The selection of candidate genes worthy of exploitation as drug development targets requires a crucial but difficult prioritization process, made all the more expensive and complex nowadays by the plethora of targets candidates now on the market. Indeed, the widespread application of first generation functional genomics technologies in recent years has resulted in a large increase in new targets discovered, creating a new bottleneck in the process: the need for large-scale target validation.

The advent of RNAi technology has offered arguably the best tool available to date for addressing this need. In particular, the application of RNAi at high throughput (HT) in combination with high content (HC) readouts in human cells allows the efficient yet detailed validation of large collections of target candidates. The resulting target prioritization processes are inherently more meaningful, as they are based on the analysis of loss-of-function phenotypes, i.e. the type of cell-based experimental data that offers highest patho-physiological relevance and predictive value for the development of antagonist-type therapeutics. 

The RNAi-based Target Validation Program at Cenix has emerged from the company's pioneering expertise in carrying out genome-scale HT-RNAi studies, integrating a diverse range of HC readouts. This background has ideally prepared the company for taking on virtually any scale and scope of target validation project. Having applied HT/HC-RNAi in multiple disease areas using a wide range of human and rodent cells for industry clients and academic partners alike, Cenix scientists are uniquely experienced at combining their own assays with those of our partners and clients to build-up target validation programs that are fully-customized for their needs.

The extensive expertise available at Cenix for developing multiplexed cell-based assays offers the particularly powerful ability to efficiently carry out comprehensive profiling of RNAi-induced phenotypes. The value of this approach derives not only from the need to characterize the desired loss-of-function phenotype, but also, and perhaps even more importantly, to broaden the analysis window so as to maximize the ability to detect undesirable aspects of a target's associated phenotypes as early as possible.

Indeed, a key guiding principle of Cenix's philosophy in building target validation and prioritization programs is the concept of Target Invalidation: making all possible efforts to extract the most comprehensive and predictive datasets that can be obtained from in vitro cell-based experimentation not only to confirm "winners" but also to eliminate false leads at this early stage when investments are still relatively modest, before much larger downstream expenses are incurred. Such

• testing a target's possible involvement in other pathways known to be beneficial or problematic;
• surveying broader range of cellular components and processes;
  
• surveying results from several cell lines of different tissue derivations;
  
• monitoring more time points to better understand the kinetics of a given phenotype;
  

The RNAi Profiling approach therefore offers an ideal way of efficiently generating broader, more predictive validation datasets that will not only facilitate target prioritization in the short-term, but also greatly strengthen the scientific basis for securing regulatory approvals in the long-term.

Target validation projects at Cenix, especially the ones starting from large collections of genes, are typically structured in two stages:

1. Prioritization stage: a primary, streamlined set of multiplexed assays is applied to eliminate "false leads" and select those targets that warrant the more in-depth analysis;
   
2. Profiling stage: a more comprehensive program of cell-based analyses, jointly designed with the client, is applied to  those targets selected above, making maximal use of multiplexed assays to generate the most complete yet most cost-efficient profile possible.
   

		Typical Project Outline for a Large-Scale HT-RNAi Target Validation Study: