A preclinical secondary pharmacology resource illuminates target-adverse drug reaction associations of marketed drugs.

In vitro secondary pharmacology assays are an important tool for predicting clinical adverse drug reactions (ADRs) of investigational drugs. We created the Secondary Pharmacology Database (SPD) by testing 1958 drugs using 200 assays to validate target-ADR associations. Compared to public and subscription resources, 95% of all and 36% of active (AC50 < 1 µM) results are unique to SPD, with bias towards higher activity in public resources.

Identifying multiscale translational safety biomarkers using a network-based systems approach.

Animal testing is the current standard for drug and chemicals safety assessment, but hazards translation to human is uncertain. Human models can address the species translation but might not replicate complexity. Herein, we propose a network-based method addressing these translational multiscale problems that derives liver injury biomarkers applicable to human early safety screening.

Neurofilament light chain and dorsal root ganglia injury after adeno-associated virus 9 gene therapy in nonhuman primates.

In nonhuman primates (NHPs), adeno-associated virus serotype 9 (AAV9) vectorized gene therapy can cause asymptomatic microscopic injury to dorsal root ganglia (DRG) and trigeminal ganglia (TG) somatosensory neurons, causing neurofilament light chain (NfL) to diffuse into cerebrospinal fluid (CSF) and blood. Data from 260 cynomolgus macaques administered vehicle or AAV9 vectors (intrathecally or intravenously) were analyzed to investigate NfL as a soluble biomarker for monitoring DRG/TG microscopic findings. The incidence of key DRG/TG findings with AAV9 vectors was 78% (maximum histopathology severity, moderate) at 2-12 weeks after the dose.

"3D, human renal proximal tubule (RPTEC-TERT1) organoids 'tubuloids' for translatable evaluation of nephrotoxins in high-throughput".

The importance of human cell-based in vitro tools to drug development that are robust, accurate, and predictive cannot be understated. There has been significant effort in recent years to develop such platforms, with increased interest in 3D models that can recapitulate key aspects of biology that 2D models might not be able to deliver. We describe the development of a 3D human cell-based in vitro assay for the investigation of nephrotoxicity, using RPTEC-TERT1 cells.

The human hepatocyte TXG-MAPr: gene co-expression network modules to support mechanism-based risk assessment.

Mechanism-based risk assessment is urged to advance and fully permeate into current safety assessment practices, possibly at early phases of drug safety testing. Toxicogenomics is a promising source of mechanisms-revealing data, but interpretative analysis tools specific for the testing systems (e.g.

A Set of Six Gene Expression Biomarkers Identify Rat Liver Tumorigens in Short-term Assays.

Chemical-induced liver cancer occurs in rodents through well-characterized adverse outcome pathways. We hypothesized that measurement of the 6 most common molecular initiating events (MIEs) in liver cancer adverse outcome pathways in short-term assays using only gene expression will allow early identification of chemicals and their associated doses that are likely to be tumorigenic in the liver in 2-year bioassays. We tested this hypothesis using transcript data from a rat liver microarray compendium consisting of 2013 comparisons of 146 chemicals administered at doses with previously established effects on rat liver tumor induction.

Machine learning guided association of adverse drug reactions with in vitro target-based pharmacology.

Background: Adverse drug reactions (ADRs) are one of the leading causes of morbidity and mortality in health care. Understanding which drug targets are linked to ADRs can lead to the development of safer medicines.

Methods: Here, we analyse in vitro secondary pharmacology of common (off) targets for 2134 marketed drugs.

A Novel Open Access Web Portal for Integrating Mechanistic and Toxicogenomic Study Results.

Applying toxicogenomics to improving the safety profile of drug candidates and crop protection molecules is most useful when it identifies relevant biological and mechanistic information that highlights risks and informs risk mitigation strategies. Pathway-based approaches, such as gene set enrichment analysis, integrate toxicogenomic data with known biological process and pathways. Network methods help define unknown biological processes and offer data reduction advantages.

Assessment of Patient Medication Adherence, Medical Record Accuracy, and Medication Blood Concentrations for Prescription and Over-the-Counter Medications.

Importance: Inaccurate medication records and poor medication adherence result in incomplete knowledge of therapy for patients.

Objective: To study accuracy of medical records and patient adherence by measuring blood concentrations of medications.

