There is a growing consensus that Drug Repurposing, Repositioning and Rescue (DRPx) impacts all stakeholders involved in the therapeutic drug sector.
Recent advances of single cell technologies are facilitating the opportunity to discern biological insights within individual cells and providing a means to reveal previously hidden relationships between individual cells within a population.
The study of rare cell populations is important to advance medical diagnostics and therapeutics. For many clinical studies, rare cell counts promise to provide valuable alternate end points; examples are circulating tumour cells in peripheral blood, tumour stem cells, endothelial cells in blood, hematopoietic progenitor cells and their subpopulations, antigen specific T-cells and foetal cells in maternal circulation.
In the last few years, technological advancements in the life sciences have changed many ways in which we think about research. Next-generation sequencing, qPCR and microRNA offer new avenues to ask and answer research questions in more detail and in less time. However, much of the effort today centres around data gathering, and many researchers are realising that collecting massive quantities of data is not the same as biological discovery.
Understanding the function of a protein in the context of normal and abnormal cellular processes requires a comprehensive knowledge not only of its regulation but also of its role in signalling and metabolic networks in the cell. Malfunctioning signalling pathways can lead to a variety of pathologies, hence why they are particularly investigated in the oncology/cancer disease area.
Bearing in mind the cost and time required to conduct a screening campaign, it is of paramount importance that screening laboratory scientists process and analyse screen data as carefully and consistently as possible. This paper argues that data analysis software that is modular, process-based and supports visualisation and flexible result generation is essential.
Affinity proteomic methods can translate genomic data into validated targets for drug discovery. Baits such as tagged gene product or small molecules obtained from cell-based assays are used to purify interacting proteins. These proteins are then identified by high sensitivity, high throughput mass spectrometric techniques. Successful examples of this novel method are discussed in this article, such as the discovery of key components of the prototypical NF-B inflammation pathway, which are now in drug screening programs.
The coupling of High Throughput co-structure analysis with focused library generation is not only proving a powerful general tool in lead optimisation but also increasing the probability of successful discovery of high quality oral development compounds for targets that have been quite difficult for the pharmaceutical industry.
It is clear that gene expression profiling systems have a role to play in many facets of drug discovery and development but several questions remain.We take a look at the use of DNA microarray for gene expression or expression profiling and how DNA chips are used for drug discovery and development as a whole.
The number of high content screens will increase by 50% over the coming year; signal pathway analysis was seen as the most relevant high content screening (HCS) application; with greatest interest in applying HCS coming from oncology groups. Novel reagent/probes and pathway analysis developments were considered as the tools and technology developments which will impact most on HCS over the next few years.These were the main findings of the recent market survey reviewed in this article and are used as a setting to discuss some of the latest technologies now being applied to HCS.
In the modern drug discovery industry, the development of cell based assays for High Content Screening (HCS) is necessary for the efficient screening of compound libraries. Until recently, assays for the analysis of chemotactic responses were not amenable for use in high content cell-based assay approaches. However, recent developments have enabled the investigation of chemotactic responses to be applied in cell-based High Throughput Screening (HTS) assays.
Cost is now a key driver for pharmaceutical companies and in many respects shapes the capital, revenue and resource decisions that have to be made during the drug discovery process. Where companies are resource rich, the need for fully automated screening platforms is reduced and workstation-based systems tend to be more abundant.
Drug discovery currently focuses on targeted approaches, relying on validation of the target as a disease driver. However, the underlying biological complexity of disease often frustrates these attempts at therapeutic intervention, resulting in high failure rates due to lack of efficacy.