Presentation to Diane Litman's lab at the University of Pittsburgh about modeling and acquiring evidence for the Drug Interaction Knowledge Base (DIKB) project.
Medication safety as a use case for argumentation mining, Dagstuhl seminar 16...jodischneider
Medication safety as a use case for argumentation mining
We present a use case for argumentation mining, from biomedical informatics, specifically from medication safety. Tens of thousands of preventable medical errors occur in the U.S. each year, due to limitations in the information available to clinicians. Current knowledge sources about potential drug-drug interactions (PDDIs) often fail to provide essential management recommendations and differ significantly in their coverage, accuracy, and agreement. The Drug Interaction Knowledge Base Project (Boyce, 2006-present; dikb.org) is addressing this problem.
Our current work is using knowledge representations and human annotation in order to represent clinically-relevant claims and evidence. Our data model incorporates an existing argumentation-focused ontology, the Micropublications Ontology. Further, to describe more specific information, such as the types of studies that allow inference of a particular type of claim, we are developing an evidence-focused ontology called DIDEO--Drug-drug Interaction and Drug-drug Interaction Evidence Ontology. On the curation side, we will describe how our research team is hand-extracting knowledge claims and evidence from the primary research literature, case reports, and FDA-approved drug labels for 65 drugs.
We think that medication safety could be an important domain for applying automatic argumentation mining in the future. In discussions at Dagstuhl, we would like to investigate how current argumentation mining techniques might be used to scale up this work. We can also discuss possible implications for representing evidence from other biomedical domains.
Talk for Dagstuhl Seminar 16161: Natural Language Argumentation: Mining, Processing, and Reasoning over Textual Arguments
http://www.dagstuhl.de/en/program/calendar/semhp/?semnr=16161
Prof. Boyce discusses the "Linked SPLs" system its relationship to SPLs stored in DailyMed and the OpenFDA initiative. The talk will focus on the potential uses, strengths, and limitations Linked SPLs which represents drug product labeling as Semantic Web Linked Data.
Video of this talk can be found at the link below starting at starts at 3:11:26: http://videocast.nih.gov/summary.asp?Live=14776&bhcp=1
Pharmacogenomics annotation in drug structured product labeling for clinical ...Richard Boyce, PhD
Prof. Boyce presents work on a semantic model for clinical pharmacogenomics statements in structured product labeling (SPLs) and how it can be integrated into clinical decision support.
See a video of the talk starting at 32:04 at the following link: http://videocast.nih.gov/summary.asp?Live=14776&bhcp=1
An overview of the research aims for the National Library of Medicine funded research project titled "Addressing gaps in clinically useful evidence on drug-drug interactions" (1R01LM011838-01)
Towards a foundational representation of potential drug-drug interaction know...Mathias Brochhausen
Inadequate representation of evidence and knowledge about potential drug-drug interactions is a major factor underlying disagreements among sources of drug information that are used by clinicians. In this paper we describe the initial steps toward developing a foundational domain representation that allows tracing the evidence underlying potential drug-drug interaction knowledge. The new representation includes biological and biomedical entities represented in existing ontologies and terminologies to foster integration of data from relevant fields such as physiology, anatomy, and laboratory sciences.
Orientation and Adaptation for Post-Graduate Pharmacy ProgramsBhaswat Chakraborty
PG Pharmacy programs are more focused and professionally oriented than the undergraduate counterpart. Many soft skills are required along with the curricular competence for excellence at the PG level.
Medication safety as a use case for argumentation mining, Dagstuhl seminar 16...jodischneider
Medication safety as a use case for argumentation mining
We present a use case for argumentation mining, from biomedical informatics, specifically from medication safety. Tens of thousands of preventable medical errors occur in the U.S. each year, due to limitations in the information available to clinicians. Current knowledge sources about potential drug-drug interactions (PDDIs) often fail to provide essential management recommendations and differ significantly in their coverage, accuracy, and agreement. The Drug Interaction Knowledge Base Project (Boyce, 2006-present; dikb.org) is addressing this problem.
Our current work is using knowledge representations and human annotation in order to represent clinically-relevant claims and evidence. Our data model incorporates an existing argumentation-focused ontology, the Micropublications Ontology. Further, to describe more specific information, such as the types of studies that allow inference of a particular type of claim, we are developing an evidence-focused ontology called DIDEO--Drug-drug Interaction and Drug-drug Interaction Evidence Ontology. On the curation side, we will describe how our research team is hand-extracting knowledge claims and evidence from the primary research literature, case reports, and FDA-approved drug labels for 65 drugs.
We think that medication safety could be an important domain for applying automatic argumentation mining in the future. In discussions at Dagstuhl, we would like to investigate how current argumentation mining techniques might be used to scale up this work. We can also discuss possible implications for representing evidence from other biomedical domains.
Talk for Dagstuhl Seminar 16161: Natural Language Argumentation: Mining, Processing, and Reasoning over Textual Arguments
http://www.dagstuhl.de/en/program/calendar/semhp/?semnr=16161
Prof. Boyce discusses the "Linked SPLs" system its relationship to SPLs stored in DailyMed and the OpenFDA initiative. The talk will focus on the potential uses, strengths, and limitations Linked SPLs which represents drug product labeling as Semantic Web Linked Data.
