Algorithmic Identification of Treatment-Emergent Adverse Events From Clinical Notes Using Large Language Models: A Pilot Study in Inflammatory Bowel Disease

Outpatient clinical notes are a rich source of information regarding drug safety. However, data in these notes are currently underutilized for pharmacovigilance due to methodological limitations in text mining. Large language models (LLMs) like Bidirectional Encoder Representations from Transformers (BERT) have shown progress in a range of natural language processing tasks but have not yet been evaluated on adverse event (AE) detection. We adapted a new clinical LLM, University of California - San Francisco (UCSF)-BERT, to identify serious AEs (SAEs) occurring after treatment with a non-steroid immunosuppressant for inflammatory bowel disease (IBD). We compared this model to other language models that have previously been applied to AE detection. We annotated 928 outpatient IBD notes corresponding to 928 individual patients with IBD for all SAE-associated hospitalizations occurring after treatment with a non-steroid immunosuppressant. These notes contained 703 SAEs in total, the most common of which was failure of intended efficacy. Out of eight candidate models, UCSF-BERT achieved the highest numerical performance on identifying drug-SAE pairs from this corpus (accuracy 88-92%, macro F1 61-68%), with 5-10% greater accuracy than previously published models. UCSF-BERT was significantly superior at identifying hospitalization events emergent to medication use (P < 0.01). LLMs like UCSF-BERT achieve numerically superior accuracy on the challenging task of SAE detection from clinical notes compared with prior methods. Future work is needed to adapt this methodology to improve model performance and evaluation using multicenter data and newer architectures like Generative pre-trained transformer (GPT). Our findings support the potential value of using large language models to enhance pharmacovigilance.

Deep learning-enabled natural language processing to identify directional pharmacokinetic drug-drug interactions

BACKGROUND

During drug development, it is essential to gather information about the change of clinical exposure of a drug (object) due to the pharmacokinetic (PK) drug-drug interactions (DDIs) with another drug (precipitant). While many natural language processing (NLP) methods for DDI have been published, most were designed to evaluate if (and what kind of) DDI relationships exist in the text, without identifying the direction of DDI (object vs. precipitant drug). Here we present a method for the automatic identification of the directionality of a PK DDI from literature or drug labels.

METHODS

We reannotated the Text Analysis Conference (TAC) DDI track 2019 corpus for identifying the direction of a PK DDI and evaluated the performance of a fine-tuned BioBERT model on this task by following the training and validation steps prespecified by TAC.

RESULTS

This initial attempt showed the model achieved an F-score of 0.82 in identifying sentences as containing PK DDI and an F-score of 0.97 in identifying object versus precipitant drugs in those sentences.

DISCUSSION AND CONCLUSION

Despite a growing list of NLP methods for DDI extraction, most of them use a common set of corpora to perform general purpose tasks (e.g., classifying a sentence into one of several fixed DDI categories). There is a lack of coordination between the drug development and biomedical informatics method development community to develop corpora and methods to perform specific tasks (e.g., extract clinical exposure changes due to PK DDI). We hope that our effort can encourage such a coordination so that more "fit for purpose" NLP methods could be developed and used to facilitate the drug development process.

Algorithmic identification of treatment-emergent adverse events from clinical notes using large language models: a pilot study in inflammatory bowel disease

Background and Aims

Outpatient clinical notes are a rich source of information regarding drug safety. However, data in these notes are currently underutilized for pharmacovigilance due to methodological limitations in text mining. Large language models (LLM) like BERT have shown progress in a range of natural language processing tasks but have not yet been evaluated on adverse event detection.

Methods

We adapted a new clinical LLM, UCSF BERT, to identify serious adverse events (SAEs) occurring after treatment with a non-steroid immunosuppressant for inflammatory bowel disease (IBD). We compared this model to other language models that have previously been applied to AE detection.

Results

We annotated 928 outpatient IBD notes corresponding to 928 individual IBD patients for all SAE-associated hospitalizations occurring after treatment with a non-steroid immunosuppressant. These notes contained 703 SAEs in total, the most common of which was failure of intended efficacy. Out of 8 candidate models, UCSF BERT achieved the highest numerical performance on identifying drug-SAE pairs from this corpus (accuracy 88-92%, macro F1 61-68%), with 5-10% greater accuracy than previously published models. UCSF BERT was significantly superior at identifying hospitalization events emergent to medication use (p < 0.01).

Conclusions

LLMs like UCSF BERT achieve numerically superior accuracy on the challenging task of SAE detection from clinical notes compared to prior methods. Future work is needed to adapt this methodology to improve model performance and evaluation using multi-center data and newer architectures like GPT. Our findings support the potential value of using large language models to enhance pharmacovigilance.

The expanding universe of NUTM1 fusions in pediatric cancer

NUT midline carcinoma family member 1 (NUTM1) fusions were originally identified in poorly differentiated and clinically aggressive carcinomas typically located in the midline structures of children and young adults, and collectively known as NUT (midline) carcinomas. Next-generation sequencing later uncovered NUTM1 fusions in a variety of other pediatric and adult cancers of diverse location and type, including hematologic malignancies, cutaneous adnexal tumors, and sarcomas. A vast array of NUTM1 fusions with bromodomain containing 4 (BRD4) or bromodomain containing 3 (BRD3), which are characteristic of NUT carcinoma, and with several other fusion partners have been identified and associated with variable prognosis. These non-kinase fusions are thought to cause epigenetic reprogramming, thereby promoting proliferation, and hindering the differentiation of cancer cells. Many questions about both the function of the naïve NUTM1 protein, which is mostly restricted to the germ cells of the testis and is related to spermatogenesis and the oncogenic mechanisms of the various NUTM1 fusions in both adult and pediatric cancer, are still unanswered. Moreover, whether there is a relationship defined by the presence of NUTM1 fusions between conventional NUT carcinoma and other NUTM1-rearranged neoplasms remains to be elucidated. This review will focus on recent discoveries of NUTM1 fusions found in pediatric cancers, their prognostic impact, and emergence as novel oncogenic drivers.

