The Drug Discovery and Development Subcommittee (D3SC) is part of IUPAC Division VII – Chemistry and Human Health and our mission is to facilitate the understanding and public awareness of the topic of Drug Discovery and Development and its international impact with an emphasis on medicinal chemistry.
The D3SC NEWSLETTER is a web-based offering complementary to IUPAC’s Chemistry International and focusing on advances in Drug Discovery & Development Chemistry. In addition to posting current information, we will invite Expert‘s Opinions to introduce and/or critically comment on new technologies, therapeutic modalities or new approaches in Drug Discovery and Development Chemistry. These brief articles will focus on the key advantages, current status of maturity and its impact on Drug Discovery & Development. In addition, the D3SC Newsletter will highlight news from IUPAC Division VII and its Subcommittees and alerts on conferences and key publications in the field.
The first edition [Sep 2021] of this newsletter will cover the topic of Artificial Intelligence in Drug Discovery & Development.
Recent and ongoing projects in D3SC
- Glossary of terms related to Drug Metabolism (P. Erhardt), Computational Chemistry (Y.C. Martin), Medicinal Chemistry (D.R. Buckle) and Combinatorial Chemistry (A. Ganesan)
- Training Courses in the field: Medicinal Chemistry in Drug Discovery and Development, India 2019 (Balu Balasubramanian & William Greenlee)
- IUPAC book series Successful Drug Discovery (Wiley Editor J. Fischer), last published: Volume 5
- Technical Report on The Emerging Problem of Psychoactive Substances by V. Abbate
and on Human Drug Metabolism database compiled by P. Erhardt
- A new project is analyzing drug failures in multiple sclerosis and the impact on drug discovery and development (M. Liebman).
- The D3SC is involved in the selection of the IUPAC Richter Prize Winner every two years for outstanding achievements in medicinal chemistry. The 2020 Richter Prize awardee is J. Macor (Sanofi) + Call for nominations (next deadline 15 Dec 2021).
- Winners of the 2021 IUPAC-Solvay International Award for Young Chemists
- Guiding principles for the regulatory evaluation of nano-pesticides
- Climate Change 2021: The Physical Science Basis
- Terminology and the Naming of Conjugates based on Polymers or other Substrates
Upcoming Conferences related to Drug Discovery and Development
- Drug Discovery Chemistry (18 Apr 2022)
- 37th ACS National Medicinal Chemistry Symposium (26 June 2022)
- EFMC Advances in Synthetic and Medicinal Chemistry (3 Sep 2023)
- XXVII EFMC International Symposium on Medicinal Chemistry (4 Sept 2022)
- Other calendars from drughunter | from 10times | from efmc
All comments to content and suggestions for improving the NEWSLETTER are welcome from the editors, Michael Liebman <Michael.email@example.com>, Gerd Schnorrenberg <firstname.lastname@example.org>, and Balu Balasubramanian <Neel.email@example.com>
Feature (full text to appear in Chemistry International Jan 2022)
The Role of Artificial Intelligence in Drug Discovery and Development
Artificial Intelligence (AI) is an exciting growing field. Due to the high and growing number of data, the comprehensive evaluation of information behind data makes AI tools indispensable. In Drug Discovery and Development the application of AI has become important to accelerate progress and enhance decision making in many fields and disciplines of medicinal chemistry, upscaling, molecular and cell biology, pharmacology, pharmacokinetics, formulation development and toxicology. In clinical testing AI has high importance in increasing success rates by enhancing trial design (biomarkers, efficacy parameters, dose selection, trial duration), selection of the target patient population, patient stratification and evaluation of patient samples. The increasing relevance of AI in drug discovery and development is reflected by the growing number of start-up companies specialized in this field, the growing number of collaborations from Pharma with AI platforms, and the high number of articles and reviews reporting current applications, their success and limitations.
In the first part of this article, Michael Liebman focuses on a general overview on AI in drug discovery and development; the second part provided by Yann Gasthon-Mathé and his colleagues from IKTOS (France)–an AI company specialized in drug discovery and development-related AI applications, highlights key points to succeed in AI drug discovery projects.
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