Slides from my talk at the ACS CINF Symposium on Collaborations & Data Sharing in Rare & Orphan Disease Drug Discovery on 31 March 2019 in Orlando.
Abstract:
For the pharmaceutical industry as a whole, addressing the challenge of rare or orphan diseases is high on the agenda. But for the patients and their families, rare diseases can be very isolating and it can often feel like the potential for new treatments is low. One avenue for potential treatments is to identify drug repurposing candidates for the rare disease in question. This talk will give an overview of various collaborative projects undertaken in the last few years, which involved the combination, normalisation and analysis of data from various disparate sources, including some valuable lessons learnt along the way.
Finding novel lead compounds in pesticide discovery inspired by pharmaceutica...Frederik van den Broek
Slides from my talk at the ACS AGRO Symposium on High Throughput Approaches to Support Pesticide Discovery & Development on 29 August 2019 in San Diego.
Abstract:
The use of high throughput (HTP) methodologies for supporting discovery and development of new agrochemical products opens up new opportunities to test many new compounds potentially acting on biological targets in various organisms. Finding new lead compounds which might act as a new pesticide can sometimes be a lengthy process; we present a method which can provide lead compounds by using the breath of information available from pharmaceutical research. This talk will give an overview of the chemical and biological informatics methods and data used to map compounds active against biological targets in parasites in humans to fungal targets. The talk will also explore how AI and Machine Learning techniques recently developed for pharmaceutical research projects can augment these mappings. Thereby demonstrating how findings from pharmaceutical research can be transferred to fungal research.
UDM (Unified Data Model) - Enabling Exchange of Comprehensive Reaction Inform...Frederik van den Broek
Slides from my talk at the ACS CINF Symposium on Chemical Nomenclature & Representation on 26 August 2019 in San Diego.
Abstract:
The first edition of the Beilstein Handbook of Organic Chemistry was published nearly 140 years ago. Electronic laboratory notebooks have been in use in chemistry for almost 20 years. And the life science industry still doesn't have a well-defined way of capturing and exchanging information about chemical reactions and relies on imprecise or vendor-specific data formats. Without a common language and structure to describe experiments, data integration is unnecessarily expensive and a significant part of published data has not been readily available for processing or analysis.
The Unified Data Model (UDM) project team aims to improve the situation. UDM is a collective effort of vendors and life science organizations to create an open, extendable and freely available reference model and data format for exchange of experimental information about compound synthesis and testing. Run under the umbrella of the Pistoia Alliance, the project team has published two releases of the UDM data format and it is expected that the model will continue to be improved as demand stipulates working with the Pistoia FAIR data implementation by industry community.
De-siloing data and building knowledge graphs outside of drug discovery: Oppo...Frederik van den Broek
Slides from my talk at the ACS CINF Symposium on Expanding cheminformatics to adjacent industries on 20 March 2022 in San Diego & online.
Abstract:
Extracting structured data from literature, patents and documents using various text mining techniques and technologies is an established part of the process of building knowledge repositories for drug discovery. There is an increasing interest from research areas outside of drug discovery to make use of such techniques to de-silo data and build knowledge graphs, e.g. for chemical manufacturing, consumer products, and other fields. This talk will give an overview of the opportunities and challenges faced in building up systems to extract the data to build semantic searches and knowledge graphs.
Exploring Chemical and Biological Knowledge Spaces with PubChemPaul Thiessen
My presentation for the Drug Repurposing workshop at the upcoming Bio-IT World Expo.
http://www.bio-itworldexpo.com/Bio-It_Expo_Content.aspx?id=124256
Presentation abstract:
PubChem has a wealth of chemical structure and biological activity information. In conjunction with NCBI’s other resources such as PubMed and GenBank, PubChem is a vast source of information relevant to repurposing not only of established drugs but any compounds with in vivo pharmacology and/or clinical results. The challenge is how to take advantage of this knowledge. The ability to explore not only chemical similarity but relationships between diseases and disease targets has crucial value in repurposing. While focused investigations are already possible within the existing Entrez system, navigation across these linked information spaces can be difficult to do on a large scale with current tools. We are actively developing new infrastructure to support such analyses, and pursuing new methods of exploring inter- and intra-database relationships between chemicals, targets, diseases, and patents. Progress and some future direction in these areas will be presented.
Finding novel lead compounds in pesticide discovery inspired by pharmaceutica...Frederik van den Broek
Slides from my talk at the ACS AGRO Symposium on High Throughput Approaches to Support Pesticide Discovery & Development on 29 August 2019 in San Diego.