Rewiring Drug Research and Development through Human Data-Driven Discovery (HD3)

In an era of unparalleled technical advancement, the pharmaceutical industry is struggling to transform data into increased research and development efficiency, and, as a corollary, new drugs for patients. Here, we briefly review some of the commonly discussed issues around this counterintuitive innovation crisis. Looking at both industry- and science-related factors, we posit that traditional preclinical research is front-loading the development pipeline with data and drug candidates that are unlikely to succeed in patients. Applying a first principles analysis, we highlight the critical culprits and provide suggestions as to how these issues can be rectified through the pursuit of a Human Data-driven Discovery (HD³) paradigm. Consistent with other examples of disruptive innovation, we propose that new levels of success are not dependent on new inventions, but rather on the strategic integration of existing data and technology assets. In support of these suggestions, we highlight the power of HD³, through recently published proof-of-concept applications in the areas of drug safety analysis and prediction, drug repositioning, the rational design of combination therapies and the global response to the COVID-19 pandemic. We conclude that innovators must play a key role in expediting the path to a largely human-focused, systems-based approach to drug discovery and research.

New science, drug regulation, and emergent public health issues: The work of FDA's division of applied regulatory science

The U.S. Food and Drug Administration (FDA) Division of Applied Regulatory Science (DARS) moves new science into the drug review process and addresses emergent regulatory and public health questions for the Agency. By forming interdisciplinary teams, DARS conducts mission-critical research to provide answers to scientific questions and solutions to regulatory challenges. Staffed by experts across the translational research spectrum, DARS forms synergies by pulling together scientists and experts from diverse backgrounds to collaborate in tackling some of the most complex challenges facing FDA. This includes (but is not limited to) assessing the systemic absorption of sunscreens, evaluating whether certain drugs can convert to carcinogens in people, studying drug interactions with opioids, optimizing opioid antagonist dosing in community settings, removing barriers to biosimilar and generic drug development, and advancing therapeutic development for rare diseases. FDA tasks DARS with wide ranging issues that encompass regulatory science; DARS, in turn, helps the Agency solve these challenges. The impact of DARS research is felt by patients, the pharmaceutical industry, and fellow regulators. This article reviews applied research projects and initiatives led by DARS and conducts a deeper dive into select examples illustrating the impactful work of the Division.

A network paradigm predicts drug synergistic effects using downstream protein-protein interactions

In some cases, drug combinations affect adverse outcome phenotypes by binding the same protein; however, drug-binding proteins are associated through protein-protein interaction (PPI) networks within the cell, suggesting that drug phenotypes may result from long-range network effects. We first used PPI network analysis to classify drugs based on proteins downstream of their targets and next predicted drug combination effects where drugs shared network proteins but had distinct binding proteins (e.g., targets, enzymes, or transporters). By classifying drugs using their downstream proteins, we had an 80.7% sensitivity for predicting rare drug combination effects documented in gold-standard datasets. We further measured the effect of predicted drug combinations on adverse outcome phenotypes using novel observational studies in the electronic health record. We tested predictions for 60 network-drug classes on seven adverse outcomes and measured changes in clinical outcomes for predicted combinations. These results demonstrate a novel paradigm for anticipating drug synergistic effects using proteins downstream of drug targets.

Effect of Paroxetine or Quetiapine Combined With Oxycodone vs Oxycodone Alone on Ventilation During Hypercapnia: A Randomized Clinical Trial

IMPORTANCE

Opioids can cause severe respiratory depression by suppressing feedback mechanisms that increase ventilation in response to hypercapnia. Following the addition of boxed warnings to benzodiazepine and opioid products about increased respiratory depression risk with simultaneous use, the US Food and Drug Administration evaluated whether other drugs that might be used in place of benzodiazepines may cause similar effects.

OBJECTIVE

To study whether combining paroxetine or quetiapine with oxycodone, compared with oxycodone alone, decreases the ventilatory response to hypercapnia.

DESIGN, SETTING, AND PARTICIPANTS

Randomized, double-blind, crossover clinical trial at a clinical pharmacology unit (West Bend, Wisconsin) with 25 healthy participants from January 2021 through May 25, 2021.

INTERVENTIONS

Oxycodone 10 mg on days 1 and 5 and the following in a randomized order for 5 days: paroxetine 40 mg daily, quetiapine twice daily (increasing daily doses from 100 mg to 400 mg), or placebo.

MAIN OUTCOMES AND MEASURES

Ventilation at end-tidal carbon dioxide of 55 mm Hg (hypercapnic ventilation) using rebreathing methodology assessed for paroxetine or quetiapine with oxycodone, compared with placebo and oxycodone, on days 1 and 5 (primary) and for paroxetine or quetiapine alone compared with placebo on day 4 (secondary).

RESULTS

Among 25 participants (median age, 35 years [IQR, 30-40 years]; 11 female [44%]), 19 (76%) completed the trial. The mean hypercapnic ventilation was significantly decreased with paroxetine plus oxycodone vs placebo plus oxycodone on day 1 (29.2 vs 34.1 L/min; mean difference [MD], -4.9 L/min [1-sided 97.5% CI, -∞ to -0.6]; P = .01) and day 5 (25.1 vs 35.3 L/min; MD, -10.2 L/min [1-sided 97.5% CI, -∞ to -6.3]; P < .001) but was not significantly decreased with quetiapine plus oxycodone vs placebo plus oxycodone on day 1 (33.0 vs 34.1 L/min; MD, -1.2 L/min [1-sided 97.5% CI, -∞ to 2.8]; P = .28) or on day 5 (34.7 vs 35.3 L/min; MD, -0.6 L/min [1-sided 97.5% CI, -∞ to 3.2]; P = .37). As a secondary outcome, mean hypercapnic ventilation was significantly decreased on day 4 with paroxetine alone vs placebo (32.4 vs 41.7 L/min; MD, -9.3 L/min [1-sided 97.5% CI, -∞ to -3.9]; P < .001), but not with quetiapine alone vs placebo (42.8 vs 41.7 L/min; MD, 1.1 L/min [1-sided 97.5% CI, -∞ to 6.4]; P = .67). No drug-related serious adverse events were reported.

CONCLUSIONS AND RELEVANCE

In this preliminary study involving healthy participants, paroxetine combined with oxycodone, compared with oxycodone alone, significantly decreased the ventilatory response to hypercapnia on days 1 and 5, whereas quetiapine combined with oxycodone did not cause such an effect. Additional investigation is needed to characterize the effects after longer-term treatment and to determine the clinical relevance of these findings.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04310579.

