Most drug development pipelines in the industry today contain numerous compounds, from leads to Phase 3, whose exact cellular mechanisms of action (MoA) remains poorly understood. Such knowledge is recognized by all as being crucial to understanding and thereby minimizing the risks of side-effects, while maximizing the chance of long-term therapeutic success. The high profile withdrawal of several so-called blockbuster drugs from the market in recent years has forced many to fundamentally re-assess their approaches to characterizing drug MoAs. However, until recently, experimental methods to broaden and deepen such studies in meaningful yet still cost-effective ways have proven limited. The advent of RNAi, and particularly, the combination of HT-RNAi with HC readouts, now offers an important new tool in this endeavor.

The RNAi-based analysis of drug MoAs represents perhaps the most advanced and challenging application of RNAi technology in cultured cells today. With the right tools, infrastructure and know-how, as offered by Cenix, two main complementary types of RNAi experiments can be conducted to gain insights into drug MoAs: Comparative Screening and Modifier Screening.

The basic approach can be summarized as follows:

1. HC Assay Development: Design HC cell-based readouts to document drug-induced phenotypes in rich and quantitative manner, i.e. generating a drug phenotype profile. This step in itself may already offer important new insights into the drug's MoA.
   
2. Comparative RNAi screen: Apply the same HC cell-based readouts in the context of an RNAi screen to identify genes whose RNAi phenotype profile closely resembles the drug's profile. Of course, this requires careful optimization and extensive HT-RNAi experience to best address the inherent differences between the drug and RNAi modes of action, which yield completely different kinetic requirements for these assays. Such genes are most likely to be involved in the same pathway as the drug's target, or in a parallel pathway showing high relevance for the observed phenotypes. The strength of this link and the ability to narrow-down the field here depends heavily on the richness and precision of the profile, i.e. of the chosen readouts. Obviously, something as simple as a proliferation readout in itself offers insufficient classification potential (i.e. too many genes will give similar results) to be of much help in this context.
3. Modifier RNAi/drug screen: Apply the tried-and-true principles of enhancer/suppressor screening, which geneticists have been exploiting for decades to uncover entire pathways. Here, the effects on drug-induced phenotypes of pre-treating cells by RNAi to target "relevant genes" as defined above (or vice-versa) can reveal even more directly and precisely the exact drug MoA with relation to known molecular components of given pathways.