The strength of OcellO’s 3D screening platform lies within the multi-dimensional, multi-parametric profiling of the microtissues by using our proprietary software toolset. By combining up to 900 different feature measurements, we can distinguish within one single assay between multiple different compound targets and address their specificity, mode of action and off-target effects.

Output

  • Dose-response curves
  • Compound classification
  • Insight into target specificity & MOA
  • Polypharmacology

Example: different compounds project differently in phenotypic space
These anti-cancer compounds are all ‘hits’ in viability assays but actually induce very different phenotypes. Compounds inducing specific phenotypes, such as reduced invasion or growth, can be identified and selected. Compounds that target the same pathway induce the same phenotype.

Different compounds phenotypic space

Zi et al PlosOne 2014

Using this approach, we can classify compounds based on the phenotype they induce, which correlates with the compound class, as is shown below:

classifying on biological action

Phenotypic profiling allows compounds to be compared and classified. For example, compounds that are most similar to a ‘standard of care’ reference compound or compounds within a series of analogs or derivatives.   This approach allows “best-in-class” compounds to be selected. In the example below, a library of 240 compounds was screened to identify molecules that inhibited invasive breast cancer with a similar response to a low-dose of dasatinib.  Of the compounds that gave the most similar phenotype, many were other Src family kinase inhibitors and dasatanib analogs, as expected.  Novel compounds were also identified, and compounds that inhibited non-Src targets, identifying potential new targets for disease.

Structure-phenotype-activity