Analysis of secondary pharmacology assays received by the US Food and Drug Administration

Secondary pharmacology studies are a time-efficient and cost-effective method for determining the safety profile of a potential new drug before it enters human trials. The results of these multi-target screens are commonly submitted with Investigational New Drug (IND) applications, but there currently is little guidance on how such information is presented and which targets are chosen for testing. In this study, we expand on our previous analysis of secondary pharmacology reports by manually curating and analyzing all secondary pharmacology results received by the FDA received as part of an IND submission. A total of 1120 INDs submitted by 480 sponsors between 1999 and October 2020 were included in this study. The overall results were largely consistent with previous internal and external studies, showing that the most tested target in our set was the histamine 1 receptor (tested 938 times), the most hit target was sodium channel site 2 (hit 141 times), and the target with the highest hit percentage was the vesicular monoamine transporter 2 (hit 42.2% of the time). Additionally, this study demonstrated that improvements in the secondary pharmacology submission process, such as changes in formatting and nomenclature, could enhance the utility of these assays for regulatory review, including assisting with identifying the safety liabilities of a drug candidate early in development. This updated data set will allow FDA-industry collaborative working groups to continue developing the best methods for regulatory submission of secondary pharmacology data and evaluate the need for a standard target panel.

Ontology-Based Classification and Analysis of Adverse Events Associated With the Usage of Chloroquine and Hydroxychloroquine

Multiple methodologies have been developed to identify and predict adverse events (AEs); however, many of these methods do not consider how patient population characteristics, such as diseases, age, and gender, affect AEs seen. In this study, we evaluated the utility of collecting and analyzing AE data related to hydroxychloroquine (HCQ) and chloroquine (CQ) from US Prescribing Information (USPIs, also called drug product labels or package inserts), the FDA Adverse Event Reporting System (FAERS), and peer-reviewed literature from PubMed/EMBASE, followed by AE classification and modeling using the Ontology of Adverse Events (OAE). Our USPI analysis showed that CQ and HCQ AE profiles were similar, although HCQ was reported to be associated with fewer types of cardiovascular, nervous system, and musculoskeletal AEs. According to EMBASE literature mining, CQ and HCQ were associated with QT prolongation (primarily when treating COVID-19), heart arrhythmias, development of Torsade des Pointes, and retinopathy (primarily when treating lupus). The FAERS data was analyzed by proportional ratio reporting, Chi-square test, and minimal case number filtering, followed by OAE classification. HCQ was associated with 63 significant AEs (including 21 cardiovascular AEs) for COVID-19 patients and 120 significant AEs (including 12 cardiovascular AEs) for lupus patients, supporting the hypothesis that the disease being treated affects the type and number of certain CQ/HCQ AEs that are manifested. Using an HCQ AE patient example reported in the literature, we also ontologically modeled how an AE occurs and what factors (e.g., age, biological sex, and medical history) are involved in the AE formation. The methodology developed in this study can be used for other drugs and indications to better identify patient populations that are particularly vulnerable to AEs.

Effects of sedative psychotropic drugs combined with oxycodone on respiratory depression in the rat

Following a decision to require label warnings for concurrent use of opioids and benzodiazepines and increased risk of respiratory depression and death, the US Food and Drug Administratioin (FDA) recognized that other sedative psychotropic drugs may be substituted for benzodiazepines and be used concurrently with opioids. In some cases, data on the ability of these alternatives to depress respiration alone or in conjunction with an opioid are lacking. A nonclinical in vivo model was developed that could detect worsening respiratory depression when a benzodiazepine (diazepam) was used in combination with an opioid (oxycodone) compared to the opioid alone based on an increased arterial partial pressure of carbon dioxide (pCO2 ). The current study used that model to assess the impact on respiration of non-benzodiazepine sedative psychotropic drugs representative of different drug classes (clozapine, quetiapine, risperidone, zolpidem, trazodone, carisoprodol, cyclobenzaprine, mirtazapine, topiramate, paroxetine, duloxetine, ramelteon, and suvorexant) administered alone and with oxycodone. At clinically relevant exposures, paroxetine, trazodone, and quetiapine given with oxycodone significantly increased pCO2 above the oxycodone effect. Analyses indicated that most pCO2 interaction effects were due to pharmacokinetic interactions resulting in increased oxycodone exposure. Increased pCO2 recorded with oxycodone-paroxetine co-administration exceeded expected effects from only drug exposure suggesting another mechanism for the increased pharmacodynamic response. This study identified drug-drug interaction effects depressing respiration in an animal model when quetiapine or paroxetine were co-administered with oxycodone. Clinical pharmacodynamic drug interaction studies are being conducted with these drugs to assess translatability of these findings.

Aggregation and analysis of secondary pharmacology data from investigational new drug submissions at the US Food and Drug Administration

Secondary pharmacology studies are utilized by the pharmaceutical industry as a cost-efficient tool to identify potential safety liabilities of drugs before entering Phase 1 clinical trials. These studies are recommended by the Food and Drug Administration (FDA) as a part of the Investigational New Drug (IND) application. However, despite the utility of these assays, there is little guidance on which targets should be screened and which format should be used. Here, we evaluated 226 secondary pharmacology profiles obtained from close to 90 unique sponsors. The results indicated that the most tested target in our set was the GABA benzodiazepine receptor (tested 168 times), the most hit target was adenosine 3 (hit 24 times), and the target with the highest hit percentage was the quinone reductase 2 (NQO2) receptor (hit 29% of the time). The overall results were largely consistent with those observed in previous publications. However, this study also identified the need for improvement in the submission process of secondary pharmacology studies by industry, which could enhance their utility for regulatory purpose. FDA-industry collaborative working groups will utilize this data to determine the best methods for regulatory submission of these studies and evaluate the need for a standard target panel.

Target Adverse Event Profiles for Predictive Safety in the Postmarket Setting

We improved a previous pharmacological target adverse-event (TAE) profile model to predict adverse events (AEs) on US Food and Drug Administration (FDA) drug labels at the time of approval. The new model uses more drugs and features for learning as well as a new algorithm. Comparator drugs sharing similar target activities to a drug of interest were evaluated by aggregating AEs from the FDA Adverse Event Reporting System (FAERS), FDA drug labels, and medical literature. An ensemble machine learning model was used to evaluate FAERS case count, disproportionality scores, percent of comparator drug labels with a specific AE, and percent of comparator drugs with the reports of the event in the literature. Overall classifier performance was F1 of 0.71, area under the precision-recall curve of 0.78, and area under the receiver operating characteristic curve of 0.87. TAE analysis continues to show promise as a method to predict adverse events at the time of approval.

