Drug target validation

 

Developing a drug from early screening stages to regulatory approval is a cost and time consuming process that can take 12-15 years and has been estimated to cost 2.6 billion US$ [1]. Importantly, lowest success rates are seen in clinical stages of development (Fig. 1a). If compounds fail in the clinics this is due to either efficacy or safety and “both of these are often the direct result of sloppy early target validation," says David Szymkowski, director of biotherapeutics at the biopharmaceutical company Xencor [2].

As the development a drug against a certain target is a big commitment in terms of time and money, target validation is of paramount importance in the drug-discovery process. Therefore, model systems are needed to test whether the chosen target is instrumental in the given disease of interest in humans.

The novel physiological and pathophysiological hepatic in vitro systems offer the possibility to test and validate targets before committing vast monetary and temporal resources to a promising lead compound. The system allows to use sense reversal strategies by which modulation of expression of the gene(s) of interest and monitor its effects on the efficacy of the drug candidate using a multitude of biochemical and molecular endpoints. Thereby, we can provide proof-of-concept data that directly demonstrates whether the potential target is indeed implicated in drug action, thus bolstering confidence and reducing the likelihood of expensive failures of poorly-chosen candidates (Fig. 1b,c).


 

Figure 1: The importance of validated drug targets in drug discovery and development. a, Flow scheme showing the percentage of compounds progressing through the different stages of drug discovery and development. The model is based on a set of industry-appropriate R&D assumptions (industry benchmarks and data from Eli lilly and Company) and was modified from [3]. Note that the lowest progression rates are observed in the expensive clinical stages of development, suggesting suboptimal compound selection. b-c, Proof-of-concept evaluation of downstream effects of an antagomiR candidate drug. 3D spheroids were transfected with the fluorescent Dy547-labeled miRNA transfection control reagent to monitor the delivery of miRIDIAN antagomiRs ( b). c, PHH were transfected with miR-103 antagomiR and total RNA was isolated. Subsequent expression analyses revealed that CYP2C8 mRNA levels were increased dose-dependently with increasing amounts of miR-103 antagomiR, indicating the risk of potential drug-drug-interactions. * indicates p<0.05. Figure from Bell et al., SciRep, 2016.

 

 

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