Learning Medicinal Chemistry Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Rules from Cross-Company Matched Molecular Pairs Analysis (MMPA).

The first large scale analysis of in vitro absorption, distribution, metabolism, excretion, and toxicity (ADMET) data shared across multiple major pharma has been performed. Using advanced matched molecular pair analysis (MMPA), we combined data from three pharmaceutical companies and generated ADMET rules, avoiding the need to disclose the full chemical structures. On top of the very large exchange of knowledge, all companies involved synergistically gained approximately 20% more rules from the shared transformations. There is good quantitative agreement between the rules based on shared data compared to both individual companies' rules and rules published in the literature. Known correlations between log  D, solubility, in vitro clearance, and plasma protein binding also hold in transformation space, but there are also interesting exceptions. Data pools such as this allow focusing on particular functional groups and characterizing their ADMET profile. Finally the role of a corpus of robustly tested medicinal chemistry knowledge in the training of medicinal chemistry is discussed.

Synthesis and structure-activity relationships of thieno[2,3-b]pyrroles as antagonists of the GnRH receptor.

A new class of small-molecule GnRH antagonists, the thieno[2,3-b]pyrroles, was designed. Herein, the synthesis and structure-activity relationships are described. Substitution at the C4 position was investigated; during this study, it was observed that introducing piperazines and piperidines improved the physical properties of the compounds while retaining good in vitro potency. This exploration led to the discovery of amidopiperidines with improved pharmacokinetic properties.

'Big data' in pharmaceutical science: challenges and opportunities.

Future Medicinal Chemistry invited a selection of experts to express their views on the current impact of big data in drug discovery and design, as well as speculate on future developments in the field. The topics discussed include the challenges of implementing big data technologies, maintaining the quality and privacy of data sets, and how the industry will need to adapt to welcome the big data era. Their enlightening responses provide a snapshot of the many and varied contributions being made by big data to the advancement of pharmaceutical science.

Highly diastereoselective radical cyclisations of chiral sulfinimines.

Chiral amines are formed by the highly diastereoselective intramolecular addition of alkyl and aryl radicals onto chiral mesityl sulfinimines.