Journal of chemical information and modeling
Feb 21, 2019
We describe a novel deep learning neural network method and its application to impute assay pIC values. Unlike conventional machine learning approaches, this method is trained on sparse bioactivity data as input, typical of that found in public and c...
European journal of hospital pharmacy : science and practice
Feb 4, 2019
OBJECTIVES: To design and execute a comprehensive microbiological validation protocol to assess a brand-new sterile compounding robot in a hospital pharmacy environment, according to ISO and EU GMP standards.
Journal of chemical information and modeling
Jan 25, 2019
Assay interference caused by small molecules continues to pose a significant challenge for early drug discovery. A number of rule-based and similarity-based approaches have been derived that allow the flagging of potentially "badly behaving compounds...
Journal of chemical information and modeling
Jan 24, 2019
Successful drug discovery projects require control and optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety. While volume and chemotype coverage of public and corporate ADME-Tox (absorption, distribution, excr...
In this review, we present important, recent developments in the computational prediction of cytochrome P450 (CYP) metabolism in the context of drug discovery. We discuss in silico models for the various aspects of CYP metabolism prediction, includin...
Journal of chemical information and modeling
Jan 11, 2019
Deep learning has drawn significant attention in different areas including drug discovery. It has been proposed that it could outperform other machine learning algorithms, especially with big data sets. In the field of pharmaceutical industry, machin...
Database : the journal of biological databases and curation
Jan 1, 2019
Information about the interactions between chemical compounds and proteins is indispensable for understanding the regulation of biological processes and the development of therapeutic drugs. Manually extracting such information from biomedical litera...
BACKGROUND: Previous studies have suggested deep learning to be a highly effective approach for screening lead compounds for new drugs. Several deep learning models have been developed by addressing the use of various kinds of fingerprints and graph ...
BACKGROUND: Cyclic peptide-based drug discovery is attracting increasing interest owing to its potential to avoid target protein depletion. In drug discovery, it is important to maintain the biostability of a drug within the proper range. Plasma prot...
Journal of chemical information and modeling
Dec 21, 2018
A key component of automated molecular design is the generation of compound ideas for subsequent filtering and assessment. Recently deep learning approaches have been explored as alternatives to traditional de novo molecular design techniques. Deep l...