In light of the high failure rate of compounds when they are subjected to clinical testing, we are seeing a renaissance in phenotypic screening in drug discovery. However, most phenotypic screening is based on the use of cellular assays and here we debate the advantages and disadvantages of single-cell versus 3D multi-cell analyses.
Large pharmaceutical companies have struggled to efficiently implement tools, technologies and platforms into their drug discovery and development (DDD) programmes.
The serial dilution method is standard practice in the preparation of doseresponse series for IC50 determination. However, it is well recognised that inadequacies in the liquid handling or mixing technique will affect the dilution ratio and hence the compound concentration and any errors will be compounded during each successive serial dilution, mix and transfer.
Microfluidics platforms that harness picodroplet technology (picolitre volume aqueous droplets in stabilised oil emulsions) are unlocking the potential of single cell analysis to enable exciting new discoveries and advances with the potential to transform scientific research, drug development and precision medicine.
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.
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.
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.
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.
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.
There is a growing pressure in todays climate for pharmaceutical companies to find tomorrows wonder drugs and dominate the major market segments. Recently, they have also been under attack for poor research productivity, for failures in drug safety and for off-label marketing. The use of visual analysis could do much to improve their performance in research and across all areas of activity.
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.