Carsten Wrenger

By Carsten Wrenger and Henning Ulrich

Part of the book: Drug Discovery and Development

By Carsten Wrenger, Isolmar Schettert and Eva Liebau

Part of the book: Drug Discovery

By Sergey Lunev, Fernando A. Batista, Soraya S. Bosch, Carsten Wrenger and Matthew R. Groves

In order to counter the malarial parasite’s striking ability to rapidly develop drug resistance, a constant supply of novel antimalarial drugs and potential drug targets must be available. The so-called Harlow-Knapp effect, or “searching under the lamp post,” in which scientists tend to further explore only the areas that are already well illuminated, significantly limits the availability of novel drugs and drug targets. This chapter summarizes the pool of electron transport chain (ETC) and carbon metabolism antimalarial targets that have been “under the lamp post” in recent years, as well as suggest a promising new avenue for the validation of novel drug targets. The interplay between the pathways crucial for the parasite, such as pyrimidine biosynthesis, aspartate metabolism, and mitochondrial tricarboxylic acid (TCA) cycle, is described in order to create a “road map” of novel antimalarial avenues.

Part of the book: Current Topics in Malaria

By Arne Krüger, Vinicius Gonçalves Maltarollo, Carsten Wrenger and Thales Kronenberger

The drug discovery and development pipeline have more and more relied on in vitro testing and in silico predictions to reduce investments and optimize lead compounds. A comprehensive set of in vitro assays is available to determine key parameters of absorption, distribution, metabolism, and excretion, for example, lipophilicity, solubility, and plasma stability. Such test systems aid the evaluation of the pharmacological properties of a compound and serve as surrogates before entering in vivo testing and clinical trials. Nowadays, computer-aided techniques are employed not just in the discovery of new lead compounds but embedded as part of the entire drug development process where the ADME profiling and big data analyses add a new layer of complexity to those systems. Herein, we give a short overview of the history of the drug development pipeline presenting state-of-the-art ADME in vitro assays as established in academia and industry. We will further introduce the underlying good practices and give an example of the compound development pipeline. In the next step, recent advances at in silico techniques will be highlighted with special emphasis on how pharmacogenomics and in silico PK profiling can enhance drug monitoring and individualization of drug therapy.

Part of the book: Drug Discovery and Development