Video of this talk can be found at the link below starting at starts at 3:11:26: http://videocast.nih.gov/summary.asp?Live=14776&bhcp=1
Pharmacogenomics annotation in drug structured product labeling for clinical ...Richard Boyce, PhD
Prof. Boyce presents work on a semantic model for clinical pharmacogenomics statements in structured product labeling (SPLs) and how it can be integrated into clinical decision support.
See a video of the talk starting at 32:04 at the following link: http://videocast.nih.gov/summary.asp?Live=14776&bhcp=1
An overview of the research aims for the National Library of Medicine funded research project titled "Addressing gaps in clinically useful evidence on drug-drug interactions" (1R01LM011838-01)
Towards a foundational representation of potential drug-drug interaction know...Mathias Brochhausen
Inadequate representation of evidence and knowledge about potential drug-drug interactions is a major factor underlying disagreements among sources of drug information that are used by clinicians. In this paper we describe the initial steps toward developing a foundational domain representation that allows tracing the evidence underlying potential drug-drug interaction knowledge. The new representation includes biological and biomedical entities represented in existing ontologies and terminologies to foster integration of data from relevant fields such as physiology, anatomy, and laboratory sciences.
Orientation and Adaptation for Post-Graduate Pharmacy ProgramsBhaswat Chakraborty
PG Pharmacy programs are more focused and professionally oriented than the undergraduate counterpart. Many soft skills are required along with the curricular competence for excellence at the PG level.
Basics of Publishing by Dr Animesh Jain @Pharmaquest 2021Animesh Jain
This presentation was done at Pharmaquest 2021 organized by Vydehi Medical College, Bengaluru on 5th August 2021. This was aimed at motivating and informing the undergraduates, postgraduate residents and PhD Scholars about the Basics of Publishing. This 40 minute capsule is in a simple and easy to understand format covering the Why, What, When, Where, Who and How of Publishing.
Clinical study types and designs are terms which represent the way in which clinical trials are structured and formulated.
Since we all know that clinical research is an extremely complex topic and not everything can be explained in a simple way, here we’ll focus only on some of the most basic types of clinical study types and designs which involve human subjects or participants.
First of all, you should know that the most basic grouping of study designs is experimental (treatment) studies and observational studies.
As we can suppose from the names, in an observational study, researchers have less control over subjects and they’re just observing what happens to subjects, while in experimental studies, researchers are using different methods (such as randomization) to place subjects in separate groups. This gives experimental studies much more validity than observational studies.
In this guide, we’ll talk about the 2 possible types of studies, as well as different study designs within.
This presentation is aimed at presenting the issues associated with subgroup analyses in clinical trials: the different types of subgroup analyses and the statistical issues associated with the conduct of subgroup analyses.
Basics of Publishing by Dr Animesh Jain @Pharmaquest 2021Animesh Jain
This presentation was done at Pharmaquest 2021 organized by Vydehi Medical College, Bengaluru on 5th August 2021. This was aimed at motivating and informing the undergraduates, postgraduate residents and PhD Scholars about the Basics of Publishing. This 40 minute capsule is in a simple and easy to understand format covering the Why, What, When, Where, Who and How of Publishing.
Clinical study types and designs are terms which represent the way in which clinical trials are structured and formulated.
Since we all know that clinical research is an extremely complex topic and not everything can be explained in a simple way, here we’ll focus only on some of the most basic types of clinical study types and designs which involve human subjects or participants.
First of all, you should know that the most basic grouping of study designs is experimental (treatment) studies and observational studies.
As we can suppose from the names, in an observational study, researchers have less control over subjects and they’re just observing what happens to subjects, while in experimental studies, researchers are using different methods (such as randomization) to place subjects in separate groups. This gives experimental studies much more validity than observational studies.
In this guide, we’ll talk about the 2 possible types of studies, as well as different study designs within.
This presentation is aimed at presenting the issues associated with subgroup analyses in clinical trials: the different types of subgroup analyses and the statistical issues associated with the conduct of subgroup analyses.
Contribution of metabolites to the drug drug interactionRx Ravi Goyani
1. The contribution of drug metabolites to the drug drug interaction presented by RAVI GOYANI M.S(Pharm)pharmaceutics(NIPER).
2. Contents of the presentation: Introduction, Drug-drug interaction, regulatory perspectives of drug-drug interaction, potential pharmacokinetic interaction produced by metabolites, case study, evaluation of metabolites to drug interaction, conclusion , references.
3. Introduction of metabolites and its examples.
4.Types of metabolites and how its formation in to the body by phase 1&2 metabolism.
5.Types of drug drug interaction.
6.7. Short discussion about the pharmacokinetics drug interation which are essential for the preclinical pharmacokinetics drug interaction.
8. Regulatory perspective on the metabolites contribution to the drug drug interaction.
9. Criteria for the absence of a based drug interaction on the results of a clinical study.
10.11.12. Case study of the some drug metabolites(efavirenz, verapamil) participate in to the drug drug interaction by the known mechanism such as irreversible of CYP 450 enzymes bye protein adduct formation or intermediate complex formation.
13. Evaluation of metabolites drug interaction by following study.
1. Estimation of metabolites concentration
2. Metabolites and parent cytochrome P450 inhibition potency comparison
3. RMet strategy
14.15.16. Brief discussion about the evaluation and specific criteria for that evaluation parameters which are considering for the metabolites drug interaction.
17. Proposed algorithm for the evaluation of drug metabolites interaction.
18. Conclusion.
19. List of references.
Presentation gives an overview of the inter-relationship between nutrition and pharmacy. Its importance is an imperative consideration in patient care. The presentation begins with an introduction to both areas but then focuses on specific drug-nutrient interactions with specific drug categories.
