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A microplate-based method for the determination of association and dissociation rate values in high throughput using a kinetic probe competition assay (kPCA).
This issue includes articles that discuss the development of long-term 3D tissue cultures from human biopsy samples, the application of flow cytometry in drug discovery and automation for upstream processing in a biologics manufacturing environment. Also included are features on informatics, proteomics and CRISPR.
Scientists used a new screen to identify FAM72A as a cause of mutagenesis that affects antibody development in COVID-19 and cancer.
Transformational machine learning (TML) learns from multiple problems and improves performance while it learns, potentially accelerating drug discovery.
With an ever-increasing emphasis on minimising drug candidate attrition, scientists are focusing on target safety at earlier points in the research process. In this exclusive interview, Drug Target Review spoke with Dr Gordon Baxter, Chief Scientific Officer of Instem, to learn how target safety assessments can enable researchers to quickly…
The study paves the way for the construction of complex nanoscale computers for the prevention and treatment of cancer and other diseases.
Biologics solutions from discovery to manufacturing.
Scientists have used several machine learning models to predict bacterial gene exchange, which could reveal novel antibiotic targets.
A new computer-aided tool maps allosteric sites in G protein-coupled receptors to search for allosteric drugs to treat a range of diseases.
Scientists have identified potential cancer drugs to treat pulmonary hypertension using experimental and computational approaches.
Researchers have visualised SARS-CoV-2 protein dynamics using in silico methods. In this article, Navodya Roemer explains how a team from the University of Warwick developed a computational strategy that could assist scientists in the production of new treatments and drugs for COVID-19.
An MIT study has used the first statistical model to finely characterise how ketamine anaesthesia affects the brain, possibly improving patient outcomes.
View Drug Target Review's new infographic on the use of AI and informatics within early therapeutic development here.
Artificial intelligence was shown to predict the 3D shapes of RNA molecules, which could significantly advance RNA therapeutics.
An artificial intelligence technique can identify which neoantigens are recognised by the immune system, possibly improving cancer prognosis and treatment.
