Expert view: Toward physiological relevance in drug discovery and development
Physiologically relevant screening models have become increasingly important in assay development and the screening of drug candidates.
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Physiologically relevant screening models have become increasingly important in assay development and the screening of drug candidates.
Declining R&D productivity is a key challenge in the pharmaceutical industry. To increase the success rate of candidate drugs entering the clinical phase, companies must address the early stages of drug discovery.
Predictiveness is one of the key factors for success in the drug discovery workflow. Many compounds fail at late stages due to lack of predictive data or the discovery of unwanted side effects.
In this issue: how lab automation has accelerated pharmaceutical research by simplifying operations, reducing manual tasks and increasing the efficiency, quality and reproducibility of results.
In this In-Depth Focus: enabling research on understudied and unstudied targets, and using multi-omics data to detail drug responses in the human metabolic network.
In this In-Depth Focus: high throughput strategies for antibody library screening, and the latest in vitro 3D cell and tissue culture model systems in HTS.
In this issue: how customised cell engineering advances immunotherapy, how insights into auto-immunity are providing new opportunities for immune-oncology, and advances in lab automation and robotics are accelerating the pace of antimicrobial therapy.
From the early use of Hansch parameters and Topliss Trees to today’s computational structure–activity techniques, medicinal chemists have long sought to rationalise drug design to find the quickest and most resource-efficient route to market. But while modern strategies are more reliant on statistical algorithms and vast data libraries, these founding…
A new race is well underway involving big pharma and big data companies to see who can most effectively mine the new massive data using artificial intelligence (AI). The aim: reducing costs by using targeted in silico analysis, reducing in vitro and in vivo screening, and reviewing huge quantities of…
Proteogenomics is the systematic and comprehensive integration of proteomics with genomics and transcriptomics. Proteogenomics is opening new hallmarks in biomedical research. Recently, several studies have demonstrated the relevance of proteogenomics in cancer research. This article provides a brief review of the advantages of proteogenomics in precision medicine.
Failing early in drug discovery is the primary driving force for new techniques in the hit-to-lead phase.
Neglected tropical diseases (NTD) affect more than one billion people and new targets and drugs are needed to tackle these infections. The multi-disciplinary NMTrypI consortium has identified a number of different compound classes which could be effective against these diseases. This article reviews some of these compounds...
Efforts to develop new medicines for diseases of the developing world (DDW) have been somewhat fragmented in the past and progress has been limited, despite considerable investment. Public-private partnership (PPP) is becoming an essential model for research in neglected disease areas. However, collaboration on this scale presents unique challenges, some…
Mitochondrial DNA (mtDNA) mutations cause severe disorders that are untreatable and mostly affect the nervous system. The difficulty in funding therapies may also be explained by the lack of viable modelling systems...
Hits identified in high-throughput screens are evaluated within the hit-to-lead phase of drug discovery, where they undergo an iterative optimisation process employing a variety of techniques to identify promising lead compounds to move forward to the lead optimisation phase.