Design, Setting, And Participants: This cross-sectional study validated a serum-based liquid chromatography-tandem mass spectrometry assay to simultaneously quantify 263 medications used for acute and chronic conditions.

Characterisation of the NRF2 transcriptional network and its response to chemical insult in primary human hepatocytes: implications for prediction of drug-induced liver injury.

The transcription factor NRF2, governed by its repressor KEAP1, protects cells against oxidative stress. There is interest in modelling the NRF2 response to improve the prediction of clinical toxicities such as drug-induced liver injury (DILI). However, very little is known about the makeup of the NRF2 transcriptional network and its response to chemical perturbation in primary human hepatocytes (PHH), which are often used as a translational model for investigating DILI.

Medication Exposure in Highly Adherent Psychiatry Patients.

Medication exposure is dependent upon many factors, the single most important being if the patient took the prescribed medication as indicated. To assess medication exposure for psychotropic and other medication classes, we enrolled 115 highly adherent psychiatry patients prescribed five or more medications. In these patients, we measured 21 psychotropic and 38 nonpsychotropic medications comprising a 59 medication multiplex assay panel.

Medication adherence, medical record accuracy, and medication exposure in real-world patients using comprehensive medication monitoring.

Background: Poor adherence to medication regimens and medical record inconsistencies result in incomplete knowledge of medication therapy in polypharmacy patients. By quantitatively identifying medications in the blood of patients and reconciling detected medications with the medical record, we have defined the severity of this knowledge gap and created a path toward optimizing medication therapy.

Methods And Findings: We validated a liquid chromatography-tandem mass spectrometry assay to detect and/or quantify 38 medications across a broad range of chronic diseases to obtain a comprehensive survey of patient adherence, medical record accuracy, and exposure variability in two patient populations.

Managing Psychotropic Medications in Complex, Real-World Patients Using Comprehensive Therapeutic Drug Monitoring.

There are multiple treatment options for depression, anxiety, psychosis, and other psychiatric disorders, and psychiatry patients are often comorbid with complex, polypharmacy treatment regimens. Unlike cardiovascular disease and diabetes, there are no readily available biomarkers to gauge treatment success with psychotropic medications, often resulting in subjective determination of medication therapy effectiveness. The physiochemical properties of psychiatric medications in general lend themselves to quantitative measurement in blood, offering an avenue to optimize treatment for each patient.

Assessing Concordance of Drug-Induced Transcriptional Response in Rodent Liver and Cultured Hepatocytes.

The effect of drugs, disease and other perturbations on mRNA levels are studied using gene expression microarrays or RNA-seq, with the goal of understanding molecular effects arising from the perturbation. Previous comparisons of reproducibility across laboratories have been limited in scale and focused on a single model. The use of model systems, such as cultured primary cells or cancer cell lines, assumes that mechanistic insights derived from the models would have been observed via in vivo studies.

Novel Phenotypic Outcomes Identified for a Public Collection of Approved Drugs from a Publicly Accessible Panel of Assays.

Phenotypic assays have a proven track record for generating leads that become first-in-class therapies. Whole cell assays that inform on a phenotype or mechanism also possess great potential in drug repositioning studies by illuminating new activities for the existing pharmacopeia. The National Center for Advancing Translational Sciences (NCATS) pharmaceutical collection (NPC) is the largest reported collection of approved small molecule therapeutics that is available for screening in a high-throughput setting.

Co-prescription trends in a large cohort of subjects predict substantial drug-drug interactions.

Pharmaceutical prescribing and drug-drug interaction data underlie recommendations on drug combinations that should be avoided or closely monitored by prescribers. Because the number of patients taking multiple medications is increasing, a comprehensive view of prescribing patterns in patients is important to better assess real world pharmaceutical response and evaluate the potential for multi-drug interactions. We obtained self-reported prescription data from NHANES surveys between 1999 and 2010, and confirm the previously reported finding of increasing drug use in the elderly.

What general conclusions can we draw from kinase profiling data sets?

Understanding general selectivity trends across the kinome has implications ranging from target selection, compound prioritization, toxicity and patient tailoring. Several recent publications have described the characterization of kinase inhibitors via large assay panels, offering a range of generalizations that influenced kinase inhibitor research trends. Since a subset of profiled inhibitors overlap across reports, we evaluated the concordance of activity results for the same compound-kinase pairs across four data sources generated from different kinase biochemical assay technologies.

