Skip to main content

New Drug Approvals - Pt. XIV - Pitavastatin (Livalo)

The latest FDA approval is Pitavastatin (trade name Livalo), approved on August 3rd. Pitavastatin is an HMG-CoA reductase inhibitor, indicated for the primary treatment of hypercholesterolemia (elevated levels of cholesterol in the blood) on patients unable to sufficiently lower their cholesterol levels by diet and exercise. Hypercholesterolemia is a very widespread and leads to serious cardiovascular disease in affluent and increasingly in developing societies.
Pitavastatin (also known by the research code NKS-104) has been available in Japan since 2003 and is now the sixth statin to reach the U.S. market, after Lovastatin (trade name Mecavor), Pravastatin (trade name Pravachol), Fluvastatin (trade name Lescol), Atorvastatin (trade name Lipitor) and Rosuvastatin (trade name Crestor). All of these drugs are derived from the natural product Mevastatin from the fungus Penicillium citrinum. Like the other statins, Pitavastatin lowers the cholesterol levels by competitively inhibiting HMG-CoA reductase, which is the rate-limiting enzyme of the mevalonate pathway of cholesterol synthesis. Inhibition of this enzyme in the liver results in decreased cholesterol synthesis as well as increased synthesis of low-density lipoprotein (LDL) receptors, resulting in a greater low-density lipoprotein cholesterol (LDL-C) clearance and overall reduction of cholesterol from the bloodstream. However, even in this relatively well studied area of biology, there are still many questions to be answered over cholesterol flux and pathogenesis.
Pitavastatin is small-molecule drug (Molecular Weight of 421.5 g.mol-1), and is fully Rule-of-Five compliant. Pitavastatin has a high bioavailability of 51%, and high protein plasma binding (ppb) of 99%), along with volume of distribution of 148 L and a half-life of 11 hours. Metabolism is primarily by glucuronidation (see below) but there is minor oxidative processing by CYP2C9 (and to a lesser by CYP2C8). The major metabolite isolated from human plasma is the lactone is formed via an ester-type pitavastatin glucuronide conjugate catalysed by UGT1A3 and UGT2B7. Excretion is primarily through feces (79% of dose). Typical dosage is of a single 2 mg tablet once a day (equivalent to a daily dose of 4.8 umol).

The structure (3R,5S,6E)-7-(2-cyclopropyl-4-(4-fluorophenyl)quinolin-3-yl)-3,5-dihydroxyhept-6-enoic acid contains a diol group with two defined stereocenters and a free carboxylic acid group (which mimic the mevalonic acid substrate of the enzyme). The acid group will make the drug negatively charged under physiological conditions and dominate its physical chemistry), common features among many synthetic statins. The remainder of the molecule is largely lipophilic and rigid.
Pitavastatin canonical SMILES: O=C(O)CC(O)CC(O)/C=C/c1c(c3ccccc3nc1C2CC2)c4ccc(F)cc4
Pitavastatin InChI: InChI=1/C25H24FNO4/c26-17-9-7-15(8-10-17)24-20-3-1-2-4-22(20)27-2 5(16-5-6-16)21(24)12-11-18(28)13-19(29)14-23(30)31/h1-4,7-12,16,1 8-19,28-29H,5-6,13-14H2,(H,30,31)/b12-11+
Pitavastatin CAS registry: 147511-69-1
Pitavastatin ChemDraw: Pitavastatin.cdx
The license holder is Kowa Pharmaceuticals and the product website is


Popular posts from this blog

A python client for accessing ChEMBL web services

Motivation The CheMBL Web Services provide simple reliable programmatic access to the data stored in ChEMBL database. RESTful API approaches are quite easy to master in most languages but still require writing a few lines of code. Additionally, it can be a challenging task to write a nontrivial application using REST without any examples. These factors were the motivation for us to write a small client library for accessing web services from Python. Why Python? We choose this language because Python has become extremely popular (and still growing in use) in scientific applications; there are several Open Source chemical toolkits available in this language, and so the wealth of ChEMBL resources and functionality of those toolkits can be easily combined. Moreover, Python is a very web-friendly language and we wanted to show how easy complex resource acquisition can be expressed in Python. Reinventing the wheel? There are already some libraries providing access to ChEMBL d

ChEMBL 29 Released

  We are pleased to announce the release of ChEMBL 29. This version of the database, prepared on 01/07/2021 contains: 2,703,543 compound records 2,105,464 compounds (of which 2,084,724 have mol files) 18,635,916 activities 1,383,553 assays 14,554 targets 81,544 documents Data can be downloaded from the ChEMBL FTP site: .  Please see ChEMBL_29 release notes for full details of all changes in this release: New Deposited Datasets EUbOPEN Chemogenomic Library (src_id = 55, ChEMBL Document IDs CHEMBL4649982-CHEMBL4649998): The EUbOPEN consortium is an Innovative Medicines Initiative (IMI) funded project to enable and unlock biology in the open. The aims of the project are to assemble an open access chemogenomic library comprising about 5,000 well annotated compounds covering roughly 1,000 different proteins, to synthesiz

Identifying relevant compounds in patents

  As you may know, patents can be inherently noisy documents which can make it challenging to extract drug discovery information from them, such as the key targets or compounds being claimed. There are many reasons for this, ranging from deliberate obfuscation through to the long and detailed nature of the documents. For example, a typical small molecule patent may contain extensive background information relating to the target biology and disease area, chemical synthesis information, biological assay protocols and pharmacological measurements (which may refer to endogenous substances, existing therapies, reaction intermediates, reagents and reference compounds), in addition to description of the claimed compounds themselves.  The SureChEMBL system extracts this chemical information from patent documents through recognition of chemical names, conversion of images and extraction of attached files, and allows patents to be searched for chemical structures of interest. However, the curren

Julia meets RDKit

Julia is a young programming language that is getting some traction in the scientific community. It is a dynamically typed, memory safe and high performance JIT compiled language that was designed to replace languages such as Matlab, R and Python. We've been keeping an an eye on it for a while but we were missing something... yes, RDKit! Fortunately, Greg very recently added the MinimalLib CFFI interface to the RDKit repertoire. This is nothing else than a C API that makes it very easy to call RDKit from almost any programming language. More information about the MinimalLib is available directly from the source . The existence of this MinimalLib CFFI interface meant that we no longer had an excuse to not give it a go! First, we added a BinaryBuilder recipe for building RDKit's MinimalLib into Julia's Yggdrasil repository (thanks Mosè for reviewing!). The recipe builds and automatically uploads the library to Julia's general package registry. The build currently targe

New Drug Warnings Browser

As mentioned in the announcement post of  ChEMBL 29 , a new Drug Warnings Browser has been created. This is an updated version of the entity browsers in ChEMBL ( Compounds , Targets , Activities , etc). It contains new features that will be tried out with the Drug Warnings and will be applied to the other entities gradually. The new features of the Drug Warnings Browser are described below. More visible buttons to link to other entities This functionality is already available in the old entity browsers, but the button to use it is not easily recognised. In the new version, the buttons are more visible. By using those buttons, users can see the related activities, compounds, drugs, mechanisms of action and drug indications to the drug warnings selected. The page will take users to the corresponding entity browser with the items related to the ones selected, or to all the items in the dataset if the user didn’t select any. Additionally, the process of creating the join query is no