Impact of the COVID-19 pandemic on the spontaneous reporting and signal detection of adverse drug events.

External factors severely affecting in a short period of time the spontaneous reporting of adverse events (AEs) can significantly impact drug safety signal detection. Coronavirus disease 2019 (COVID-19) represented an enormous challenge for health systems, with over 767 million cases and massive vaccination campaigns involving over 70% of the worldwide population. This study investigates the potential masking effect on certain AEs caused by the substantial increase in reports solely related to COVID-19 vaccines within various spontaneous reporting systems (SRSs).

Comparison of Zebrafish Larvae and hiPSC Cardiomyocytes for Predicting Drug-Induced Cardiotoxicity in Humans.

Cardiovascular drug toxicity is responsible for 17% of drug withdrawals in clinical phases, half of post-marketed drug withdrawals and remains an important adverse effect of several marketed drugs. Early assessment of drug-induced cardiovascular toxicity is mandatory and typically done in cellular systems and mammals. Current in vitro screening methods allow high-throughput but are biologically reductionist.

Biological substantiation of antipsychotic-associated pneumonia: Systematic literature review and computational analyses.

Introduction: Antipsychotic (AP) safety has been widely investigated. However, mechanisms underlying AP-associated pneumonia are not well-defined.

Aim: The aim of this study was to investigate the known mechanisms of AP-associated pneumonia through a systematic literature review, confirm these mechanisms using an independent data source on drug targets and attempt to identify novel AP drug targets potentially linked to pneumonia.

The In Vitro Pharmacological Profile of Drugs as a Proxy Indicator of Potential In Vivo Organ Toxicities.

The potential of a drug to cause certain organ toxicities is somehow implicitly contained in its full pharmacological profile, provided the drug reaches and accumulates at the various organs where the different interacting proteins in its profile, both targets and off-targets, are expressed. Under this assumption, a computational approach was implemented to obtain a projected anatomical profile of a drug from its in vitro pharmacological profile linked to protein expression data across 47 organs. It was observed that the anatomical profiles obtained when using only the known primary targets of the drugs reflected roughly the intended organ targets.

Large-Scale Predictive Drug Safety: From Structural Alerts to Biological Mechanisms.

The recent explosion of data linking drugs, proteins, and pathways with safety events has promoted the development of integrative systems approaches to large-scale predictive drug safety. The added value of such approaches is that, beyond the traditional identification of potentially labile chemical fragments for selected toxicity end points, they have the potential to provide mechanistic insights for a much larger and diverse set of safety events in a statistically sound nonsupervised manner, based on the similarity to drug classes, the interaction with secondary targets, and the interference with biological pathways. The combined identification of chemical and biological hazards enhances our ability to assess the safety risk of bioactive small molecules with higher confidence than that using structural alerts only.

Automatic filtering and substantiation of drug safety signals.

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it.

Chemical probes for biological systems.

According to the latest definition in use by the NIH Molecular Libraries Screening Centers Network, a compound to be nominated as a chemical probe should have, on the one hand, an affinity below 100 nM for the primary target and, on the other hand, at least tenfold selectivity against related targets. Taking drugs as the ultimate product of an affinity and selectivity optimization process, it is found that only 14.4% of them would actually qualify as chemical probes under those criteria.

Ligand-based approaches to in silico pharmacology.

The development of computational methods that can estimate the various pharmacodynamic and pharmacokinetic parameters that characterise the interaction of drugs with biological systems has been a highly pursued objective over the last 50 years. Among all, methods based on ligand information have emerged as simple, yet highly efficient, approaches to in silico pharmacology. With the recent impact on the identification of new targets for known drugs, they are again the focus of attention in chemical biology and drug discovery.

Anticipating drug side effects by comparative pharmacology.

Importance Of The Field: Anticipating the likely side effect profile of drugs is an aspect of key importance in current drug discovery, development and marketing. It was recently shown that drug pairs having similar side effect profiles had also affinity for a common target. Acknowledging that most drugs have a rich polypharmacology, we provide proof that drugs related by side effect similarity have in fact affinities for multiple common targets beyond their primary targets and set the basis for the use of comparative pharmacology to anticipate drug side effects.

iPHACE: integrative navigation in pharmacological space.

Summary: The increasing availability of experimentally determined binding affinities for drugs on multiple protein targets requires the design of specific mining and visualization tools that graphically integrate chemical and biological data in an efficient environment. With this aim, we developed iPHACE, an integrative web-based tool to navigate in the pharmacological space defined by small molecule drugs contained in the IUPHAR-DB, with additional interactions present in PDSP. Extending beyond traditional querying and filtering tools, iPHACE offers a means to extract knowledge from the target profile of drugs as well as from the drug profile of protein targets.

FCP: functional coverage of the proteome by structures.

Motivation: Tools and resources for translating the remarkable growth witnessed in recent years in the number of protein structures determined experimentally into actual gain in the functional coverage of the proteome are becoming increasingly necessary. We introduce FCP, a publicly accessible web tool dedicated to analyzing the current state and trends of the population of structures within protein families. FCP offers both graphical and quantitative data on the degree of functional coverage of enzymes and nuclear receptors by existing structures, as well as on the bias observed in the distribution of structures along their respective functional classification schemes.

Chemical and biological profiling of an annotated compound library directed to the nuclear receptor family.

Nuclear receptors form a family of ligand-activated transcription factors that regulate a wide variety of biological processes and are thus generally considered relevant targets in drug discovery. We have constructed an annotated compound library directed to nuclear receptors (NRacl) as a means for integrating the chemical and biological data being generated within this family. Special care has been put in the appropriate storage of annotations by using hierarchical classification schemes for both molecules and nuclear receptors, which takes the ability to extract knowledge from annotated compound libraries to another level.