The pharmaceutical industry embraced “target based screening” as a means to identify increased numbers of therapeutic candidates (hits), by performing high throughput screening of large compound libraries. This approach has one important shortcoming; it does not allow for characterization of these “hits” within the context of the complex biological networks within the cell.
OFF-TARGET BINDING EFFECTS:
Even approved drugs, on average,
interact with SIX other known
molecular targets 1
Target based drug discovery will always be challenged when identification of off-target binding heterogeneity is such an important part of the drug discovery process. Approaches that interrogate multiple biological pathways and effects simultaneously at a cellular level, such as technologies integrating phenotypic analysis, can add significant value to the characterization of compounds earlier in the discovery process.
Phenotypic screening in drug discovery can allow for agnostic and simultaneous interrogation of biologically relevant pathways and physiological processes, across a variety of cell models, to assess the risk of off-target binding effects leading to toxicity, while also contributing to a mechanistic hypothesis.
• OUR DIFFERENCE •
AsedaSciences® utilizes flow cytometry to develop multiplexed phenotypic screening applications that allow for the understanding of how integrated biological networks, targets and signaling pathways interact to define a specific biological response. These applications are offered as a service – clients provide their compounds to us for testing and analysis.
We perform highly reproducible, multi-parametric, high throughput, human cell-based phenotypic screens which are analyzed using flow cytometry. Multiple physiological and biological parameters are analyzed simultaneously generating population distribution data for each compound condition (e.g., compound concentration or time). This produces a rich data set for classification of drug effect on a population of approximately 200,000 cells per compound, allowing for precise quantification of heterogeneity, such as the presence of small sub-populations and rare events.
We carefully choose combinations of parameters to allow for the observation of multiple drug effects simultaneously. The applications have been precisely developed and automated to ensure high reproducibility, which is critical for comparison of compound effects. The combination of dose response, multiple parameters per well and a sensitive cell model allows for creation of a unique fingerprint for each compound, which can then be used for similarity analysis within a database.
We concurrently designed an operator-independent algorithm for the comparison of multi-parametric compound fingerprints. It embraces the heterogeneity of the cell population analyzed and can therefore classify drugs in a manner that no univariate, or combination of univariate approaches, can achieve. We can search for specific fingerprints, such as mitochondrial toxins or, similarly, you can compare your “unknown” compounds to our database containing a selection of toxins and on-market therapeutics.
1) Lee et al. Modern Phenotypic Drug Discovery is a Viable, Neoclassic Pharma Strategy. Journal of Medicinal Chemistry. 55. 2012; 4527-4538