Abstract:
The use of high throughput (HTP) methodologies for supporting discovery and development of new agrochemical products opens up new opportunities to test many new compounds potentially acting on biological targets in various organisms. Finding new lead compounds which might act as a new pesticide can sometimes be a lengthy process; we present a method which can provide lead compounds by using the breath of information available from pharmaceutical research. This talk will give an overview of the chemical and biological informatics methods and data used to map compounds active against biological targets in parasites in humans to fungal targets. The talk will also explore how AI and Machine Learning techniques recently developed for pharmaceutical research projects can augment these mappings. Thereby demonstrating how findings from pharmaceutical research can be transferred to fungal research.
UDM (Unified Data Model) - Enabling Exchange of Comprehensive Reaction Inform...Frederik van den Broek
Slides from my talk at the ACS CINF Symposium on Chemical Nomenclature & Representation on 26 August 2019 in San Diego.
Abstract:
The first edition of the Beilstein Handbook of Organic Chemistry was published nearly 140 years ago. Electronic laboratory notebooks have been in use in chemistry for almost 20 years. And the life science industry still doesn't have a well-defined way of capturing and exchanging information about chemical reactions and relies on imprecise or vendor-specific data formats. Without a common language and structure to describe experiments, data integration is unnecessarily expensive and a significant part of published data has not been readily available for processing or analysis.
The Unified Data Model (UDM) project team aims to improve the situation. UDM is a collective effort of vendors and life science organizations to create an open, extendable and freely available reference model and data format for exchange of experimental information about compound synthesis and testing. Run under the umbrella of the Pistoia Alliance, the project team has published two releases of the UDM data format and it is expected that the model will continue to be improved as demand stipulates working with the Pistoia FAIR data implementation by industry community.
De-siloing data and building knowledge graphs outside of drug discovery: Oppo...Frederik van den Broek
Slides from my talk at the ACS CINF Symposium on Expanding cheminformatics to adjacent industries on 20 March 2022 in San Diego & online.
Abstract:
Extracting structured data from literature, patents and documents using various text mining techniques and technologies is an established part of the process of building knowledge repositories for drug discovery. There is an increasing interest from research areas outside of drug discovery to make use of such techniques to de-silo data and build knowledge graphs, e.g. for chemical manufacturing, consumer products, and other fields. This talk will give an overview of the opportunities and challenges faced in building up systems to extract the data to build semantic searches and knowledge graphs.
Exploring Chemical and Biological Knowledge Spaces with PubChemPaul Thiessen
My presentation for the Drug Repurposing workshop at the upcoming Bio-IT World Expo.
http://www.bio-itworldexpo.com/Bio-It_Expo_Content.aspx?id=124256
Presentation abstract:
PubChem has a wealth of chemical structure and biological activity information. In conjunction with NCBI’s other resources such as PubMed and GenBank, PubChem is a vast source of information relevant to repurposing not only of established drugs but any compounds with in vivo pharmacology and/or clinical results. The challenge is how to take advantage of this knowledge. The ability to explore not only chemical similarity but relationships between diseases and disease targets has crucial value in repurposing. While focused investigations are already possible within the existing Entrez system, navigation across these linked information spaces can be difficult to do on a large scale with current tools. We are actively developing new infrastructure to support such analyses, and pursuing new methods of exploring inter- and intra-database relationships between chemicals, targets, diseases, and patents. Progress and some future direction in these areas will be presented.
The internet now offers access to a myriad of online resources that can be of value to chemists working in the Life Sciences. While finding information online is, in many cases, a simple search away, the accuracy and validity of the associated data and information should be questioned. As more databases and resources are introduced online, and commonly not integrated to other resources, a scientist must perform multiple searches and then undertake the task of meshing and merging data. ChemSpider is a freely accessible online database that has taken on the challenge of meshing together distributed resources across the internet to provide a structure-based hub. It is a crowdsourcing environment hosting over 26 million unique compounds linked out to over 400 data sources. With well defined programming interfaces for integration ChemSpider has been integrated to many commercial and open software packages and is presently serving as the chemistry foundation for the IMI Open PHACTS project.
This is a presentation given at the Opal Events meeting ""Drug Discovery Partnerships: Filling the Pipeline". I was speaking in a session with Jean-Claude Bradley regarding "Pre-competitive Collaboration: Sharing Data to Increase Predictability". This presentation discussed some of the work we are doing on Open PHACTS. My thanks especially to Carole Goble, Lee Harland and Sean Ekins for their comments.
