Next-Generation Phenotypic Screening in Early Drug Discovery for Infectious Diseases. Issue 7 (July 2019) - Aulner, Nathalie; Danckaert, Anne; Ihm, JongEun; Shum, David; Shorte, Spencer L.
Abstract : Cell-based phenotypic screening has proven to be valuable, notably in recapitulating relevant biological conditions, for example, the host cell/pathogen niche. However, the corresponding methodological complexity is not readily compatible with high-throughput pipelines, and fails to inform either molecular target or mechanism of action, which frustrates conventional drug-discovery roadmaps. We review the state-of-the-art and emerging technologies that suggest new strategies for harnessing value from the complexity of phenotypic screening and augmenting powerful utility for translational drug discovery. Advances in cellular, molecular, and bioinformatics technologies are converging at a cutting edge where the complexity of phenotypic screening may no longer be considered a hinderance but rather a catalyst to chemotherapeutic discovery for infectious diseases. Highlights: The conventional wisdom of the drug-development roadmap strategy that seeks to establish therapeutic efficacy based upon knowing the molecular target and mechanism of action is being challenged. Cell-based phenotypic methods are allowing the high-fidelity host-cell/pathogen niche to be used for high-throughput image-based cell analysis for drug screening. Phenotypic screening recapitulates biological relevance at the heart of drug-screening campaigns and is becoming a primary determinate to improved therapeutic outcome. Emerging methods using transcript quantification, public databases (chem/bioactivity profiles, ontologies, image-based screening results), combined with machine-learning tools, are providing ground-breaking new and alternative screening strategies by augmenting phenotypic screening results. Empirical drug discovery refers to the emergent paradigm that harnesses the inherent complementarity of phenotypic and target-based screening strategies and augments predictivity of chemotherapeutic efficacy.