Aspects Of Drug Research Research Articles

Current situation and development trend of digital traditional Chinese medicine pharmacy

The 21st century is a highly information-driven era, and traditional Chinese medicine(TCM) pharmacy is also moving towards digitization and informatization. New technologies such as artificial intelligence and big data with information technology as the core are being integrated into various aspects of drug research, manufacturing, evaluation, and application, promoting interaction between these stages and improving the quality and efficiency of TCM preparations. This, in turn, provides better healthcare services to the general population. The deep integration of emerging technologies such as artificial intelligence, big data, and cloud computing with the TCM pharmaceutical industry will innovate TCM pharmaceutical technology, accelerate the research and industrialization process of TCM pharmacy, provide cutting-edge technological support to the global scientific community, boost the efficiency of the TCM industry, and promote economic and social development. Drawing from recent developments in TCM pharmacy in China, this paper discussed the current research status and future trends in digital TCM pharmacy, aiming to provide a reference for future research in this field.

The 2016 database issue of Nucleic Acids Research and an updated molecular biology database collection.

The 2016 Database Issue of Nucleic Acids Research starts with overviews of the resources provided by three major bioinformatics centers, the U.S. National Center for Biotechnology Information (NCBI), the European Bioinformatics Institute (EMBL-EBI) and Swiss Institute for Bioinformatics (SIB). Also included are descriptions of 62 new databases and updates on 95 databases that have been previously featured in NAR plus 17 previously described elsewhere. A number of papers in this issue deal with resources on nucleic acids, including various kinds of non-coding RNAs and their interactions, molecular dynamics simulations of nucleic acid structure, and two databases of super-enhancers. The protein database section features important updates on the EBI's Pfam, PDBe and PRIDE databases, as well as a variety of resources on pathways, metabolomics and metabolic modeling. This issue also includes updates on popular metagenomics resources, such as MG-RAST, EBI Metagenomics, and probeBASE, as well as a newly compiled Human Pan-Microbe Communities database. A significant fraction of the new and updated databases are dedicated to the genetic basis of disease, primarily cancer, and various aspects of drug research, including resources for patented drugs, their side effects, withdrawn drugs, and potential drug targets. A further six papers present updated databases of various antimicrobial and anticancer peptides. The entire Database Issue is freely available online on the Nucleic Acids Research website (http://nar.oxfordjournals.org/). The NAR online Molecular Biology Database Collection, http://www.oxfordjournals.org/nar/database/c/, has been updated with the addition of 88 new resources and removal of 23 obsolete websites, which brought the current listing to 1685 databases.

Leveraging systems biology approaches in clinical pharmacology

Computational modeling has been adopted in all aspects of drug research and development, from the early phases of target identification and drug discovery to the late-stage clinical trials. The different questions addressed during each stage of drug R&D has led to the emergence of different modeling methodologies. In the research phase, systems biology couples experimental data with elaborate computational modeling techniques to capture lifecycle and effector cellular functions (e.g. metabolism, signaling, transcription regulation, protein synthesis and interaction) and integrates them in quantitative models. These models are subsequently used in various ways, i.e. to identify new targets, generate testable hypotheses, gain insights on the drug's mode of action (MOA), translate preclinical findings, and assess the potential of clinical drug efficacy and toxicity. In the development phase, pharmacokinetic/pharmacodynamic (PK/PD) modeling is the established way to determine safe and efficacious doses for testing at increasingly larger, and more pertinent to the target indication, cohorts of subjects. First, the relationship between drug input and its concentration in plasma is established. Second, the relationship between this concentration and desired or undesired PD responses is ascertained. Recognizing that the interface of systems biology with PK/PD will facilitate drug development, systems pharmacology came into existence, combining methods from PK/PD modeling and systems engineering explicitly to account for the implicated mechanisms of the target system in the study of drug–target interactions. Herein, a number of popular system biology methodologies are discussed, which could be leveraged within a systems pharmacology framework to address major issues in drug development.

The Quest for Medicines, a Grand Challenge in the Twenty-First Century

The Quest for Medicines, a Grand Challenge in the Twenty-First Century