Skip to main content

New Drug Approvals 2014 - Pt. X - Albiglutide (Eperzan™ or Tanzeum™)

Wikipedia: Albiglutide

On April 15th the FDA approved Tanzeum (albiglutide) subcutaneous injection to improve glycemic control, along with diet and exercise, in adults with type 2 diabetes.

Type II diabetes

Type II diabetes is a metabolic disorder that is characterized by high blood sugar (hyperglycemia) due to insulin resistance or relative lack of insulin. The disease affects millions of patient world-wide and can lead to long-term complications if the blood levels are not lowered in the patients: heart diseases, strokes and kidney failure.


The drug is a dipeptidyl peptidase-4-resistant glucagon-like peptide-1 dimer fused to human albumin.
Schematic representation of the albiglutide (EMA)

Mode of action

Traditionally, a decrease in the glucose blood level of affected patients is triggered using insulin injections. One alternative mechanism consists at indirectly stimulating insulin release using a glucagon-like peptide-1 (GLP-1) or an analogue of the corresponding receptor.
GLP-1 receptor agonists are of particular interest, as they naturally stop simulating insulin release when plasma glucose concentration is in the fasting range, and hence preventing hypoglycemia in the patient too.
The natural half-life of GLP-1 is less than 2 minutes in the human blood, the peptide is rapidly degraded by an enzyme called dipeptidyl peptidase-4. On the other hand, albiglutide half-life ranges between four to seven days (resistance to dipeptidyl peptidase-4), a considerably longer time than endogenous peptide and than the others GLP-1 analogous drugs (exenatide and liraglutide). This property allows to reduce the number of injections in diabetic patient to biweekly or weekly instead of daily, hence considerably increasing treatment overheads.

Clinical trials

A series of eight clinical trials involving over 2,000 patients with type II diabetes demonstrated the safety and effectiveness of the drug. Patients reported improved HbA1c level (hemoglobin A1c or glycosylated hemoglobin, a measure of blood sugar control). The most common side-effects observed were diarrhea, nausea, and injection site reactions.

Indication and warnings

Albiglutide can be used as a stand-alone as well as in combination therapy (with metformin, glimepiride, pioglitazone, or insulin for instance). The drug is not suited to treat type I diabetes and not indicated for patients with increased ketones in their blood or urine. Albiglutide should be used only when diet and exercise therapies are not successful.
The drug has an FDA boxed warning, as cases of tumors of the thyroid gland have been observed in rodent studies with some other GLP-1 receptor agonists. The FDA further required post-marketing studies regarding dose, efficacy and safety in pediatric patients and for cardiovascular outcomes in patients with high baseline risk of cardiovascular disease.


The drug was invented by Human Genome Sciences and was developed in collaboration with GSK. Albiglutide is marketed as Eperzan in Europe and Tanzeum in the USA.


Popular posts from this blog

UniChem 2.0

UniChem new beta interface and web services We are excited to announce that our UniChem beta site will become the default one on the 11th of May. The new system will allow us to better maintain UniChem and to bring new functionality in a more sustainable way. The current interface and web services will still be reachable for a period of time at . In addition to it, the most popular legacy REST endpoints will also remain implemented in the new web services: Some downtime is expected during the swap.  What's new? UniChem’s current API and web application is implemented with a framework version that’s not maintained and the cost of updating it surpasses the cost of rebuilding it. In order to improve stability, security, and support the implementation and fast delivery of new features, we have decided to revamp our user-facing systems using the latest version of widely used and maintained frameworks, i

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

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 30 released

  We are pleased to announce the release of ChEMBL 30. This version of the database, prepared on 22/02/2022 contains: 2,786,911 compound records 2,157,379 compounds (of which 2,136,187 have mol files) 19,286,751 activities 1,458,215 assays 14,855 targets 84,092 documents Data can be downloaded from the ChEMBL FTP site: Please see ChEMBL_30 release notes for full details of all changes in this release: New Deposited Datasets EUbOPEN Chemogenomic Library (src_id = 55, ChEMBL Document ID CHEMBL4689842):   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 synthesize at least

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