Identify primary drug interaction concepts
Describe types and mechanisms of interactions
Identify drug interactions commonly encountered with antiretroviral drugs
Describe how to manage known interactions
A drug interaction is a situation in which a substance affects the activity of a drug, i.e. the effects are increased or decreased, or they produce a new effect that neither produces on its own.
pharmacist patient education and counseling Hemat Elgohary
Lack of sufficient knowledge about their health problems and medications cause of patients’ non-adherence to their pharmaco-therapeutic regimens and monitoring plans so pharmacist need to have skills and knowledge to improve patient adherence and reduce medication-related problems
discusses about the interaction of certain drugs with some food materials and explains in detail about the effect of food on absorption, distribution, metabolism and excretion. Also dicsussed about the pharmacodynamic and pharmacogenomic aspects
Toward a reliable and interoperable public repository for natural product-dru...Richard Boyce, PhD
A poster presented at the 2017 Annual Symposium of the American Medical Informatics Association (AMIA 2017). November 04- 08, 2017. Washington, DC. USA
An overview of the book to be published by Wiley "Collaborative Computational Technologies for the Life Sciences" Edited by Sean Ekins, M.Sc., Ph.D., D.Sc., Maggie A.Z. Hupcey Ph.D. and Antony J. Williams, Ph.D. published by Wiley, as part of the Technologies for the Pharmaceutical Industry Series
The Transtheoretical Model also called the Stages
of Change model,7 describes how such behavior
change often occurs. The model emphasizes the
need to understand the experience of the person we
are trying to reach in order to help them. To promote
change, interventions must be provided that are
appropriate for the stage in the process that people
are in."
"Meet people where they are:
The guiding principle of “meeting people where
they are” means more than showing compassion
or tolerance to people in crisis. This principle also
asks us to acknowledge that all people we meet are
at different stages of behavior change."
SLC CME- Evidence based medicine 07/27/2007cddirks
Saint Luke's Care, a quality improvement organization within Saint Luke's Health System, presents a CME presentation by Dr. Brent Beasley on Evidence Based Medical Care.
A Promulgation Of Incredulity In The Pharmaceutical IndustryStuart Silverman
It is simply no longer possible to believe much of the clinical research that is published, or to rely on the judgment of trusted physicians or authoritative medical guidelines.
Target ArticleDisclosing Individual GeneticResults to .docxmattinsonjanel
Target Article
Disclosing Individual Genetic
Results to Research Participants
Vardit Ravitsky, National Institutes of Health1 and University of Pennsylvania
Benjamin S. Wilfond, Social and Behavioral Research Branch, National Human Genome Research Institute,
National Institutes of Health, Bethesda and Department of Clinical Bioethics, The Clinical Center, National
Institutes of Health1 and University of Washington
Investigators and institutional review boards should integrate plans about the appropriate dis-
closure of individual genetic results when designing research studies. The ethical principles of
beneficence, respect, reciprocity, and justice provide justification for routinely offering certain
results to research participants. We propose a result-evaluation approach that assesses the
expected information and the context of the study in order to decide whether results should
be offered. According to this approach, the analytic validity and the clinical utility of a specific
result determine whether it should be offered routinely. Different results may therefore require
different decisions even within the same study. We argue that the threshold of clinical utility for
disclosing a result in a research study should be lower than the threshold used for clinical use
of the same result. The personal meaning of a result provides additional criteria for evaluation.
Finally, the context of the study allows for a more nuanced analysis by addressing the investi-
gators’ capabilities for appropriate disclosure, participants’ alternative access to the result, and
their relationship with the investigators. This analysis shows that the same result may require
different decisions in different contexts.
Keywords
Clinical Utility
Clinical Validity
Disclosure
Research Results
Genetic Research
Open Peer
Commentaries
Lynn G. Dressler
and Eric T. Juengst, 18
Mark A. Rothstein, 20
Lisa S. Parker, 22
Pilar N. Ossorio, 24
Christopher H. Wade
and Andrea L. Kalfoglou, 26
Leslie A. Meltzer, 28
Kelly E. Ormond, 30
Teri A. Manolio, 32
Robert Klitzman, 34
Kelly Fryer-Edwards
and Stephanie M. Fullerton, 36
Laura M. Beskow, 38
Flavia M. Facio, 40
Richard R. Sharp
and Morris W. Foster, 42
Conrad V. Fernandez
and Charles Weijer, 44
Robert R. Lavieri
and Samuel A. Garner, 46
Disclosure of individual results to participants in
clinical and epidemiologic research has emerged as
a complex and contentious issue. The approaches
and practices of investigators, institutional review
boards (IRBs) (Hull et al. 2004), and funding
agencies (Bookman et al. 2006) are quite diverse.
Some argue that disclosure should be the routine
practice in research, based on the principle of re-
spect for participants (Partridge and Winer 2002;
Fernandez, Kodish, and Weijer 2003; Shalowitz
and Miller 2005), while others emphasize the bal-
ance of benefits and harms and argue that disclo-
sure should be limited to certain situations (Fuller
et al. 1999; National Bioethic ...