A brief history of reaction analytics (CINF 144, ACS National Meeting 2018-08...Frederik van den Broek
These slides are from the opening presentation of the CINF Symposium on Reaction Analytics at the ACS National Meeting in August 2018.
Abstract:
Although the fields of cheminformatics and retrosynthetic analysis have been well established for a number of decades, there has recently been a large increase in applying methods from the world of Big Data and Predictive Analytics to the field of chemical reactions. This presentation gives an overview of the past achievements in the field.
PubChem for chemical information literacy trainingSunghwan Kim
Presented at the American Chemical Society Fall 2021 National Meeting (August 23, 2021; virtual).
==== Abstracts ====
PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public chemical information resource that collects chemical information from 780+ data sources. It is visited by millions of users every month and many of them are young students at academic undergraduate or graduate students at academic institutions. While PubChem has a great potential as an online resource for chemical education, it also has important issues that are not familiar to students and educators, including data accuracy, data provenance, structure standardization, terminologies, etc. In this presentation, various aspects of PubChem as a chemical education resource will be discussed, with a special emphasis on how to help students develop chemical information literacy skills.
Presented at the Fall 2020 American Chemical Society (ACS) National Meeting (Virtual) on August 20, 2020.
Sunghwan Kim, Jian Zhang, Paul Thiessen, Asta Gindulyte, Pertti J. Hakkinen & Evan Bolton
National Library of Medicine, National Institutes of Health, Rockville, Maryland, United States
==== Abstract ====
PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public chemical information resource at the U.S. National Institutes of Health. It collects chemical information from 700+ data sources and disseminates the collected data to the public free of charge. Arguably, PubChem contains the largest amount of chemical information available in the public domain, with more than 250 million depositor-provided substance descriptions, 100 million unique chemical structures, and 265 million bioactivity outcomes from one million assays covering around twenty thousand unique protein target sequences.
Included in the many types of content in PubChem is toxicological information about chemicals, e.g., human and animal toxicity, ecotoxicity, exposure limits, exposure symptoms, and antidote & emergency treatment. Notably, a substantial amount of toxicological information from resources formerly offered by the TOXicology data NETwork (TOXNET) is now integrated into PubChem, e.g., the Hazardous Substances Data Bank (HSDB), LactMed, and LiverTox. In addition, PubChem contains a large amount of bioactivity and toxicity screening data that can be used to build toxicity prediction models based on statistical and machine-learning approaches. This presentation provides an overview of PubChem’s toxicological information as well as tools and services that help users exploit this information. It also describes how open data in PubChem can be used to develop prediction models for chemical toxicity.
Generating Biomedical Hypotheses Using Semantic Web TechnologiesMichel Dumontier
With its focus on investigating the nature and basis for the sustained existence of living systems, modern biology has always been a fertile, if not challenging, domain for formal knowledge representation and automated reasoning. Over the past 15 years, hundreds of projects have developed or leveraged ontologies for entity recognition and relation extraction, semantic annotation, data integration, query answering, consistency checking, association mining and other forms of knowledge discovery. In this talk, I will discuss our efforts to build a rich foundational network of ontology-annotated linked data, discover significant biological associations across these data using a set of partially overlapping ontologies, and identify new avenues for drug discovery by applying measures of semantic similarity over phenotypic descriptions. As the portfolio of Semantic Web technologies continue to mature in terms of functionality, scalability and an understanding of how to maximize their value, increasing numbers of biomedical researchers will be strategically poised to pursue increasingly sophisticated KR projects aimed at improving our overall understanding of the capability and behavior of biological systems.
Searching for patent information in PubChem Sunghwan Kim
Presented at the 256th American Chemical Society (ACS) National Meeting in Boston, MA (August 19, 2018).
==== Abstract ====
PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public chemical information resource, containing more than 242 million chemical substance descriptions, 94 million unique compounds, and 234 million bioactivities determined from 1.25 million assay experiments. Importantly, data contribution from multiple sources, including IBM, SureChEMBL, ScripDB, NextMove, and BindingDB, allows PubChem to provide links to patent documents that mention chemicals. Currently, PubChem offers links between about 6.7 million patent documents and more than 20 million unique chemical structures, with over 137 million compound-patent links, covering primarily U.S. patents with some from European, and World Intellectual Property Organization, and Japanese patent documents. This presentation will provide an overview of the patent information in PubChem as well as the best practice for using it.
