RESUMEN
Historically, sample management successfully focused on providing compound quality and tracking distribution within a diverse geographic. However, if a competitive advantage is to be delivered in a changing environment of outsourcing, efficiency and customer service must now improve or face reconstruction. The authors have used discrete event simulation to model the compound process from chemistry to assay and applied lean manufacturing techniques to analyze and improve these processes. In doing so, they identified a value-adding process time of just 11 min within a procedure that took days. Modeling also allowed the analysis of equipment and human resources necessary to complete the expected demand in an acceptable cycle time. Layout and location of sample management and screening departments are key in allowing process integration, creating rapid flow of work, and delivering these efficiencies. Following this analysis and minor process changes, the authors have demonstrated for 2 programs that solid compounds can be converted to assay-ready plates in less than 4 h. In addition, it is now possible to deliver assay data from these compounds within the same working day, allowing chemistry teams more flexibility and more time to execute the next chemistry round. Additional application of lean manufacturing principles has the potential to further decrease cycle times while using fewer resources.
Asunto(s)
Descubrimiento de Drogas , Industria Farmacéutica , Eficiencia Organizacional , Control de Calidad , Descubrimiento de Drogas/economía , Descubrimiento de Drogas/métodos , Industria Farmacéutica/economía , Industria Farmacéutica/métodos , Industria Farmacéutica/organización & administración , Competencia Económica/organización & administración , Humanos , Técnicas de Planificación , Factores de TiempoRESUMEN
Measurement of intracellular calcium release following agonist challenge within cells expressing the relevant membrane protein is a commonly used format to derive structure-activity relationship (SAR) data within a compound profiling assay. The Fluorometric Imaging Plate Reader (FLIPR) has become the gold standard for this purpose. FLIPR traditionally uses cells that are maintained in continuous culture for compound profiling of iterative chemistry campaigns. This supply dictates that assays can only be run on 4 of 5 weekdays, or alternative cell culture machinery is required such that plating can occur remotely at the weekend. The data reported here demonstrate that high-quality compound profiling data can be generated from the use of cryopreserved cells and that these cells can also be plated at various densities to generate equivalent data between 24 and 72 h post-plating. Hence, the authors report a method that allows data generation throughout the week and without the requirement of highly automated cell culture or continuous culture.
Asunto(s)
Calcio/análisis , Criopreservación , Fluorometría/métodos , Animales , Células CHO , Calcio/metabolismo , Cricetinae , Cricetulus , Fluorometría/instrumentación , Humanos , Relación Estructura-ActividadRESUMEN
Drug discovery has successfully exploited the superfamily of seven transmembrane receptors (7TMR), with over 35% of clinically marketed drugs targeting them. However, it is clear that there remains an undefined potential within this protein family for successful drugs of the future. The human genome sequencing project identified approximately 720 genes that belong to the 7TMR superfamily. Around half of these genes encode sensory receptors, while the other half are potential drug targets. Natural ligands have been identified for approximately 215 of these, leaving 155 receptors classified as orphan 7TMRs having no known ligand. Deorphanisation of these receptors by identification of natural ligands has been the traditional method enabling target validation by use of these ligands as tools to define biological relevance and disease association. Such ligands have been paired with their cognate receptor experimentally by screening of small molecule and peptide ligands, reverse pharmacology and the use of bioinformatics to predict candidate ligands. In this manuscript, we review the methodologies developed for the identification of ligands at orphan 7TMRs and exemplify these with case studies.