Generic non-biological complex drugs DIA CMC Workshop 2017Ajaz Hussain
#DIACMC17
Assigned title for the talk by the organizers:“The need of conducting clinical study for assuring safety and efficacy, as well as a lack of immunogenicity for generic NBCDs”
SUMMARY
Integrated analytical, product and process development to reduce uncertainty in ‘pharmaceutical equivalence’ is the foundation on which confidence in generic drugs rests
Need to leverage the context: RLD “Prescribe-ability” and lot-lot “Switchability” is acceptable
The “sameness” mindset (as opposed to an “equivalence” mindset) poses challenges to evidence ‘synthesis” (not “piece meal” check the box ) in ANDA submissions
Integrated evidence must a priori account for posed/anticipated “legal challenges” intrinsic to the US system
Clinical assessment of Therapeutic Equivalence of generic product intended (i.e., designed) to be equivalent to RLD should only be needed in rare circumstances
When there is a need to provide assurance to non-scientists stakeholders
Currently the FDA’s GADUFA Research and efforts by many in the sector are predominantly focused on developing a “test of bioequivalence”
For most complex products such a test, in and of itself, may be insufficient to ensure therapeutic equivalence over generic product life-cycle
Continued citation of bad science and what we can do about it--2021-04-20jodischneider
Continued Citation of Bad Science and What We Can Do About It
Even papers that falsify data continue to be cited. I describe network and text analysis for studying how authors continue to cite bad science: articles retracted from the literature due to serious flaws or errors. I will present an in-depth case study of a human trial cited for over 10 years after it was retracted for falsifying data. Then, I will describe how the team scaled up to study a data set of 7000 retracted papers and hundreds of thousands of citations. Finally, I will discuss an ongoing Sloan-funded stakeholder consultation that is bringing editors, publishers, librarians, researchers, and research integrity experts together to address this problem.
BiographyJodi Schneider is Assistant Professor at the School of Information Sciences, University of Illinois at Urbana-Champaign where she runs the Information Quality Lab. She studies the science of science through the lens of arguments, evidence, and persuasion with a special interest in controversies in science. Her recent work has focused on topics such as systematic review automation, semantic publication, and the citation of retracted papers. Interdisciplinarity (PhD in Informatics, MS Library & Information Science, MA Mathematics; BA Great Books/liberal arts) is a fundamental principle of her work. She has held research positions across the U.S. as well as in Ireland, England, France, and Chile. She leads the Alfred P. Sloan-funded project, Reducing the Inadvertent Spread of Retracted Science: Shaping a Research and Implementation Agenda. With Aaron Cohen and Neil Smalheiser she is working on the NIH R01 "Text Mining Pipeline to Accelerate Systematic Reviews in Evidence-Based Medicine". Talk with her about scoping reviews and about citation-based methods for updating systematic reviews!
Tuesday, April 20th, 2021
Noon-1PM Eastern
GWU - CNHS Informatics Seminar
Continued citation of bad science and what we can do about it--2021-02-19jodischneider
Title: Continued Citation of Bad Science and What We Can Do About It
Abstract: Even papers that falsify data continue to be cited. I describe network and text analysis for studying how authors continue to cite bad science: articles retracted from the literature due to serious flaws or errors. Jodi will present an in-depth case study of a human trial cited for over 10 years after it was retracted for falsifying data. Then, will describe how the team scaled up to study a data set of 7000 retracted papers and hundreds of thousands of citations. Finally, Jodi will discuss an ongoing Sloan-funded stakeholder consultation that is bringing editors, publishers, librarians, researchers, and research integrity experts together to address this problem.
The problems of post retraction citation - and mitigation strategies that wor...jodischneider
Presentation for the Bibliometrics & Research Assessment Symposium 2020 (bibSymp20) https://www.nihlibrary.nih.gov/services/bibliometrics/bibSymp20
October 9, 2020
Retraction is intended to remove articles from the citable literature. However, a series of studies from over 30 years, from 1990 through 2020, have found that many retracted papers continue to be cited, and cited positively, even following misconduct-related retractions. For instance, a fraudulent clinical trial report retracted in 2008 continues to receive citations in 2020, and 96% of post-retraction citations do not mention its citation - perhaps because its retraction not marked on the publisher website and its retraction notice cannot be readily retrieved from 7 out of 8 databases (8 out of 9 database records) we tested. This talk draws an ongoing systematic mapping study of research about retraction and our own research projects to summarize what is known about post-retraction citation in biomedicine. We outline practical steps that authors and reviewers can take to avoid being caught out by poorly marked retracted papers.
20 minutes including Q&A
Towards knowledge maintenance in scientific digital libraries with the keysto...jodischneider
JCDL2020 full paper.
Abstract:
Scientific digital libraries speed dissemination of scientific publications, but also the propagation of invalid or unreliable knowledge. Although many papers with known validity problems are highly cited, no auditing process is currently available to determine whether a citing paper’s findings fundamentally depend on invalid or unreliable knowledge. To address this, we introduce a new framework, the keystone framework, designed to identify when and how citing unreliable findings impacts a paper, using argumentation theory and citation context analysis. Through two pilot case studies, we demonstrate how the keystone framework can be applied to knowledge maintenance tasks for digital libraries, including addressing citations of a non-reproducible paper and identifying statements most needing validation in a high-impact paper. We identify roles for librarians, database maintainers, knowledge base curators, and research software engineers in applying the framework to scientific digital libraries.
doi:10.1145/3383583.3398514
Preprint: http://jodischneider.com/pubs/jcdl2020.pdf
Methods Pyramids as an Organizing Structure for Evidence-Based Medicine--SIGC...jodischneider
Keynote talk 2020-08-01 for the JCDL Workshop on Conceptual Models: https://sig-cm.github.io/news/JCDL-2020-CFP/
Discussion points:
* Methods are a key part of the Knowledge Organizing Structure for Evidence-Based Medicine.