PubChem and its application for cheminformatics educationSunghwan Kim
Presented at the American Chemical Society Middle Atlantic Regional Meeting (MARM) 2021 (June 9, 2021).
==== Abstract ====
PubChem (https://pubchem.ncbi.nlm.nih.gov) is a chemical information resource, developed and maintained by the U.S. National Institutes of Health. It contains a large corpus of publicly chemical data collected from more than 700 data sources. Visited by millions of users every month, it serves a wide range of audiences, from scientific communities to the general public. Considering that many PubChem users are undergraduate and graduate students at academic institutions, it has great potential as a cheminformatics education resource. In this presentation, we will give a brief overview of PubChem’s data content, tools, and services. Important aspects of PubChem as cheminformatics education will be discussed, including data quality and accuracy, data provenance and governance, and structure standardization. Besides, we will discuss PubChem’s education and outreach efforts, including the PubChem Laboratory Chemical Safety Summary (LCSS) and the Cheminformatics On-Line Chemistry Course (OLCC).
Automate your literature monitoring for more effective pharmacovigilanceAnn-Marie Roche
Embase and QUOSA experts take you through a complete literature management workflow, demonstrating how Elsevier’s Pharmacovigilance solution enables efficient and comprehensive post-market surveillance.
The internet now offers access to a myriad of online resources that can be of value to chemists working in the Life Sciences. While finding information online is, in many cases, a simple search away, the accuracy and validity of the associated data and information should be questioned. As more databases and resources are introduced online, and commonly not integrated to other resources, a scientist must perform multiple searches and then undertake the task of meshing and merging data. ChemSpider is a freely accessible online database that has taken on the challenge of meshing together distributed resources across the internet to provide a structure-based hub. It is a crowdsourcing environment hosting over 26 million unique compounds linked out to over 400 data sources. With well defined programming interfaces for integration ChemSpider has been integrated to many commercial and open software packages and is presently serving as the chemistry foundation for the IMI Open PHACTS project.
This is a presentation given at the Opal Events meeting ""Drug Discovery Partnerships: Filling the Pipeline". I was speaking in a session with Jean-Claude Bradley regarding "Pre-competitive Collaboration: Sharing Data to Increase Predictability". This presentation discussed some of the work we are doing on Open PHACTS. My thanks especially to Carole Goble, Lee Harland and Sean Ekins for their comments.
A brief history of reaction analytics (CINF 144, ACS National Meeting 2018-08...Frederik van den Broek
These slides are from the opening presentation of the CINF Symposium on Reaction Analytics at the ACS National Meeting in August 2018.
Abstract:
Although the fields of cheminformatics and retrosynthetic analysis have been well established for a number of decades, there has recently been a large increase in applying methods from the world of Big Data and Predictive Analytics to the field of chemical reactions. This presentation gives an overview of the past achievements in the field.
PubChem for chemical information literacy trainingSunghwan Kim
Presented at the American Chemical Society Fall 2021 National Meeting (August 23, 2021; virtual).
==== Abstracts ====
PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public chemical information resource that collects chemical information from 780+ data sources. It is visited by millions of users every month and many of them are young students at academic undergraduate or graduate students at academic institutions. While PubChem has a great potential as an online resource for chemical education, it also has important issues that are not familiar to students and educators, including data accuracy, data provenance, structure standardization, terminologies, etc. In this presentation, various aspects of PubChem as a chemical education resource will be discussed, with a special emphasis on how to help students develop chemical information literacy skills.
Presented at the Fall 2020 American Chemical Society (ACS) National Meeting (Virtual) on August 20, 2020.
Sunghwan Kim, Jian Zhang, Paul Thiessen, Asta Gindulyte, Pertti J. Hakkinen & Evan Bolton
National Library of Medicine, National Institutes of Health, Rockville, Maryland, United States
==== Abstract ====
PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public chemical information resource at the U.S. National Institutes of Health. It collects chemical information from 700+ data sources and disseminates the collected data to the public free of charge. Arguably, PubChem contains the largest amount of chemical information available in the public domain, with more than 250 million depositor-provided substance descriptions, 100 million unique chemical structures, and 265 million bioactivity outcomes from one million assays covering around twenty thousand unique protein target sequences.