VaximmutorDB: A Web-Based Vaccine Immune Factor Database and Its Application for Understanding Vaccine-Induced Immune Mechanisms

Vaccines stimulate various immune factors critical to protective immune responses. However, a comprehensive picture of vaccine-induced immune factors and pathways have not been systematically collected and analyzed. To address this issue, we developed VaximmutorDB, a web-based database system of vaccine immune factors (abbreviated as “vaximmutors”) manually curated from peer-reviewed articles. VaximmutorDB currently stores 1,740 vaccine immune factors from 13 host species (e.g., human, mouse, and pig). These vaximmutors were induced by 154 vaccines for 46 pathogens. Top 10 vaximmutors include three antibodies (IgG, IgG2a and IgG1), Th1 immune factors (IFN-γ and IL-2), Th2 immune factors (IL-4 and IL-6), TNF-α, CASP-1, and TLR8. Many enriched host processes (e.g., stimulatory C-type lectin receptor signaling pathway, SRP-dependent cotranslational protein targeting to membrane) and cellular components (e.g., extracellular exosome, nucleoplasm) by all the vaximmutors were identified. Using influenza as a model, live attenuated and killed inactivated influenza vaccines stimulate many shared pathways such as signaling of many interleukins (including IL-1, IL-4, IL-6, IL-13, IL-20, and IL-27), interferon signaling, MARK1 activation, and neutrophil degranulation. However, they also present their unique response patterns. While live attenuated influenza vaccine FluMist induced significant signal transduction responses, killed inactivated influenza vaccine Fluarix induced significant metabolism of protein responses. Two different Yellow Fever vaccine (YF-Vax) studies resulted in overlapping gene lists; however, they shared more portions of pathways than gene lists. Interestingly, live attenuated YF-Vax simulates significant metabolism of protein responses, which was similar to the pattern induced by killed inactivated Fluarix. A user-friendly web interface was generated to access, browse and search the VaximmutorDB database information. As the first web-based database of vaccine immune factors, VaximmutorDB provides systematical collection, standardization, storage, and analysis of experimentally verified vaccine immune factors, supporting better understanding of protective vaccine immunity.

Aggregation and analysis of indication-symptom relationships for drugs approved in the USA

Purpose

Drug indications and disease symptoms often confound adverse event reports in real-world datasets, including electronic health records and reports in the FDA Adverse Event Reporting System (FAERS). A thorough, standardized set of indications and symptoms is needed to identify these confounders in such datasets for drug research and safety assessment. The aim of this study is to create a comprehensive list of drug-indication associations and disease-symptom associations using multiple resources, including existing databases and natural language processing.

Methods

Drug indications for drugs approved in the USA were extracted from two databases, RxNorm and Side Effect Resource (SIDER). Symptoms for these indications were extracted from MedlinePlus and using natural language processing from PubMed abstracts.

Results

A total of 1361 unique drugs, 1656 unique indications, and 2201 unique symptoms were extracted from a wide variety of MedDRA System Organ Classes. Text-mining precision was maximized at 0.65 by examining Term Frequency Inverse Document Frequency (TF-IDF) scores of the disease-symptom associations.

Conclusion

The drug-indication associations and disease-symptom associations collected in this study may be useful in identifying confounders in other datasets, such as safety reports. With further refinement and additional drugs, indications, and symptoms, this dataset may become a quality resource for disease symptoms.

Electronic supplementary material

The online version of this article (10.1007/s00228-020-02898-w) contains supplementary material, which is available to authorized users.

Predicting potential adverse events using safety data from marketed drugs

BACKGROUND

While clinical trials are considered the gold standard for detecting adverse events, often these trials are not sufficiently powered to detect difficult to observe adverse events. We developed a preliminary approach to predict 135 adverse events using post-market safety data from marketed drugs. Adverse event information available from FDA product labels and scientific literature for drugs that have the same activity at one or more of the same targets, structural and target similarities, and the duration of post market experience were used as features for a classifier algorithm. The proposed method was studied using 54 drugs and a probabilistic approach of performance evaluation using bootstrapping with 10,000 iterations.

RESULTS

Out of 135 adverse events, 53 had high probability of having high positive predictive value. Cross validation showed that 32% of the model-predicted safety label changes occurred within four to nine years of approval (median: six years).

CONCLUSIONS

This approach predicts 53 serious adverse events with high positive predictive values where well-characterized target-event relationships exist. Adverse events with well-defined target-event associations were better predicted compared to adverse events that may be idiosyncratic or related to secondary target effects that were poorly captured. Further enhancement of this model with additional features, such as target prediction and drug binding data, may increase accuracy.

Evaluating kratom alkaloids using PHASE

Kratom is a botanical substance that is marketed and promoted in the US for pharmaceutical opioid indications despite having no US Food and Drug Administration approved uses. Kratom contains over forty alkaloids including two partial agonists at the mu opioid receptor, mitragynine and 7-hydroxymitragynine, that have been subjected to the FDA's scientific and medical evaluation. However, pharmacological and toxicological data for the remaining alkaloids are limited. Therefore, we applied the Public Health Assessment via Structural Evaluation (PHASE) protocol to generate in silico binding profiles for 25 kratom alkaloids to facilitate the risk evaluation of kratom. PHASE demonstrates that kratom alkaloids share structural features with controlled opioids, indicates that several alkaloids bind to the opioid, adrenergic, and serotonin receptors, and suggests that mitragynine and 7-hydroxymitragynine are the strongest binders at the mu opioid receptor. Subsequently, the in silico binding profiles of a subset of the alkaloids were experimentally verified at the opioid, adrenergic, and serotonin receptors using radioligand binding assays. The verified binding profiles demonstrate the ability of PHASE to identify potential safety signals and provide a tool for prioritizing experimental evaluation of high-risk compounds.

Assessing the Structural and Pharmacological Similarity of Newly Identified Drugs of Abuse to Controlled Substances Using Public Health Assessment via Structural Evaluation

The US Food and Drug Administration's Center for Drug Evaluation and Research (CDER) developed an investigational Public Health Assessment via Structural Evaluation (PHASE) methodology to provide a structure-based evaluation of a newly identified opioid's risk to public safety. PHASE utilizes molecular structure to predict biological function. First, a similarity metric quantifies the structural similarity of a new drug relative to drugs currently controlled in the Controlled Substances Act (CSA). Next, software predictions provide the primary and secondary biological targets of the new drug. Finally, molecular docking estimates the binding affinity at the identified biological targets. The multicomponent computational approach coupled with expert review provides a rapid, systematic evaluation of a new drug in the absence of in vitro or in vivo data. The information provided by PHASE has the potential to inform law enforcement agencies with vital information regarding newly emerging illicit opioids.

PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development

Failure to demonstrate efficacy and safety issues are important reasons that drugs do not reach the market. An incomplete understanding of how drugs exert their effects hinders regulatory and pharmaceutical industry projections of a drug's benefits and risks. Signaling pathways mediate drug response and while many signaling molecules have been characterized for their contribution to disease or their role in drug side effects, our knowledge of these pathways is incomplete. To better understand all signaling molecules involved in drug response and the phenotype associations of these molecules, we created a novel method, PathFX, a non-commercial entity, to identify these pathways and drug-related phenotypes. We benchmarked PathFX by identifying drugs' marketed disease indications and reported a sensitivity of 41%, a 2.7-fold improvement over similar approaches. We then used PathFX to strengthen signals for drug-adverse event pairs occurring in the FDA Adverse Event Reporting System (FAERS) and also identified opportunities for drug repurposing for new diseases based on interaction paths that associated a marketed drug to that disease. By discovering molecular interaction pathways, PathFX improved our understanding of drug associations to safety and efficacy phenotypes. The algorithm may provide a new means to improve regulatory and therapeutic development decisions.

Target-Adverse Event Profiles to Augment Pharmacovigilance: A Pilot Study With Six New Molecular Entities

Clinical trials can fail to detect rare adverse events (AEs). We assessed the ability of pharmacological target adverse‐event (TAE) profiles to predict AEs on US Food and Drug Administration (FDA) drug labels at least 4 years after approval. TAE profiles were generated by aggregating AEs from the FDA adverse event reporting system (FAERS) reports and the FDA drug labels for drugs that hit a common target. A genetic algorithm (GA) was used to choose the adverse event (AE) case count (N), disproportionality score in FAERS (proportional reporting ratio (PRR)), and percent of comparator drug labels with an AE to maximize F‐measure. With FAERS data alone, precision, recall, and specificity were 0.57, 0.78, and 0.61, respectively. After including FDA drug label data, precision, recall, and specificity improved to 0.67, 0.81, and 0.71, respectively. Eighteen of 23 (78%) postmarket label changes were identified correctly. TAE analysis shows promise as a method to predict AEs at the time of drug approval.

Towards precision informatics of pharmacovigilance: OAE-CTCAE mapping and OAE-based representation and analysis of adverse events in patients treated with cancer drugs

A critical issue in the usage of cancer drugs is its association with various adverse events (AEs) in some, but not all, patients. The National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events (CTCAE) is a controlled terminology for AE classification and analysis in cancer clinical trials. The Ontology of Adverse Events (OAE) is a community-based ontology in the domain of AEs. In this study, OAE was first updated by including AE severity grading and OAE-CTCAE mapping. An OAE subset containing CTCAE-related terms and their associated OAE terms was generated to facilitate term usage. A use case study based on a published cancer drug clinical trial demonstrates that OAE provides better hierarchical representation, includes semantic relations, and supports automated reasoning. Demonstrated with a single patient analysis, the OAE framework supports precision informatics for representing AEs and related genetic and clinical conditions in individual patients treated with cancer drugs.

Association Between Serotonin Syndrome and Second-Generation Antipsychotics via Pharmacological Target-Adverse Event Analysis

Case reports suggest an association between second‐generation antipsychotics (SGAs) and serotonin syndrome (SS). The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) was analyzed to generate hypotheses about how SGAs may interact with pharmacological targets associated with SS. FAERS was integrated with additional sources to link information about adverse events with drugs and targets. Using Proportional Reporting Ratios, we identified signals that were further investigated with the literature to evaluate mechanistic hypotheses formed from the integrated FAERS data. Analysis revealed common pharmacological targets perturbed in both SGA and SS cases, indicating that SGAs may induce SS. The literature also supported 5‐HT_2A antagonism and 5‐HT_1A agonism as common mechanisms that may explain the SGA‐SS association. Additionally, integrated FAERS data mining and case studies suggest that interactions between SGAs and other serotonergic agents may increase the risk for SS. Computational analysis can provide additional insights into the mechanisms underlying the relationship between SGAs and SS.

The Enabler Cannula Pump: A Novel Circulatory Support System

Background

The enabler circulatory support system is a catheter pump which expels blood from the left or right ventricular cavity and provides pulsatile flow in the ascending aorta or pulmonary artery. It is driven by a bedside installed pulsatile driving console. The device can easily be implanted by a minimal invasive approach, similar to the Hemopump.

Purpose

To demonstrate the hemodynamic performance of this new intracardiac support system.

Methods

In a series of 9 sheep, hemodynamic evolutions were recorded in various conditions of myocardial contractility (the non-failing, the moderately failing and the severely failing heart). Heart failure was induced by injection of microspheres in the coronary arteries.

Results

Introduction of the cannula through the aortic valve was feasible in all cases. Pump flow by the enabler was gradually increased to a maximum of 3.5 L/min. Diastolic (and mean) aortic blood pressure is significantly increased in the non-failing and moderately failing condition (counterpulsation mode). In heart failure, cardiac output is significantly increased by the pump (p<0.0001). A drop in left atrial pressure (indicating unloading) is achieved in all conditions but reaches significant levels only during heart failure (p=0.0068).

Conclusions

This new circulatory support system contributes to stabilization of the circulation in the presence of cardiac unloading. In heart failure it actually supports the circulation by increasing cardiac output and perfusion pressure.

Ontology-based collection, representation and analysis of drug-associated neuropathy adverse events

Background

Neuropathy often occurs following drug treatment such as chemotherapy. Severe instances of neuropathy can result in cessation of life-saving chemotherapy treatment.

Results

To support data representation and analysis of drug-associated neuropathy adverse events (AEs), we developed the Ontology of Drug Neuropathy Adverse Events (ODNAE). ODNAE extends the Ontology of Adverse Events (OAE). Our combinatorial approach identified 215 US FDA-licensed small molecule drugs that induce signs and symptoms of various types of neuropathy. ODNAE imports related drugs from the Drug Ontology (DrON) with their chemical ingredients defined in ChEBI. ODNAE includes 139 drug mechanisms of action from NDF-RT and 186 biological processes represented in the Gene Ontology (GO). In total ODNAE contains 1579 terms. Our analysis of the ODNAE knowledge base shows neuropathy-inducing drugs classified under specific molecular entity groups, especially carbon, pnictogen, chalcogen, and heterocyclic compounds. The carbon drug group includes 127 organic chemical drugs. Thirty nine receptor agonist and antagonist terms were identified, including 4 pairs (31 drugs) of agonists and antagonists that share targets (e.g., adrenergic receptor, dopamine, serotonin, and sex hormone receptor). Many drugs regulate neurological system processes (e.g., negative regulation of dopamine or serotonin uptake). SPARQL scripts were used to query the ODNAE ontology knowledge base.