* Methods relate to how we GENERATE evidence.
* Different methods generate evidence of different kinds and strength.
* I believe Methods can be useful in mining claims and arguments from papers: methods AUTHORIZE claims.
* More specialized hierarchies of evidence can be found in medicine
* Various groups are complicating the “evidence pyramid” hierarchy of evidence.
Annotation examples. This is an overview of some of the software I have used for annotation (and a few extra features some of this software has.) This was presented in the SwissUniversities Doctoral Programme, Language & Cognition, in the Module: Linguistic and corpus perspectives on argumentative discourse.
Screenshots are given of GATE, UAM Corpus Tool, Excel, BRAT, EPPI Reviewer, and a custom tool. In most cases there are references to one of my papers for further details.
I briefly describe a typical annotation process:
Find text of interest
Find phenomena of interest
Draft an annotation manual
Iteratively test annotation & revise manual
Find questionable annotations, check disagreements.
Revise the manual.
Iterate.
Annotate
Argumentation mining--an introduction for linguists--Fribourg--2019-09-02jodischneider
An introduction to argumentation mining for PhD students. This was presented in the SwissUniversities Doctoral Programme, Language & Cognition, in the Module: Linguistic and corpus perspectives on argumentative discourse. The presentation largely follows Chapters 1-4 and Chapter 10 of my book, Argumentation Mining, co-authored with Manfred Stede in the Synthesis Lectures on Human Language Technologies from Morgan & Claypool: https://doi.org/10.2200/S00883ED1V01Y201811HLT040
Topics:
My book w/computational linguist Manfred Stede: Argumentation Mining
What is argumentation?
Argumentation mining: a first look
Argumentative language
Challenges for argumentation mining
Argumentation structures
Corpus annotation
Why study argumentation mining?
Beyond Randomized Clinical Trials: emerging innovations in reasoning about he...jodischneider
Talk at the 3rd European Conference on Argumentation
ABSTRACT: Specialized fields may at any time invent new inference rules—that is, new warrants—to improve on their stock of resources for drawing and defending conclusions. Yet disagreement over the acceptability of an invented warrant can always be re-opened. Randomized Clinical Trial is widely regarded as the gold standard for making inferences about causal relationships between medical treatments and patient outcomes. Once controversial, RCT achieved broad acceptance within the field as a result of warrant-establishing arguments circulating in the medical literature starting in the 1950s. And RCT has accumulated a very impressive track record of generating new conclusions that withstand critical scrutiny.
Here we look at two emerging innovations whose purpose is to support reasoning about health, offering ways to generate different classes of conclusions. These innovations could be seen as complementary to RCTs, but for both there are also hints of challenge to the enormous prestige of RCTs. We see this most particularly in the gap that has developed between the RCT-generated fact base and the decisions doctors and health policy officials have to make about treatments for patients. We’ve mentioned before that specialized inference methods that become stabilized within an expert community can meet unexpected challenges when they become components of reasoning by other communities. The two innovations considered here each allow us to explore the tensions that arise from the contrasting perspectives of scientists, clinicians, and patients.
Publishers are caretakers of science. Part of that work is maintaining the integrity of scientific literature. Science builds directly upon past work, so we need to be sure that we are building upon a solid foundation and not faulty research. Publishers need to take an active role in monitoring and tracking faulty, retracted research and its influence. I'm asking publishers to (1) clearly mark retracted papers; (2) alert authors who have already cited a retracted paper; and (3) before publishing an article, check its bibliography for retracted papers.
Retracted papers should be clearly marked everywhere they appear, but today that is not the case. Publishers can also use the CrossRef CrossMark service, which lets readers check for article updates (such as retraction) from a little red ribbon at the top of an article. Checking for citations to retracted articles, and limiting future citations, can help science self-correct by shoring up its foundations.
The structure of citation networks provides evidence about how scientific information is diffused. Problematic citation patterns include the selective citation of positive findings, citation bias, as well as the continued citation of retracted literature (i.e. literature formally withdrawn due to error, fraud, or ethical problems). For instance, there is some evidence that positive results tend to receive more citations. The public domain licensing of the Open Citations Corpus makes it possible, in principle, to estimate the likelihood that any network of research papers suffers from problematic citation. To-date, problematic citation been documented ad-hoc, in several striking studies. In Alzheimer's disease research, biased citation, ignoring critical findings, was used to support successful U.S. NIH grant proposals (Greenberg 2009). Mistranslation of obesity research has been used to justify exertion game research (Marshall & Linehan 2017). Citation of fraudulent research about Chronic Obstructive Pulmonary Disease continued after its retraction (Fulton et al. 2015). The data resulting from such studies is of great use to my lab in replicating and determining how to generalize the detection of problematic citation patterns. Previously, the detection of problematic citation patterns has been a side effect of astute researchers, noticing suspicious findings while conducting systematic literature reviews. This talk will describe work-in-progress in my lab detecting problematic citation patterns using natural language processing, combined with network analysis on the Open Citations Corpus.
