acid and lactone forms of pitavastatin differ in substrate activity towards uptake and efflux transporters. These results will potentially contribute to the differences in the pharmacokinetic profiles of pitavastatin.
This paper provides a fast Projection algorithm and a step size conl.rol to obtain the same steady-state excess mean squared error (MSE) for various projection orders. Computer simulations for colored noise and speech input signal confirm the effectiveness of the Projection algorithm and the step size control. lntroductiionOf the many adaptive filtering algorithms, the Normalized LMS (NLMS) algorithm is generally used in practice because of its simplicity. The computational complexity of the NLMS algcirithm is low, however, convergence is very slow and tracking is poor for a colored input signal such as speech.Thc RLS (Recursive Least Squares) algorithm, on the other hand, has the same convergence speed for both a colored input signal and a white signal, but its large computational complexity is a drawback.In recent years, an algorithm called Projection (or Affine Projection) [ 11 has been drawing attention. This algorithm has properties that lie between those of the NLMS and RLS, i.e. less computational complexity than RLS but much faster convergence than NLMS for an input signal such as speech which can be modeled as a low-order AR process. The Projection algorithm, however, still needed more computation than NLMS, which was a problem.Recently, efforts to reduce the amount of computation have been made [2] [3] [4], and computational complexity has been significantly reduced. This paper describes the fast Projection algorithm and proposes a control method for so-called step size parameter to obtain the same steady-state excess MISE for various projection orders.
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