Included in the many types of content in PubChem is toxicological information about chemicals, e.g., human and animal toxicity, ecotoxicity, exposure limits, exposure symptoms, and antidote & emergency treatment. Notably, a substantial amount of toxicological information from resources formerly offered by the TOXicology data NETwork (TOXNET) is now integrated into PubChem, e.g., the Hazardous Substances Data Bank (HSDB), LactMed, and LiverTox. In addition, PubChem contains a large amount of bioactivity and toxicity screening data that can be used to build toxicity prediction models based on statistical and machine-learning approaches. This presentation provides an overview of PubChem’s toxicological information as well as tools and services that help users exploit this information. It also describes how open data in PubChem can be used to develop prediction models for chemical toxicity.
Generating Biomedical Hypotheses Using Semantic Web TechnologiesMichel Dumontier
With its focus on investigating the nature and basis for the sustained existence of living systems, modern biology has always been a fertile, if not challenging, domain for formal knowledge representation and automated reasoning. Over the past 15 years, hundreds of projects have developed or leveraged ontologies for entity recognition and relation extraction, semantic annotation, data integration, query answering, consistency checking, association mining and other forms of knowledge discovery. In this talk, I will discuss our efforts to build a rich foundational network of ontology-annotated linked data, discover significant biological associations across these data using a set of partially overlapping ontologies, and identify new avenues for drug discovery by applying measures of semantic similarity over phenotypic descriptions. As the portfolio of Semantic Web technologies continue to mature in terms of functionality, scalability and an understanding of how to maximize their value, increasing numbers of biomedical researchers will be strategically poised to pursue increasingly sophisticated KR projects aimed at improving our overall understanding of the capability and behavior of biological systems.
Searching for patent information in PubChem Sunghwan Kim
Presented at the 256th American Chemical Society (ACS) National Meeting in Boston, MA (August 19, 2018).
==== Abstract ====
PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public chemical information resource, containing more than 242 million chemical substance descriptions, 94 million unique compounds, and 234 million bioactivities determined from 1.25 million assay experiments. Importantly, data contribution from multiple sources, including IBM, SureChEMBL, ScripDB, NextMove, and BindingDB, allows PubChem to provide links to patent documents that mention chemicals. Currently, PubChem offers links between about 6.7 million patent documents and more than 20 million unique chemical structures, with over 137 million compound-patent links, covering primarily U.S. patents with some from European, and World Intellectual Property Organization, and Japanese patent documents. This presentation will provide an overview of the patent information in PubChem as well as the best practice for using it.
PubChem and its application for cheminformatics educationSunghwan Kim
Presented at the American Chemical Society Middle Atlantic Regional Meeting (MARM) 2021 (June 9, 2021).
==== Abstract ====
PubChem (https://pubchem.ncbi.nlm.nih.gov) is a chemical information resource, developed and maintained by the U.S. National Institutes of Health. It contains a large corpus of publicly chemical data collected from more than 700 data sources. Visited by millions of users every month, it serves a wide range of audiences, from scientific communities to the general public. Considering that many PubChem users are undergraduate and graduate students at academic institutions, it has great potential as a cheminformatics education resource. In this presentation, we will give a brief overview of PubChem’s data content, tools, and services. Important aspects of PubChem as cheminformatics education will be discussed, including data quality and accuracy, data provenance and governance, and structure standardization. Besides, we will discuss PubChem’s education and outreach efforts, including the PubChem Laboratory Chemical Safety Summary (LCSS) and the Cheminformatics On-Line Chemistry Course (OLCC).
Automate your literature monitoring for more effective pharmacovigilanceAnn-Marie Roche
Embase and QUOSA experts take you through a complete literature management workflow, demonstrating how Elsevier’s Pharmacovigilance solution enables efficient and comprehensive post-market surveillance.
ASSESSMENT OF BIOMEDICAL LITERATURE
Components of internal and external validity of controlled clinical trials
Internal validity — extent to which systematic error (bias) is minimized in clinical trials
Selection bias: biased allocation to comparison groups
Performance bias: unequal provision of care apart from treatment under evaluation
Detection bias: biased assessment of outcome
Attrition bias: biased occurrence and handling of deviations from protocol and loss to follow up
Requirements, needs
Planning, direction
Information collection
Information Assessment
- Evaluation for accuracy, correctness, relevance, usefulness
- Source reliability assessment (competency and past behavior based)
- Bias assessment (motivators, interests, funding, objectives)
- Conflicts of interest
- Sources of funding, important business relationships
- Grading of individual items (study, report, analysis, article)
Collation of information
- Exclusion of irrelevant, incorrect, and useless information
-Arrangement of information in a form which enables real-time analysis
- System for rapid retrieval of information
External validity — extent to which results of trials provide a correct basis for generalization to other circumstances
Patients: age, sex, severity of disease and risk factors, comorbidity
Treatment regimens: dosage, timing and route of administration, type of treatment within a class of treatments, concomitant treatments
Settings: level of care (primary to tertiary) and experience and specialization of care provider
Modalities of outcomes: type or definition of outcomes and duration of follow up
Mobilizing informational resources for rare diseasesMaria Shkrob
Providing comprehensive disease-specific summaries remains a serious challenge as information is scattered across multiple resources. Elsevier is collaborating with a rare disease charity Findacure to create an informational portal for patients, researchers, and doctors to help finding new treatments, increase awareness, streamline information exchange and education. Using an integrative approach of automated and manual curation of literature, we constructed a knowledgebase containing an overview of the disease mechanisms, targets, drugs, key opinion leaders, and institutions. To demonstrate the utility of this approach, congenital hyperinsulinism will be discussed.
