This is the time of year when people are gearing up for festivities and tidying up loose ends before resolving to get back to productive work and improving on personal and professional aims and targets. It’s no different at Drug Discovery Today and I hope that we can continue to provide evermore interesting and stimulating articles as we move into 2019. It is perhaps no surprise, therefore, that I use the opportunity of the final Editor’s Choice newsletter of 2018 to reflect back on the successes of the year. In order to reduce the possibility of personal bias when making this selection, I have been guided by Plum metrics, which can give an assessment of global impact of articles based upon citations, downloads, reads, saves and mentions in social media. Something you should have a look at (if you aren’t familiar with it) the next time you look for articles in Science Direct.
In the first article in this month’s offering, we touch upon the field of machine learning and its application to drug discovery. This is a relatively general article on chemoinformatics “Machine learning in chemoinformatics and drug discovery” from Yu-Chen Lo, Stefano E. Rensi, Wen Torng and Russ B. Altman of Stanford University, California, USA. It is a particularly useful introduction to the field for those interested in an introduction to the field and examines the basic principles and highlights them with some case studies. This is a great gatekeeper article for those wishing to get a good understanding of where this approach is currently heading.
The second article in this current series is the article from Mu-Lu Wu, Dinah B. Aziz, Véronique Dartois and Thomas Dick, entitled “NTM drug discovery: status, gaps and the way forward”, which, unsurprisingly, discusses the status quo of drug discovery related to the treatment of non-tuberculous mycobacteria. In addition to the current status, they highlight knowledge gaps and factors affecting the development of new drugs to address this approach and strategies for future development.
The next article, “The rise of deep learning in drug discovery” from Hongming Chen, Ola Engkvist, Yinhai Wang, Marcus Olivecrona and Thomas Blaschke from AstraZeneca touches upon the great and increasing success of deep learning techniques over the last 10 years. They discuss the initial applications of the technique to the Pharmaceutical Industry and its current value in the prediction of bioactivity, molecular design and synthetic routes amongst others.
Finally, we offer an article on what is becoming an ever more interesting field that has attracted significant coverage in scientific and popular press recently. The article discusses potential issues with adverse effects related to CAR T cell therapies. The paper, by Ping-Pin Zheng, Johan M. Kros and Jin Li of the Netherlands and Shanghai, highlights the potential for adverse reactions from currently marketed chimeric antigen receptor T cell therapies.
At this time of year, I would like to offer my thanks and best wishes to all of our contributors, as either authors or reviewers and to the Editorial staff at Elsevier who have been essential in the production of such high quality offerings this year. I also offer my best wishes to all of our readers and hope for a prosperous and healthy Christmas period and an equally prosperous New Year. Here’s to a brilliant 2019 for everyone and I wish you all every success, personal and professional.
Steve Carney was born in Liverpool, England and studied Biochemistry at Liverpool University, obtaining a BSc.(Hons) and then read for a PhD on the Biochemistry and Pathology of Connective Tissue Diseases in Manchester University, in the Departments of Medical Biochemistry and Histopathology. On completion of his PhD he moved to the Kennedy Institute of Rheumatology, London, where he worked with Professor Helen Muir FRS and Professor Tim Hardingham, on the biochemistry of experimental Osteoarthritis. He joined Eli Lilly and Co. and held a number of positions in Biology R&D, initially in the Connective Tissue Department, but latterly in the Neuroscience Department. He left Lilly to take up his present position as Managing Editor, Drug Discovery Today, at Elsevier. Currently, he also holds an honorary lectureship in Drug Discovery at the University of Surrey, UK. He has authored over 50 articles in peer-reviewed journals, written several book chapters and has held a number of patents. On the media front, Dr. Carney has been busy on some hush-hush projects that will be reported on later in the year.