Modeling Alzheimer’s Disease research claims, evidence, and arguments from a ...jodischneider
Presentation: Jodi Schneider and Novejot Sandhu, “Modeling Alzheimer’s Disease Reseach Claims, Evidence, and Arguments from a Biology Research Paper.” 9th International Conference on Argumentation, International Society for the Society of Argumentation, Amsterdam, Netherlands, July 5, 2018
Abstract: Argument visualization may help make research papers easier to understand, which could both speed quality assessment within a discipline and help build interdisciplinary knowledge networks. This paper presents a case study of the arguments in a single high-profile paper on Alzheimer's disease research. Within this one paper, we analyze and hand-annotate the main claim, which is supported by 4 subclaims, in turn supported by data, methods, and materials. We also investigate how the paper imports and uses knowledge claims from other research papers. We create a specialized argument-based knowledge representation called a micropublication. In future work, we will investigate automatic argumentation mining for experimental biology research papers. Our long-term vision is to create literature-scale claim-argument networks that help more quickly use new knowledge about human health.
Innovations in reasoning about health: the case of the Randomized Clinical Tr...jodischneider
Presentation: Jodi Schneider and Sally Jackson, “Innovations in Reasoning About Health: The Case of the Randomized Clinical Trial.” 9th International Conference on Argumentation, International Society for the Society of Argumentation, Amsterdam, Netherlands, July 5, 2018
Abstract: Field-dependence in argumentation comes about through forms of inference invented by specialized fields. In recent work we introduced the concept of a "warranting device": (1) an inference license (2) invented for a specialized argumentative purpose and (3) backed by institutional, procedural, and material assurances of the dependability of conclusions generated by the device. Once established, fields employ such devices across many situations without further defense, even as the devices develop in response to newly-noticed problems.
Many new warranting devices have appeared over the past century to solve problems in reasoning about health and medicine, replacing and obsolescing earlier forms of medical reasoning. One such device is the Randomized Controlled Trial. This case study traces its historical evolution and discusses some current movements toward competing device types.
Rhetorical moves and audience considerations in the discussion sections of ra...jodischneider
European Conference on Argumentation talk
Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu “Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions” [Conference Panel Presentation], 2nd European Conference on Argumentation: Argumentation and Inference, Fribourg, Switzerland, June 20-23
1 of 3 talks in Jodi Schneider and Sally Jackson, organizers, “Innovations in Reasoning and Arguing about Health ”[Conference Panel], 2nd European Conference on Argumentation: Argumentation and Inference, Fribourg, Switzerland, June 20-23.
Citation practices and the construction of scientific fact--ECA-facts-preconf...jodischneider
Citation practices and the construction of scientific fact. Presentation at the European Conference on Argumentation preconference on status, relevance, and authority of facts.
What WikiCite can learn from biomedical citation networks--Wikicite2017--2017...jodischneider
This is a quick, high-level tour of some ideas from evidence-based medicine, citation-related ontologies for argumentation and evidence curation and biomedicine.
Persons, documents, models: organising and structuring information for the We...jodischneider
A talk for the Moore Institute for Humanities -
People and documents are of enduring interest. Documents may be generated by individuals, collective groups, and administrations, on any number of topics. We are particularly interested in the relationships between people and documents. The most important relationships are creation (authors, illustrators, translators, ...), usage (e.g. association copies), and topic-of (e.g. people may be the subjects of biographies).
In this lecture, we will talk about several approaches for modeling, or representing, people and documents. We pay particular attention to computer-based approaches to organization, and to organizing information for websites. We will talk briefly about TEI and XML, and the focus on my area of research expertise: modeling "linked data", a widely adopted approach for interlinking data. Adopted by the UK and US governments and search engines such as Google and Yahoo!, linked data has also been widely used in the digital humanities and by libraries, archives, and museums. It consists in naming objects of interest (be they authors, documents, or whatnot) and using standard data formats to enable interlinking.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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Bob Boule
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Acquiring and representing drug-drug interaction knowledge and evidence, Litman Lab, University of Pittsburgh, 2016-03-29
1. Acquiring and representing drug-
drug interaction
knowledge and evidence
Jodi Schneider
March 29, 2016
Litman Lab, CS, University of Pittsburgh
2. Problem
o Thousands of preventable medication errors occur
each year.
o Clinicians rely on information in drug compendia
(Physician’s Desk Reference, Medscape,
Micromedex, Epocrates, …).
o Compendia have information quality problems:
• differ significantly in their coverage, accuracy, and
agreement
• often fail to provide essential management
recommendations about prescription drugs
2
4. Prescribers consult drug interaction references
which are maintained by expert pharmacists.
Medscape EpocratesMicromedex 2.0
4
5. Prescribers consult drug interaction references
which are maintained by expert pharmacists.
Medscape EpocratesMicromedex 2.0
5
6. Problem
o Drug Compendia synthesize PDDI evidence into
knowledge claims but:
• Disagree on whether specific evidence items can support
or refute PDDI knowledge claims
7. Problem
o Drug Compendia synthesize PDDI evidence into
knowledge claims but:
• Disagree on whether specific evidence items can support
or refute PDDI knowledge claims
• May fail to include important evidence
9. Goals
o Long-term, provide drug compendia editors with
better information and better tools, to create the
information clinicians use.
o This talk focuses on how we might efficiently
acquire and represent
• knowledge claims about medication safety
• and their supporting evidence
o in a standard computable format.