The Learning Health System: Thinking and Acting Across ScalesPhilip Payne
A Learning Health System (LHS) can be defined as an environment in which knowledge generation processes are embedded into daily clinical practice in order to continually improve the quality, safety, and outcomes of healthcare delivery. While still largely an aspirational goal, the promise of the LHS is a future in which every patient encounter is an opportunity to learn and improve that patient’s care, as well as the care their family and broader community receives. The foundation for building such an LHS can and should be the Electronic Health Record (EHR), which provides the basis for the comprehensive instrumentation and measurement of clinical phenotypes, as well as a means of delivering new evidence at the patient- and population levels. In this presentation, we will explore the ways in which such EHR-derived phenotypes can be combined with complementary data across a spectrum from biomolecules to population level trends, to both generate insights and deliver such knowledge in the right time, place, and format, ultimately improving clinical outcomes and value.
Introduce IUON students to evidence-based nursing literature and effective strategies for searching for and accessing evidence-based research in nursing.
The Uneven Future of Evidence-Based MedicineIda Sim
An Apple ResearchKit study enrolled 22,000 people in five days. A
study claims that Twitter can be used to identify depressed patients. A computer program crunches genomic data, the published literature, and electronic health record data to guide cancer treatment. The pace, the data sources, and the methods for generating medical evidence are changing radically. What will — what should — evidence-based medicine look like in a faster, personalized, data-dense tomorrow?
- Presented as the 3rd Annual Cochrane Lecture, October 2015 in Vienna, Austria.
MseqDR consortium: a grass-roots effort to establish a global resource aimed ...Human Variome Project
The success of whole exome sequencing (WES) for highly heterogeneous disorders, such as mitochondrial disease, is limited by substantial technical and bioinformatics challenges to correctly identify and prioritize the extensive number of sequence variants present in each patient. The likelihood of success can be greatly improved if a large cohort of patient data is assembled in which sequence variants can be systematically analysed, annotated, and interpreted relative to known phenotype. This effort has engaged and united more than 100 international mitochondrial clinicians, researchers, and bioinformaticians in the Mitochondrial Disease Sequence Data Resource (MSeqDR) consortium that formed in June 2012 to identify and prioritize the specific WES data analysis needs of the global mitochondrial disease community. Through regular web-based meetings, we have familiarized ourselves with existing strengths and gaps facing integration of MSeqDR with public resources, as well as the major practical, technical, and ethical challenges that must be overcome to create a sustainable data resource. We have now moved forward toward our common goal by establishing a central data resource (http://mseqdr.org/) that has both public access and secure web-based features that allow the coherent compilation, organization, annotation, and analysis of WES and mtDNA genome data sets generated in both clinical- and research-based settings of suspected mitochondrial disease patients. The most important aims of the MSeqDR consortium are summarized in the MSeqDR portal within the Consortium overview sections. Consortium participants are organized in 3 working groups that include (1) Technology and Bioinformatics; (2) Phenotyping, databasing, IRB concerns and access; and (3) Mitochondrial DNA specific concerns. The online MSeqDR resource is organized into discrete sections to facilitate data deposition and common reannotation, data visualization, data set mining, and access management. With the support of the United Mitochondrial Disease Foundation (UMDF) and the NINDS/NICHD U54 supported North American Mitochondrial Disease Consortium (NAMDC), the MSeqDR prototype has been built. Current major components include common data upload and reannotation using a novel HBCR based annotation tool that has also been made publicly available through the website, MSeqDR GBrowse that allows ready visualization of all public and MSeqDR specific data including labspecific aggregate data visualization tracks, MSeqDR-LSDB instance of nearly 1250 mitochondrial disease and mitochodnrial localized genes that is based on the Locus Specific Database model, exome data set mining in individuals or families using the GEM.app tool, and Account & Access Management. Within MSeqDR GBrowse it is now possible to explore data derived from MitoMap, HmtDB, ClinVar, UCSC-NumtS, ENCODE, 1000 genomes, and many other resources that bioinformaticians recruited to the project are organizing.
