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Today we are beginning to realise that lipids have been inadequately represented in biological and medical research. For decades, studies in the fields of DNA and proteins have been pushed but despite these adverse conditions, lipid research has made pioneering discoveries over the course of the last seven years. These…
Osteoarthritis (OA) is a painful and debilitating disease of articular joints.1,2 Its clinical prevalence is as high as 21.6 percent of the population in the United States,3 which constitutes direct health costs of over 80 billion US dollars annually.4
Automation offers a choice of powerful ways to design and execute high-quality laboratory research. The use of lab automation is now pervasive in biomedical labs, offering versatile platforms on which to perform an ever‑expanding array of tasks free of human errors, and a unique means to address the problems associated…
Flow chemistry is on the rise thanks to the commercial availability of benchtop continuous flow systems that has driven widespread adoption of the technique across a broad range of applications in both academia and industry. In particular, flow chemistry is delivering significant benefits in the area of drug discovery and…
Over the past 30 years, one strategy the pharmaceutical industry has adopted in the drug discovery process has been to “fail early, fail often”.1,2 As most molecules in the early stages of drug discovery will have sub-optimal characteristics, significant modification is necessary to improve their properties.
Data drives drug discovery, yet it continues to be among the biggest challenges faced by the industry.1 Experiments are often not repeatable and data interpretation is subject to the biases and limitations of human beings.
Cell line development is a major step for examining the efficiency of drug discovery, toxicity and in vitro testing. It reduces time, effort and cost, which minimises the chance of research drugs failing at the clinical trial stage. This stage involves the production of recombinant proteins such as monoclonal antibodies,…
In this In-Depth Focus: realising the promise of laboratory automation in biomedical research, drug discovery from the age of information to the age of intelligence, and transforming drug discovery, development and delivery with flow chemistry.
In this In-Depth Focus: AI-driven automated chemistry as a tool to accelerate drug discovery, and a look at network-driven drug discovery
In this In-Depth Focus: the importance of characterising chemical starting points of drugs using appropriate in vitro ADME-toxicity assays, and why do we have no effective treatments for osteoarthritis?
In this issue: AI-driven automated chemistry as a tool to accelerate drug discovery processes, the shifting landscape of immuno-oncology, and how lipid molecules provide an insight into biological research.
Target-driven drug discovery, in which the starting point is a specific protein target hypothesised to play an important role in disease, has been the dominant paradigm for the last few decades. However, phenotypic-driven drug discovery, which does not rely on a specific target hypothesis, is starting to regain traction for…
Small molecule drug discovery has long been the domain of pharmaceutical companies, and that’s not likely to change anytime soon. But there’s a cadre of universities and nonprofit research institutes that have embraced drug development at its earliest stages, in some cases identifying and optimising compounds that target possible disease-driving…
Immunotherapy and targeted treatments, including targeted chemotherapy, continue to show great potential in cancer care. Future steps in their development will involve improving their ability to treat a wider range of cancers and a broader cross-section of the patient population, especially those for whom current treatments have shown limited efficacy...
Drug discovery is still hampered by the routine use of cell-based models that often fail to recapitulate the truly relevant biological complexity of the corresponding disease. Just moving from two- (2D) towards three-dimensional (3D) cell culture model systems like spheroids and organoids is not enough to generate truly representative and…