11. Definitions
o Drug-drug interaction
• A biological process that results in a clinically
meaningful change to the response of at least one co-
administrated drug.
o Potential drug-drug interaction
• POSSIBILITY of a drug-drug interaction
• Data from a clinical/physiological study OR reasonable
extrapolation about drug-drug interaction mechanisms
11
12. Existing approaches: Representation
Bradford-Hill criteria (1965)
1. Strength
2. Consistency
3. Specificity
4. Temporality
5. Biological gradient
6. Plausibility
7. Coherence
Bradford-Hill A. The Environment and Disease: Association or Causation?.
Proc R Soc Med. 1965;58:295-300.
12
13. Existing approaches: Representation
Horn, J. R., Hansten, P. D., & Chan, L. N. (2007). Proposal for a new tool to evaluate
drug interaction cases. Annals of Pharmacotherapy, 41(4), 674-680.
13
14. Existing approaches: Representation
Royal Dutch Association for the Advancement of
Pharmacy (2005)
1. Existence & quality of evidence on the interaction
2. Clinical relevance of the potential adverse reaction
resulting from the interaction
3. Risk factors identifying patient, medication or disease
characteristics for which the interaction is of special
importance
4. The incidence of the adverse reaction
Van Roon, E.N. et al: Clinical relevance of drug-drug interactions:
a structured assessment procedure. Drug Saf. 2005;28(12):1131-9.
14
18. Why is a new data model needed?
o Need computer integration
o Want a COMPUTABLE model that can make
inferences
18
19. Multiple layers of evidence
Medication Safety
Studies Layer
Clinical Studies and
Experiments
Scientific Evidence Layer
19
20. Scientific Evidence Layer: Micropublications
20
Clark, Ciccarese, Goble (2014) Micropublications: a semantic model for claims, evidence, arguments and
annotations in biomedical communications
34. Hand-extracting knowledge claims and
evidence
o Sources
• Primary research literature
• Case reports
• FDA-approved drug labels
o Process
• Spreadsheets
• PDF annotation
34
39. We are developing a search/retrieval portal
It will:
o Integrate information (removing silos)
o Offer the same information to all compendium
editors
o Provide direct access to information
• E.g. quotes in context
41. Evaluation plan for the search/retrieval portal
o 20-person user study
o Measures of
• Completeness of information
• Level of agreement
• Time required
• Perceived ease of use
42. Implications
o Implications for evidence modeling & curation
o Implications for ontology development.
o Implications for improving medication safety.
43. Implications for evidence modeling &
curation
o Evidence modeling & curation is a general process.
o Analogous processes could be used in other fields.
o Biomedical curation is most mature: structured
nature of the evidence interpretation, existing
ontologies, trained curators, information extraction
and natural language processing pipelines
o Curation pipelines need to be designed with
stakeholders in mind.
44. Thanks to collaborators & funders
o Training grant T15LM007059 from the National
Library of Medicine and the National Institute of
Dental and Craniofacial Research
o The entire “Addressing gaps in clinically useful
evidence on drug-drug interactions” team from U.S.
National Library of Medicine R01 grant
(PI, Richard Boyce; R01LM011838) and other
collaborators
44
45. “Addressing gaps in clinically useful
evidence on drug-drug interactions”
4-year project, U.S. National Library of Medicine R01
grant
(PI, Richard Boyce; R01LM011838)
o Evidence panel of domain experts: Carol Collins,
Amy Grizzle, Lisa Hines, John R Horn, Phil Empey,
Dan Malone
o Informaticists: Jodi Schneider, Harry Hochheiser,
Katrina Romagnoli, Samuel Rosko
o Ontologists: Mathias Brochhausen, Bill Hogan
o Programmers: Yifan Ning, Wen Zhang, Louisa
Zhang
45
46. Jodi Schneider, Mathias Brochhausen, Samuel Rosko, Paolo Ciccarese,
William R. Hogan, Daniel Malone, Yifan Ning, Tim Clark and Richard D.
Boyce. “Formalizing knowledge and evidence about potential drug-drug
interactions.” International Workshop on Biomedical Data Mining, Modeling,
and Semantic Integration: A Promising Approach to Solving Unmet Medical
Needs (BDM2I 2015) at ISWC 2015 Bethlehem, Pennsylvania, USA.
Jodi Schneider, Paolo Ciccarese, Tim Clark and Richard D. Boyce. “Using the
Micropublications ontology and the Open Annotation Data Model to represent
evidence within a drug-drug interaction knowledge base.” 4th Workshop on
Linked Science 2014—Making Sense Out of Data (LISC2014) at ISWC 2014
Riva de Garda, Italy.
Mathias Brochhausen, Jodi Schneider, Daniel Malone, Philip E. Empey,
William R. Hogan and Richard D. Boyce “Towards a foundational
representation of potential drug-drug interaction knowledge.” First
International Workshop on Drug Interaction Knowledge Representation
(DIKR-2014) at the International Conference on Biomedical Ontologies (ICBO
2014) Houston, Texas, USA.
Richard D. Boyce, John Horn, Oktie Hassanzadeh, Anita de Waard, Jodi
Schneider, Joanne S. Luciano, Majid Rastegar-Mojarad, Maria Liakata,
“Dynamic Enhancement of Drug Product Labels to Support Drug Safety,
Efficacy, and Effectiveness.” Journal of Biomedical Semantics. 4(5), 2013.
doi:10.1186/2041-1480-4-5
47.