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
Follow us on: Pinterest
Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
Triangles of Neck and Clinical Correlation by Dr. RIG.pptx
Data-driven drug discovery for rare diseases - Tales from the trenches (CINF 20, ACS National Meeting 2019-03-31)
1. CINF20 - 31 March 2019
Dr Frederik van den Broek, Elsevier Professional Services
Data-driven drug
discovery for rare
diseases
Tales from the trenches
2. This is what we are all after in drug discovery…
Image: Elsevier
3. If drug discovery and development only were that simple…
Disease
Drug
compound
4. If drug discovery and development only were that simple…
Disease
Protein
Target
Drug
compound
5. If drug discovery and development only were that simple…
Disease
Protein
Target
Drug
compound
• Cell processes
• Regulators
• Pathways
• …
• Bioactivity
• Toxicity
• Specificity
• …
6. If drug discovery and development only were that simple…
Disease
Protein
Target
Drug
compound
• Cell processes
• Regulators
• Pathways
• …
• Bioactivity
• Toxicity
• Specificity
• …
• Availability
• Synthesis
• PK/PD
• …
• Genotype
• Phenotype
• Individual
7. If drug discovery and development only were that simple…
Disease
Protein
Target
Drug
compound
• Cell processes
• Regulators
• Pathways
• …
• Bioactivity
• Toxicity
• Specificity
• …
• Availability
• Synthesis
• PK/PD
• …
• Genotype
• Phenotype
• Individual
8. This makes it all a lengthy and costly process
Image: https://www.phrma.org/graphic/the-biopharmaceutical-research-and-development-process
9. With rare diseases it is even harder
Small(er) patient populations leading to
• Less (integral) medical and scientific knowledge
• Small population for clinical trials
• Unawareness with doctors, researchers, policymakers
• Smaller potential market size for a drug
Image: http://www.campingtourist.com/camping-activities/climbing/difficult-mountains-climb/
10. Drug repurposing: a new hope for rare diseases
• Less costly and of interest for pharma
• Quicker to Phase II/III tests, so hopefully quicker to market
• Need reliable information from various sources to find suitable repurposing
candidates
Image: https://www.starwars.com/news/poll-what-is-the-best-scene-in-star-wars-a-new-hope
11. Accelerate with new knowledge and data
Disease
Protein
Target
Drug
compound
• Cell processes
• Regulators
• Pathways
• …
• Bioactivity
• Toxicity
• Specificity
• …
• Availability
• Synthesis
• PK/PD
• …
• Genotype
• Phenotype
• Individual
12. Various initiatives we were recently involved in
• Project with Findacure to find drug repurposing candidates for Congenital
Hyperinsulinism
• Pistoia Hackaton: Elsevier-Findacure challenge on Friedrich’s Ataxia
• Sub-network enrichment analysis for neuromuscular disorder pathways
• Disease pathway analysis for Huntingdon's Disease
• Pistoia Datathon for drug repurposing for rare diseases
13. | 13
• A rare genetic disease
• Permanently excessive level of insulin in the
blood
• Develops within the first few days of life
• Can lead to brain injury or even death
• In the most severe cases the only viable treatment is
the removal of the pancreas, consigning the patient to
a lifetime of diabetes
Congenital hyperinsulinsm (CHI)
https://res.cloudinary.com/indiegogo-media-prod-
cld/image/upload/c_limit,w_620/v1440424745/uzvnq
zhvbpsrtthzxqpu.jpg
14. Creating a comprehensive view of CHI
• CHI Literature Library
• Disease, Target, Pathway, and
Compound Analysis
• Research Landscape Analysis
Information Assets Applied
• Content Elsevier’s vast set of literature and patent data
• Data normalization Taxonomies and dictionaries to
normalize author names, institutions, drugs, targets, and
other important terms
• Information extraction Finding semantic
relationships, targets, pathways, drugs, and bioactivities
15. Building and refining the CHI disease model
Picked relevant
pathways
(from a collection of 1800
models)
Explored functions of
proteins using 6.2M pre-
text mined relations
and embedded Gene
Ontology
Summarized what is known
about CHI mechanism in an
overview model
16. From pathways to CHI treatments:
Automated analysis combines bioassay data with pathway data
Mean of activities among
these targets
Me
Targets and activities for
each compound
Drug-likeness
metrics for
sorting/classification
• All compounds that
were observed to bind
to targets in pathway
• Sorted by number of
active targets.
