Skip to main content

New Drug Approvals 2011 - Pt. XXVII Deferiprone (FerriproxTM)




 
ATC code V03AC02 
Wikipedia Deferiprone

On October 14th, 2011 FDA announced the approval of Deferiprone (trade name: FerriproxTM) for the treatment of iron overload which is potentially fatal in patients with thalassemia. Deferiprone is an oral iron chelating agent, binding excess iron in the blood and thus making it available to excretion from the body. Thalassaemia is a inherited (mostly autosomal recessive) blood disease that can lead to anemia by causing the formation of abnormal hemoglobin molecules not able to properly bind and release oxygen. Thalassaemia (OMIM: 141800 (α-) / 141900 (β-)) is sub-classified according to which of the subunits of the hetero-tetrameric (2α/2β, UniProt: P69905 / P68871) hemoglobin is affected, contrary to sickle-cell anaemia (OMIM: 603903) which results exclusively from a specific mutation in the β subunit. The primary treatment of thalassaemia major, the severe form of β-thalassaemia, requires frequent blood transfusions to establish stable levels of functional hemoglobin but results in high levels of iron accumulating and impairing organ function. Thus, the secondary treatment aims on reducing the toxic iron levels by binding excess iron utilizing an iron chelating agent such as Deferoxamine (ChEMBL ID: CHEMBL556) requiring parenteral administration; Deferiprone has the desirable property of being orally available.

Deferiprone (3-hydroxy-1,2-dimethylpyridin-4(1H)-one, canonical SMILES: CN1C=CC(=O)C(=C1C)O, Standard InChI: InChI=1S/C7H9NO2/c1-5-7(10)6(9)3-4-8(5)2/h3-4,10H,1-2H3 , ChEMBL ID: CHEMBL556, CAS number: 30652-11-0, PubChem: CID 2972, ChemSpider: 2866) is a very simple synthetic small molecule with molecular weight of 139.152 Da, it has no rotatable bonds, two hydrogen bond acceptors, one hydrogen bond donor, ALogP of -0.14 and is thus fully rule-of-five compliant. 

Ferriprox is dosed as 500 mg tablets and administred orally three times daily in doses of 25 mg/kg to 33 mg/kg body weight (rounded to the nearest half-tablet), resulting in a daily molar dose of ~38-50 mmol for a 70 kg individual. Common adverse reactions include chromaturia, nausea, vomiting and abdominal pain, among others. Ferriprox is not suitable for pregnant or nursing women. Ferriprox reaches a maximum concentration (Cmax) of 20 mcg/mL, has an elimination half life (t1/2) of 1.9 hours and is excreted renally. The volume of distribution is 1.6 L/kg and 1 L/kg in thalassaemia patients and healthy subjects, respectively. Peak serum concentrations are reached 2 to 4 hours after administration.

Ferriprox has been issued a boxed warning for its potential to cause agranulocytosis/neutropenia, hematological disorders characterized by abnormally low numbers of white blood cells potentially leading to serious infections and death. 

Ferriprox is marketed and has been developed by Apotex

The full prescribing information can be found here. Prior to its approval in North America, Ferriprox has been approved and available in Europe and Asia for several years - approval in North America had been delayed considerably by safety concerns brought forward by a clinical researcher formerly involved in the clinical studies.

Comments

Popular posts from this blog

New SureChEMBL announcement

(Generated with DALL-E 3 ∙ 30 October 2023 at 1:48 pm) We have some very exciting news to report: the new SureChEMBL is now available! Hooray! What is SureChEMBL, you may ask. Good question! In our portfolio of chemical biology services, alongside our established database of bioactivity data for drug-like molecules ChEMBL , our dictionary of annotated small molecule entities ChEBI , and our compound cross-referencing system UniChem , we also deliver a database of annotated patents! Almost 10 years ago , EMBL-EBI acquired the SureChem system of chemically annotated patents and made this freely accessible in the public domain as SureChEMBL. Since then, our team has continued to maintain and deliver SureChEMBL. However, this has become increasingly challenging due to the complexities of the underlying codebase. We were awarded a Wellcome Trust grant in 2021 to completely overhaul SureChEMBL, with a new UI, backend infrastructure, and new f

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

Multi-task neural network on ChEMBL with PyTorch 1.0 and RDKit

  Update: KNIME protocol with the model available thanks to Greg Landrum. Update: New code to train the model and ONNX exported trained models available in github . The use and application of multi-task neural networks is growing rapidly in cheminformatics and drug discovery. Examples can be found in the following publications: - Deep Learning as an Opportunity in VirtualScreening - Massively Multitask Networks for Drug Discovery - Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set But what is a multi-task neural network? In short, it's a kind of neural network architecture that can optimise multiple classification/regression problems at the same time while taking advantage of their shared description. This blogpost gives a great overview of their architecture. All networks in references above implement the hard parameter sharing approach. So, having a set of activities relating targets and molecules we can tra

LSH-based similarity search in MongoDB is faster than postgres cartridge.

TL;DR: In his excellent blog post , Matt Swain described the implementation of compound similarity searches in MongoDB . Unfortunately, Matt's approach had suboptimal ( polynomial ) time complexity with respect to decreasing similarity thresholds, which renders unsuitable for production environments. In this article, we improve on the method by enhancing it with Locality Sensitive Hashing algorithm, which significantly reduces query time and outperforms RDKit PostgreSQL cartridge . myChEMBL 21 - NoSQL edition    Given that NoSQL technologies applied to computational chemistry and cheminformatics are gaining traction and popularity, we decided to include a taster in future myChEMBL releases. Two especially appealing technologies are Neo4j and MongoDB . The former is a graph database and the latter is a BSON document storage. We would like to provide IPython notebook -based tutorials explaining how to use this software to deal with common cheminformatics p

ChEMBL 26 Released

We are pleased to announce the release of ChEMBL_26 This version of the database, prepared on 10/01/2020 contains: 2,425,876 compound records 1,950,765 compounds (of which 1,940,733 have mol files) 15,996,368 activities 1,221,311 assays 13,377 targets 76,076 documents You can query the ChEMBL 26 data online via the ChEMBL Interface and you can also download the data from the ChEMBL FTP site . Please see ChEMBL_26 release notes for full details of all changes in this release. Changes since the last release: * Deposited Data Sets: CO-ADD antimicrobial screening data: Two new data sets have been included from the Community for Open Access Drug Discovery (CO-ADD). These data sets are screening of the NIH NCI Natural Product Set III in the CO-ADD assays (src_id = 40, Document ChEMBL_ID = CHEMBL4296183, DOI = 10.6019/CHEMBL4296183) and screening of the NIH NCI Diversity Set V in the CO-ADD assays (src_id = 40, Document ChEMBL_ID = CHEMBL4296182, DOI = 10.601