48. o Evidence
48
7.19 Drugs Metabolized by Cytochrome P4502D6
In vitro studies did not reveal an inhibitory effect of
escitalopram on CYP2D6.
Editor's Notes
Abstract:
Limitations in the information available to clinicians are a contributing factor to the many thousands of preventable medication errors that occur each year. Current knowledge sources about potential drug-drug interactions (PDDIs) often fail to provide essential management recommendations and differ significantly in their coverage, accuracy, and agreement. To address this, we seek to more efficiently acquire and represent PDDIs knowledge claims and their supporting evidence in a standard computable format.
In this talk we will present work in progress on both representation (a data model) and acquisition (an evidence curation pipeline). Our data model has a reusable generic layer, provided by the Micropublications Ontology, as well as a domain-specific layer represented using the new Drug-drug Interaction and Drug-drug Interaction Evidence Ontology (DIDEO). We will discuss the motivation for our approach and possible implications for representing evidence from other biomedical domains. On the curation side, we will describe how our research team is hand-extracting knowledge claims and evidence from the primary research literature, case reports, and FDA-approved drug labels. This work has implications for ontology development, the design of curation pipelines, and for improving medication safety.
Adverse drug events are a leading cause of death
Image from https://www.njpharmacy.com/wp-content/uploads/2013/02/drug-interactions-checker.png
Image from http://www.clipartbest.com/clipart-McLLpbGKi
Adverse drug events are a leading cause of death
Images from
http://www.knowabouthealth.com/android-version-of-medscape-app-ready-to-download/7568/
Android Play store
http://amazingsgs.blogspot.com/2011/10/top-5-free-android-medical-apps-for.html
Drug Compendia synthesize PDDI evidence into knowledge claims but
May fail to include important evidence
Disagree if specific evidence items can support or refute PDDI knowledge claims
Most sources of clinically-oriented PDDI knowledge disagree substantially in their content,
including about which drug combinations should never be never co-administered. For
example, only one quarter of 59 contraindicated drug pairs were listed in three PDDI
information sources[4], only 18 (28%) of 64 pharmacy information and clinical decisions
support systems correctly identified 13 PDDIs considered clinically significant
by a team of drug interaction experts[5], and four clinically oriented drug information
compendia agreed on only 2.2% of 406 PDDIs considered to be “major” by at least
one source[6].
From our paper: http://ceur-ws.org/Vol-1309/paper2.pdf
4. Wang, L.M., Wong, M., Lightwood, J.M., Cheng, C.M.: Black box
warning contraindicated comedications: concordance among three
major drug interaction screening programs. Ann. Pharmacother. 44,
28–34 (2010).
5. Saverno, K.R., Hines, L.E., Warholak, T.L., Grizzle, A.J., Babits, L.,
Clark, C., Taylor, A.M., Malone, D.C.: Ability of pharmacy clinical
decision-support software to alert users about clinically important
drug-drug interactions. J. Am. Med. Inform. Assoc. JAMIA. 18, 32–
37 (2011).
6. Abarca, J., Malone, D.C., Armstrong, E.P., Grizzle, A.J., Hansten,
P.D., Van Bergen, R.C., Lipton, R.B.: Concordance of severity ratings
provided in four drug interaction compendia. J. Am. Pharm. Assoc.
JAPhA. 44, 136–141 (2004).
Adverse drug events are a leading cause of death
Images from
http://www.knowabouthealth.com/android-version-of-medscape-app-ready-to-download/7568/
Android Play store
http://amazingsgs.blogspot.com/2011/10/top-5-free-android-medical-apps-for.html
Animation here
Product labeling is incomplete
Search strategy
No standard way of searching/assessing the evidence
By reducing the variability in searching (more standardize)
(others working on standardizing assessing evidence)
No standard way to synthesize
DIDEO:
A potential drug-drug interaction (PDDI) is an information content entity that specifies the possibility of a drug-drug interaction based on either reasonable extrapolation about drug-drug interaction mechanisms or a data item created by clinical studies, clinical observation or physiological experiment.
Implementation/specification of Bradford-Hill to DDIs/PDDIs
1. Are there previous credible reports of this interaction in humans?2. Is the observed interaction consistent with the known interactive properties of precipitant drug?3. Is the observed interaction consistent with the known interactive properties of object drug?4. Is the event consistent with the known or reasonable time course of the interaction (onset and/or offset)?
5. Did the interaction remit upon dechallenge of the precipitant drug with no change in the object drug? (if no dechallenge, use Unknown or NA and skip Question 6)
6. Did the interaction reappear when the precipitant drug was readministered in the presence of continued use of object drug?
7. Are there reasonable alternative causes for the event?a8. Was the object drug detected in the blood or other fluids in concentrations consistent with the proposed interaction?9. Was the drug interaction confirmed by any objective evidence consistent with the effects on the object drug (other than drug concentrations from question 8)?10. Was the interaction greater when the precipitant drug dose was increased or less when the precipitant drug dose was decreased?
From http://dailymed.nlm.nih.gov/dailymed/fda/fdaDrugXsl.cfm?setid=13bb8267-1cab-43e5-acae-55a4d957630a&type=display
From http://dailymed.nlm.nih.gov/dailymed/fda/fdaDrugXsl.cfm?setid=13bb8267-1cab-43e5-acae-55a4d957630a&type=display
Evidence entry form from:
https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnxkZGlrcmFuZGlyfGd4OjE0ZGIwY2IwNzJhOWNjMjY