Too many targets may
suggest lack of specificity.
Find all targets that
could be used to affect
the disease state
Query for each target to find
compounds that have high
affinity for them (>6 log units)
Collate data by compound to summarize the
targets/activities related to disease that the
compound hits
• Compute geometric mean of activities for ranking
• Rank by number of targets and geometric mean of
activities against targets
Step 1 Step 2
Step 3
17. Pistoia Hackathon Challenge (2017)
Elsevier would like you to demonstrate the ability of deep learning to help
Findacure, a UK-based charity, accelerate treatment and clinical research for
Friedreich’s ataxia (FRDA). You’ll have access to a heterogeneous set of
data related to the disease: biological pathway analysis, associated chemical
compounds and bioactivities, potential candidates for drug re-purposing, full-
text scientific literature and clinical trial data.
Basically, giving others a go with the data sets we worked with on CHI….
18. Promising results, but still hard work
“We spent most of our time the first day just trying to get our heads around
the data, so we could start to find some solutions. Even opening the files was
tricky.” The students used various tools to try to extract data from the
provided XML files, but it was slow going. Daniel [one of the participants]
commented that, “we wound up having to do a lot of things manually, so we
could at least read the files in plain text.”
19. Sharing disease pathways
• Shared curated pathways (with supporting literature
references) with rare disease organisations to help their
discussions with researchers and fill in potential “blanks”
• Comparing gene expression algorithms for the identification
of expression regulators
• Well-defined datasets, with supporting
literature references which resonate
with researchers
21. “Machine learning
won’t work if your data
is rigidly siloed.”
“One major challenge
is collecting enough
reliable information to
properly train AI systems.
AI is as good as the
data.”
Nick Patience
Founder, 451
Research
“Organizations need to
make sure that the data
being accessed is
treated and defined
consistently across the
sources. Otherwise,
virtualization won't work.”
“All the major AI
advances have been
fueled by advances in
data sets. The algorithms
are easy….
"Collecting, classifying
and labeling datasets
used to train the
algorithms is the grunt
work that’s difficult”
Aspuru-Guzik
Professor of Chemistry &
Machine Learning, Harvard
University JJ Guy
CTO, Jask (AI co.)
‘Siloed’ Lack of standards
Requires labeling and
contextPoor quality1
2 3 4
Using the Entellect Platform and Data Curation
22. Access, curation of
authoritative life science
data
Integration of disparate
data, structured and
unstructured
Normalized and
standardized data with
industry standard
taxonomies
Build custom and off-the-
shelf analytics tools
‘Un-siloed’ Harmonized Enriched and linkedQuality
Nick Patience
Founder, 451
Research
Aspuru-Guzik
Professor of Chemistry &
Machine Learning, Harvard
University
1
2 3 4
Using the Entellect Platform and Data Curation
24. Various teams using various approaches
• Semantic data: Target Identification
• Semantic data: Small Molecule Binding
• Machine Learning
− Ensemble Learning
− Mol2Vec, Prot2Vec
− Network diffusion
• Expert collaboration
− Virtual docking
− Adverse Event profiling
“I could work on the important stuff straight away, using all the data”
26. Aiming to make data-driven drug discovery for rare diseases
a little easier…
Disease
Protein
Target
Drug
compound
• Cell processes
• Regulators
• Pathways
• …
• Bioactivity
• Toxicity
• Specificity
• …
• Availability
• Synthesis
• PK/PD
• …
• Genotype
• Phenotype
• Individual
27. Conclusions
• Data, data, data…
• Data has to be FAIR and of good and trusted provenance as the
researchers and clinicians will want to see the “chain of evidence” (beware
of black box models)
• Data sets also have to be FAIR for each other: enabling the integral
approaches repurposing needs have to be linked data sets across siloes
and domains to go from disease to target to compound (and back)
Image: Sangya Pundir, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=53414062
28. Acknowledgements
• Maria Shkrob
• Jabe Wilson
• Anton Yuryev
• Matthew Clark
• Christy Wilson
• Finlay Maclean
• Elsevier’s Entellect team
• Pistioia hackaton and datathon teams