Conclusions

ODNAE is an effective platform for building a drug-induced neuropathy knowledge base and for analyzing the underlying mechanisms of drug-induced neuropathy. The ODNAE-based methods used in this study can also be extended to the representation and study of other categories of adverse events.

Electronic supplementary material

The online version of this article (doi:10.1186/s13326-016-0069-x) contains supplementary material, which is available to authorized users.

DNAVaxDB: the first web-based DNA vaccine database and its data analysis

Since the first DNA vaccine studies were done in the 1990s, thousands more studies have followed. Here we report the development and analysis of DNAVaxDB (http://www.violinet.org/dnavaxdb), the first publically available web-based DNA vaccine database that curates, stores, and analyzes experimentally verified DNA vaccines, DNA vaccine plasmid vectors, and protective antigens used in DNA vaccines. All data in DNAVaxDB are annotated from reliable resources, particularly peer-reviewed articles. Among over 140 DNA vaccine plasmids, some plasmids were more frequently used in one type of pathogen than others; for example, pCMVi-UB for G- bacterial DNA vaccines, and pCAGGS for viral DNA vaccines. Presently, over 400 DNA vaccines containing over 370 protective antigens from over 90 infectious and non-infectious diseases have been curated in DNAVaxDB. While extracellular and bacterial cell surface proteins and adhesin proteins were frequently used for DNA vaccine development, the majority of protective antigens used in Chlamydophila DNA vaccines are localized to the inner portion of the cell. The DNA vaccine priming, other vaccine boosting vaccination regimen has been widely used to induce protection against infection of different pathogens such as HIV. Parasitic and cancer DNA vaccines were also systematically analyzed. User-friendly web query and visualization interfaces are available in DNAVaxDB for interactive data search. To support data exchange, the information of DNA vaccines, plasmids, and protective antigens is stored in the Vaccine Ontology (VO). DNAVaxDB is targeted to become a timely and vital source of DNA vaccines and related data and facilitate advanced DNA vaccine research and development.

Fullerene-rare gas mixed plasmas in an electron cyclotron resonance ion source

A synthesis technology of endohedral fullerenes such as Fe@C60 has developed with an electron cyclotron resonance (ECR) ion source. The production of N@C60 was reported. However, the yield was quite low, since most fullerene molecules were broken in the ECR plasma. We have adopted gas-mixing techniques in order to cool the plasma and then reduce fullerene dissociation. Mass spectra of ion beams extracted from fullerene-He, Ar or Xe mixed plasmas were observed with a Faraday cup. From the results, the He gas mixing technique is effective against fullerene destruction.

Chronic hibernating myocardium in sheep can occur without degenerating events and is reversed after revascularization

INTRODUCTION

Our goal was to show that blunting of myocardial flow reserve is mainly involved in adaptive chronic myocardial hibernation without apparent cardiomyocyte degeneration.

METHODS AND RESULTS

Sheep chronically instrumented with critical multivessel stenosis and/or percutaneous transluminal coronary angioplasty (PTCA)-induced revascularization were allowed to run and feed in the open for 2 and 5 months, respectively. Regional myocardial blood flow (MBF) with colored microspheres, regional and global left ventricular function and dimensions (2D echocardiography), and myocardial structure were studied. In sheep with a critical stenosis, a progressive increase in left ventricular end-diastolic and end-systolic cavity area and a decrease in fractional area change were found. Fraction of wall thickness decreased in all left ventricular wall segments. MBF was slightly but not significantly decreased at rest at 2 months. Morphological quantification revealed a rather small but significant increase in diffusely distributed connective tissue, cardiomyocyte hypertrophy, and presence of viable myocardium of which almost 30 % of the myocytes showed depletion of sarcomeres and accumulation of glycogen. The extent of myolysis in the transmural layer correlated with the degree of left ventricular dilation. Structural degeneration of cardiomyocytes was not observed. Balloon dilatation (PTCA) of one of the coronary artery stenoses at 10 weeks revealed recovery of fraction of wall thickness and near normalization of global subcellular structure at 20 weeks.

CONCLUSION

These data indicate that chronic reduction of coronary reserve by itself can induce ischemic cardiomyopathy characterized by left ventricular dilatation, depressed regional and global function, adaptive chronic myocardial hibernation, reactive fibrosis and cardiomyocyte hypertrophy in the absence of obvious degenerative phenomena.

SUMMARY

Reduction of myocardial flow reserve due to chronic coronary artery stenosis in sheep induces adaptive myocardial hibernation without involvement of degenerative phenomena.

Updates on the web-based VIOLIN vaccine database and analysis system

The integrative Vaccine Investigation and Online Information Network (VIOLIN) vaccine research database and analysis system (http://www.violinet.org) curates, stores, analyses and integrates various vaccine-associated research data. Since its first publication in NAR in 2008, significant updates have been made. Starting from 211 vaccines annotated at the end of 2007, VIOLIN now includes over 3240 vaccines for 192 infectious diseases and eight noninfectious diseases (e.g. cancers and allergies). Under the umbrella of VIOLIN, >10 relatively independent programs are developed. For example, Protegen stores over 800 protective antigens experimentally proven valid for vaccine development. VirmugenDB annotated over 200 'virmugens', a term coined by us to represent those virulence factor genes that can be mutated to generate successful live attenuated vaccines. Specific patterns were identified from the genes collected in Protegen and VirmugenDB. VIOLIN also includes Vaxign, the first web-based vaccine candidate prediction program based on reverse vaccinology. VIOLIN collects and analyzes different vaccine components including vaccine adjuvants (Vaxjo) and DNA vaccine plasmids (DNAVaxDB). VIOLIN includes licensed human vaccines (Huvax) and veterinary vaccines (Vevax). The Vaccine Ontology is applied to standardize and integrate various data in VIOLIN. VIOLIN also hosts the Ontology of Vaccine Adverse Events (OVAE) that logically represents adverse events associated with licensed human vaccines.