Relating molecular properties and in vitro assay results to in vivo drug disposition and toxicity outcomes.

A primary goal of lead optimization is to identify compounds with improved absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. A number of reports have linked computed molecular properties to desirable in vivo ADMET outcomes, but a significant limitation of these analyses is the failure to control statistically for possible covariates. We examine the relationship between molecular properties and in vitro surrogate assays vs in vivo properties within 173 chemical series from a database of 3773 compounds with rodent pharmacokinetic and toxicology data.

A robust high-content imaging approach for probing the mechanism of action and phenotypic outcomes of cell-cycle modulators.

High-content screening is increasingly used to elucidate changes in cellular biology arising from treatment with small molecules and biological probes. We describe a cell classifier for automated analysis of multiparametric data from immunofluorescence microscopy and characterize the phenotypes of 41 cell-cycle modulators, including several protein kinase inhibitors in preclinical and clinical development. This method produces a consistent assessment of treatment-induced phenotypes across experiments done by different biologists and highlights the prevalence of nonuniform and concentration-dependent cellular response to treatment.

Predicting the accuracy of ligand overlay methods with Random Forest models.

The accuracy of binding mode prediction using standard molecular overlay methods (ROCS, FlexS, Phase, and FieldCompare) is studied. Previous work has shown that simple decision tree modeling can be used to improve accuracy by selection of the best overlay template. This concept is extended to the use of Random Forest (RF) modeling for template and algorithm selection.

Prioritizing hits from phenotypic high-content screens.

In the past decade, advances in the field of high-content screening (HCS) have provided researchers with a powerful new screening tool to observe treatment effects on multiple experimental parameters. While extremely useful, HCS has resulted in the collection of large datasets of increased complexity that require intensive analysis. Recently, approaches have been developed to analyze multi-parametric HCS data more completely and, when used in conjunction with RNA interference, target-based biochemistry and structural analysis, these approaches have begun to unlock the potential of this screening format in aiding drug discovery.

Chemical fragments as foundations for understanding target space and activity prediction.

The use of small inhibitors' fragment frequencies for understanding kinase potency and selectivity is described. By quantification of differences in the frequency of occurrence of fragments, similarities between small molecules and their targets can be determined. Naive Bayes models employing fragments provide highly interpretable and reliable means for predicting potency in individual kinases, as demonstrated in retrospective tests and prospective selections that were subsequently screened.

Lessons in molecular recognition. 2. Assessing and improving cross-docking accuracy.

Docking methods are used to predict the manner in which a ligand binds to a protein receptor. Many studies have assessed the success rate of programs in self-docking tests, whereby a ligand is docked into the protein structure from which it was extracted. Cross-docking, or using a protein structure from a complex containing a different ligand, provides a more realistic assessment of a docking program's ability to reproduce X-ray results.

Dependence of molecular properties on proteomic family for marketed oral drugs.

An association of drugs with their proteomic family reveals that molecular properties of drugs targeting proteases, lipid and peptide G-protein-coupled receptors (GPCRs), and nuclear hormone receptors significantly exceed limits for some properties in the "rule of five", while drugs targeting cytochrome P450s, biogenic amine GPCRs, and transporters have significantly lower values for certain properties. Also, the variation in drug targets appears to be a factor explaining increasing molecular weight over time.

Ferroelectric liquid crystals induced by dopants with axially chiral 2,2'-spirobiindan-1,1'-dione cores.

The axially chiral dopants (R)-5,5'-, 5,6'-, and 6,6'-diheptyloxy-2,2'-spirobiindan-1,1'-dione ((R)-2, -3, and -4) were synthesized in optically pure form, and their absolute configurations were assigned by the exciton chirality method using circular dichroism spectroscopy. These new compounds were doped in four achiral liquid crystal hosts to give chiral smectic C* (SmC*) phases with spontaneous polarizations (Ps) that vary with the core structure of the host. The spontaneous polarization induced by the 5,5'-dialkoxy derivative (R)-2 is uniformly positive, whereas that induced by the 6,6'-dialkoxy derivative (R)-4 is uniformly negative and shows a different trend in host dependence.