Systematic annotation and analysis of "virmugens"-virulence factors whose mutants can be used as live attenuated vaccines

Live attenuated vaccines are usually generated by mutation of genes encoding virulence factors. "Virmugen" is coined here to represent a gene that encodes for a virulent factor of a pathogen and has been proven feasible in animal models to make a live attenuated vaccine by knocking out this gene. Not all virulence factors are virmugens. VirmugenDB is a web-based virmugen database (http://www.violinet.org/virmugendb). Currently, VirmugenDB includes 225 virmugens that have been verified to be valuable for vaccine development against 57 bacterial, viral, and protozoan pathogens. Bioinformatics analysis has revealed significant patterns in virmugens. For example, 10 Gram-negative and 1 Gram-positive bacterial aroA genes are virmugens. A sequence analysis has revealed at least 50% of identities in the protein sequences of the 10 Gram-negative bacterial aroA virmugens. As a pathogen case study, Brucella virmugens were analyzed. Out of 15 verified Brucella virmugens, 6 are related to carbohydrate or nucleotide transport and metabolism, and 2 involving cell membrane biogenesis. In addition, 54 virmugens from 24 viruses and 12 virmugens from 4 parasites are also stored in VirmugenDB. Virmugens tend to involve metabolism of nutrients (e.g., amino acids, carbohydrates, and nucleotides) and cell membrane formation. Host genes whose expressions were regulated by virmugen mutation vaccines or wild type virulent pathogens have also been annotated and systematically compared. The bioinformatics annotation and analysis of virmugens helps to elucidate enriched virmugen profiles and the mechanisms of protective immunity, and further supports rational vaccine design.

Effect of pulse-modulated microwaves on fullerene ion production with electron cyclotron resonance ion source

Fullerene plasmas generated by pulse-modulated microwaves have been investigated under typical conditions at the Bio-Nano electron cyclotron resonance ion source. The effect of the pulse modulation is distinct from that of simply structured gases, and then the density of the fullerene plasmas increased as decreasing the duty ratio. The density for a pulse width of 10 μs at the period of 100 μs is 1.34 times higher than that for CW mode. We have studied the responses of fullerene and argon plasmas to pulsed microwaves. After the turnoff of microwave power, fullerene plasmas lasted ∼30 times longer than argon plasmas.

Study on the beam transport from the Bio-Nano ECRIS

The beam transport of N(+) ion and C(60)(+) ion in the Bio-Nano ECRIS with min-B configuration was investigated based on the ion beam profiles. The N(+) beam could be focused under the low-beam current conditions. Also the C(60)(+) beam could be focused in spite of the large space-charge effect which will lead the divergence of the beam. We confirmed that our beam transport system works well even for the C(60)(+) ion beam. We estimated the highest C(60)(+) beam current with the focused beam profile by comparing the N(+) ion beam.

Effect of transmyocardial laser revascularization on chronic ischemic hearts in sheep

BACKGROUND

We investigated the effect of transmyocardial laser revascularization (TMR) on myocardial function and regional blood flow in an animal model of ischemic heart disease.

METHODS

Chronic ischemia was induced in 11 sheep by the application of coronary stenosis on the left anterior descending (LAD) and circumflex coronary artery (LCX). Ten weeks later, in six of them, transmyocardial channels were created in the anterior free wall and in the posterior wall of the left ventricle. Five animals served as controls. The myocardial function was assessed by echocardiography taken at baseline and every 2 weeks after coronary stenosis and after TMR. Myocardial perfusion was measured by colored microspheres, injected at baseline, immediately after coronary stenosis, before and after TMR, and at 20 weeks after coronary stenosis. The hearts were retrieved at 20 weeks for light microscopic examination.

RESULTS

The left ventricular end-diastolic and end-systolic cavity area was elevated 20 weeks after coronary stenosis in the control and TMR groups. There was no difference between groups (analysis of variance; ANOVA, non-significant). The wall thickening fraction (WTF) decreased progressively and significantly after coronary stenosis in both groups. The WTF was further acutely reduced by TMR, and recovered gradually to the pre-TMR level. No significant difference in WTF was observed between the TMR and control groups. The resting myocardial blood flow was significantly increased by TMR at 20 weeks (P=0.03). Light microscopic examination revealed channel patency in 49% of the laser scars at 10 weeks post-TMR. A dense capillary network was observed at the edges of the surrounding scar.

CONCLUSIONS

In an experimental model of ischemic heart disease, TMR developed angiogenesis in the lased channels, but, however, failed to improve myocardial function.

Ascending versus descending aortic balloon pumping: organ and myocardial perfusion during ischemia

BACKGROUND

The ICS-Supracor (Abiomed, Danvers, MA) is a preshaped ascending aorta balloon pump. We compared the effects of this catheter with the classical descending intraaortic balloon pump (IABP). The study focused on hemodynamic effects, myocardial blood flow in normal and ischemic regions, cerebral perfusion, and peripheral organ perfusion.

METHODS

We placed a stenosis on the lateral branch of the coronary artery to reduce flow 50% (sheep). Measurements included hemodynamic changes, myocardial blood flow, and organ flow (colored microspheres) at baseline, after stenosis, during IABP support, and during ICS support.

RESULTS

Counterpulsation with the ICS led to a significantly higher peak diastolic aortic augmentation than with the IABP (IABP, 99 +/- 14 mm Hg; ICS, 140 +/- 29 mm Hg; p = 0.003). There was no significant change in cerebral perfusion or peripheral organ perfusion. Myocardial blood perfusion was significantly increased by the IABP as well as the ICS. This effect was seen in ischemic and nonischemic regions (subendocardial and subepicardial). The ICS improved myocardial blood flow significantly more than the IABP (IABP, 0.65 +/- 0.1 mL/min/g; ICS, 0.94 +/- 0.06 mL/min/g; p = 0.0005).

CONCLUSIONS

The ICS increases myocardial blood flow in ischemic regions significantly more than the IABP, without impairment of cerebral flow. Assessment of vascular complications, peripherally and in the ascending aorta, has to await results of clinical trials.

The intra-aortic cannula pump: A novel assist device for the acutely failing heart

OBJECTIVE

The intra-aortic cannula pump is a catheter pump designed to support the acutely failing heart. It expels blood from the left ventricle into the ascending aorta in a pulsatile flow pattern. The aim of the study was to analyze the hemodynamic performance of this new intracardiac support system in acute heart failure.

METHODS

A 24F cannula was studied in a series of 16 sheep. Hemodynamic changes were assessed in the nonfailing, the moderately failing, and the severely failing heart. Heart failure was induced by an injection of microspheres into the left anterior descending coronary artery. The cannula was inserted through the aortic arch and introduced through the aortic valve into the left ventricle.

RESULTS

Cannula insertion was feasible in all animals. Flow through the intra-aortic cannula flow was increased to a maximum of 3 L/min. No hemodynamic changes were observed in the nonfailing heart. A significant increase in cardiac output was observed in the moderately and severely reduced left ventricle (2.67 +/- 0.7 L to 3.51 +/- 0.83 L; P =.001; and 1.18 +/- 0.77 L to 2.43 +/- 0.44 L; P =.001, respectively). A drop in left atrial pressure was achieved in moderate and severe heart failure (14.1 +/- 5.93 mm Hg to 9.71 +/- 2.63 mm Hg; P =.0001; and 23 +/- 7.16 mm Hg to 11.2 +/- 2.55 mm Hg; P = 0.0001, respectively). Systolic and diastolic systemic blood pressures increased in the severely failing heart (57.3 +/- 12.8 mm Hg to 75.4 +/- 11.2 mm Hg; P =.0001; and 35.6 +/- 8.2 mm Hg to 60 +/- 14.3 mm Hg; P =.0006, respectively).

CONCLUSIONS

Hemodynamic data demonstrate the beneficial effects of the intra-aortic cannula pump in moderate and severe heart failure. The intra-aortic cannula pump represents a new modality for the treatment of acute heart failure.

The enabler cannula pump: a novel circulatory support system

BACKGROUND

The enabler circulatory support system is a catheter pump which expels blood from the left or right ventricular cavity and provides pulsatile flow in the ascending aorta or pulmonary artery. It is driven by a bedside installed pulsatile driving console. The device can easily be implanted by a minimal invasive approach, similar to the Hemopump.

PURPOSE

To demonstrate the hemodynamic performance of this new intracardiac support system.

METHODS

In a series of 9 sheep, hemodynamic evolutions were recorded in various conditions of myocardial contractility (the non-failing, the moderately failing and the severely failing heart). Heart failure was induced by injection of microspheres in the coronary arteries.

RESULTS

Introduction of the cannula through the aortic valve was feasible in all cases. Pump flow by the enabler was gradually increased to a maximum of 3.5 L/min. Diastolic (and mean) aortic blood pressure is significantly increased in the non-failing and moderately failing condition (counterpulsation mode). In heart failure, cardiac output is significantly increased by the pump (p < 0.0001). A drop in left atrial pressure (indicating unloading) is achieved in all conditions but reaches significant levels only during heart failure (p=0.0068).

CONCLUSIONS

This new circulatory support system contributes to stabilization of the circulation in the presence of cardiac unloading. In heart failure it actually supports the circulation by increasing cardiac output and perfusion pressure.

Miniaturized implantable rotary blood pump in atrial-aortic position supports and unloads the failing heart

The purpose of this study was to test the pump performance of a miniaturized, newly developed, implantable rotary blood pump (the diagonal pump). In a series of six sheep, the pump was interposed in an atrial-aortic connection. Heart failure was induced by serial injection of glass beads into the left coronary artery. The assistance of the non-failing heart (with pump output up to 4.5 liter/min) did not change the total cardiac output or the blood pressure of the animal. The heart was significantly unloaded as demonstrated by a drop in first derivative of the left ventricular pressure (dP/dt) max (from 1645 to 1113 mmHg/s; P = 0.0003). Because of the specific interaction between heart function and rotary blood pump performance, the pump provided considerably more flow in the failing than in the non-failing heart. Cardiac output and perfusion pressures were restored to pre-assist values in the failing heart model. The heart-rotary blood pump interaction is an ideal substrate for long-term assistance. With this miniaturized rotary blood pump, hemodynamics in a severely failing heart can be restored. Atrial cannulation, which leaves the left ventricle untouched, provides similar results as apical cannulation in the failing heart.

Organ perfusion with Hemopump device assistance with and without intraaortic balloon pumping

OBJECTIVE

Our objective was to analyze the potential advantage of combining an intraaortic balloon pump with a transthoracic Hemopump device (Medtronic, Inc., Minneapolis, Minn.) (Nimbus Medical, Inc., Rancho Cordova, Calif.).

METHODS

Twelve sheep underwent implantation of a transthoracic Hemopump device and an intraaortic balloon pump. In the first series (n = 6), we analyzed the influence of the counterpulsation on the performance of the Hemopump device. In the second group (n = 6), hemodynamic changes, myocardial wall thickening, organ perfusion, and myocardial perfusion (determined with colored microspheres) were analyzed under the following conditions: (1) control situation, (2) during application of coronary stenosis, (3) during support with the Hemopump device, and (4) during support with the Hemopump device combined with intraaortic balloon pump support.

RESULTS

In the first series, we found that addition of counterpulsation reduced output with the Hemopump device by 11.1% +/- 6%. In the second series, it was shown that coronary stenosis significantly reduced contractility (rate of pressure change and wall thickening) but did not cause hemodynamic collapse. Myocardial blood flow was significantly reduced in the poststenotic subendocardial regions (mean subendocardial blood flow dropped from 78 +/- 33 to 24 +/- 17 ml/min/100 gm; p = 0.0486). Support with the Hemopump device alone improved the ratio of subendocardial to subepicardial blood flow, but endocardial underperfusion remained (analysis of variance, p < 0.001). The Hemopump device with an intraaortic balloon pump completely restored perfusion in poststenotic regions. Peripheral organ perfusion did not change during ischemia or mechanical support.

CONCLUSIONS

The association of balloon counterpulsation with the Hemopump device reduces the Hemopump output by 11% and increases myocardial blood flow to ischemic regions. Perfusion to peripheral organs remains unaltered. The transthoracic Hemopump device combined with an intraaortic balloon pump is an ideal support system for the ischemic, failing heart.

Identification of aldosterone secretion inhibitory factor in bovine adrenal medulla

We report the first demonstration of an Aldosterone Secretion Inhibitory Factor (ASIF) in acid extracts of bovine adrenal medulla. Following separation from catecholamines and enkephalins, this factor leads to an 80% inhibition of PGE1-stimulated secretion of aldosterone from bovine adrenal zona glomerulosa. ASIF is retained on cation exchange gels and behaves as a small 5K-dalton peptide on Sephadex G-50. This factor cross-reacts in a radio-receptor assay for [125I] atrial natriuretic factor (ANF). ASIF is distinct from all neuropeptides formerly detected in the adrenal medulla, e.g. somatostatin, enkephalin, neuropeptide Y, dynorphin, neurotensin. In the adrenal gland, this ANF-like factor is predominantly found in the medulla (4 pmol/mg protein), with only trace amounts in the cortex (0.1 pmol/mg protein). ASIF might perhaps correspond to the endogenous ligand for the receptor sites that we have previously identified with [125I]ANF in bovine adrenal cortex and could contribute to the formerly reported attenuating influence of the adrenal medulla on mineralocorticoid production.