The document summarizes GVK BIO Informatics, which provides complete informatics solutions from knowledge management to predictive analytics. It highlights key databases and tools developed by GVK including CTOD (Clinical Trial Outcome Database) and biomarker databases containing clinical trial data, small molecules, and biomarkers. The document also discusses GVK's knowledge base development through custom data curation for database providers and lists many publications that have utilized GVK's GOSTAR database.
The Role of Bioinformatics in The Drug Discovery ProcessAdebowale Qazeem
The Role of Bioinformatics in The Drug Discovery Process, is an undergraduate seminar presentation in the department of Biochemistry, Faculty of life Sciences, University of Ilorin, Ilorin.
Our second webinar in the MDC Connects Series 2021 | A Guide to Complex Medicines.
This slide deck takes a closer look at developing the assay cascade for complex medicines.
Tilly Bingham, Concept Life Sciences
Our fifth webinar in the MDC Connects Series 2021 | A Guide to Complex Medicines.
This slide deck takes a closer look at how you can determine efficacy in vivo.
Jenny Worthington (Axis Bio)
In vivo protein target identification / target deconvolution via chemical proteomics as a facilitating tool for phenotype based drug discovery.
www.j-vomacka.com
We can aid decision making from the pre-clinical to the clinical setting, supporting line of sight to the clinic, by identifying and translating crucial biomarker approaches into the real world.
The Role of Bioinformatics in The Drug Discovery ProcessAdebowale Qazeem
The Role of Bioinformatics in The Drug Discovery Process, is an undergraduate seminar presentation in the department of Biochemistry, Faculty of life Sciences, University of Ilorin, Ilorin.
Our second webinar in the MDC Connects Series 2021 | A Guide to Complex Medicines.
This slide deck takes a closer look at developing the assay cascade for complex medicines.
Tilly Bingham, Concept Life Sciences
Our fifth webinar in the MDC Connects Series 2021 | A Guide to Complex Medicines.
This slide deck takes a closer look at how you can determine efficacy in vivo.
Jenny Worthington (Axis Bio)
In vivo protein target identification / target deconvolution via chemical proteomics as a facilitating tool for phenotype based drug discovery.
www.j-vomacka.com
We can aid decision making from the pre-clinical to the clinical setting, supporting line of sight to the clinic, by identifying and translating crucial biomarker approaches into the real world.
INTRODUCTION
A PERFECT THERAPEUTIC DRUG
DRUG DISCOVERY- HISTORY
MODERN DRUG DISCOVERY
BIOINFORATICS IN DRUG DISCOVERY
DRUG DISCOVERY BASED ON BIOINFORMATIC TOOLS
BIOINFORMATICS IN COMPUTER-AIDED DRUG DISCOVERY
ECONOMICS OF DRUG DISCOVERY
CONCLUSION
REFERENCES
Bioinformatics: Introduction, Objective of Bioinformatics, Bioinformatics Databases, Concept of Bioinformatics, Impact of Bioinformatics in Vaccine Discovery
Our first webinar in the MDC Connects Series 2021 | A Guide to Complex Medicines.
This slide deck takes a closer look at the state of play for Complex Medicine and highlights the potential opportunity for the UK.
Prof Peter Simpson, Medicines Discovery Catapult
Our first webinar in the MDC Connects Series 2021 | A Guide to Complex Medicines.
This slide deck takes a closer look at the target landscape for Complex Medicine.
Dr Duygu Yilmaz, Medicines Discovery Catapult
Part of the MaRS Best Practices Series - Pre-Clinical development workshop
http://www.marsdd.com/bestpractices
Speaker: Jack Jiang, VP Medicinal and Analytical Chemistry, Ricerca BioSciences
ICIC 2016: Improving the Pharmacovigilance Literature Screening Process. How ...Dr. Haxel Consult
Screening scientific literature for the purpose of detecting adverse side effects of drugs is burdensome, yet essential. The discovery and retrieval of full-text journal articles is a necessary part of this process. Cursory screening of abstracts has been used to determine which journal articles require full-text reviews. And transactional purchases have historically been the only option for accessing the full-text for non-subscribed content when cursory reviews lead to in-depth review requirements.
In February 2016, a new full-text article rental program was introduced to the drug safety market with the potential to enable a deeper screening of scientific journal content. In this session, Reprints Desk will present information related to new full-text article rentals, including an overview of how article rentals work and time-saving workflow options.
This analysis shows how IP, regulatory, and marketing strategy have to interfere for maximizing the lifetime of IP protection in pharmaceuticals. In contrast to mechanical inventions you can use special aspects of chemical /pharmaceutical patents like medical use or SPCs and PTE or variations in formulation to optimize your product protection. Using the example of an active ingredient it is shown how filing strategy, product development and finally IP life cycle management can be combined to achieve the maximum market success.
INTRODUCTION
A PERFECT THERAPEUTIC DRUG
DRUG DISCOVERY- HISTORY
MODERN DRUG DISCOVERY
BIOINFORATICS IN DRUG DISCOVERY
DRUG DISCOVERY BASED ON BIOINFORMATIC TOOLS
BIOINFORMATICS IN COMPUTER-AIDED DRUG DISCOVERY
ECONOMICS OF DRUG DISCOVERY
CONCLUSION
REFERENCES
Bioinformatics: Introduction, Objective of Bioinformatics, Bioinformatics Databases, Concept of Bioinformatics, Impact of Bioinformatics in Vaccine Discovery
Our first webinar in the MDC Connects Series 2021 | A Guide to Complex Medicines.
This slide deck takes a closer look at the state of play for Complex Medicine and highlights the potential opportunity for the UK.
Prof Peter Simpson, Medicines Discovery Catapult
Our first webinar in the MDC Connects Series 2021 | A Guide to Complex Medicines.
This slide deck takes a closer look at the target landscape for Complex Medicine.
Dr Duygu Yilmaz, Medicines Discovery Catapult
Part of the MaRS Best Practices Series - Pre-Clinical development workshop
http://www.marsdd.com/bestpractices
Speaker: Jack Jiang, VP Medicinal and Analytical Chemistry, Ricerca BioSciences
ICIC 2016: Improving the Pharmacovigilance Literature Screening Process. How ...Dr. Haxel Consult
Screening scientific literature for the purpose of detecting adverse side effects of drugs is burdensome, yet essential. The discovery and retrieval of full-text journal articles is a necessary part of this process. Cursory screening of abstracts has been used to determine which journal articles require full-text reviews. And transactional purchases have historically been the only option for accessing the full-text for non-subscribed content when cursory reviews lead to in-depth review requirements.
In February 2016, a new full-text article rental program was introduced to the drug safety market with the potential to enable a deeper screening of scientific journal content. In this session, Reprints Desk will present information related to new full-text article rentals, including an overview of how article rentals work and time-saving workflow options.
This analysis shows how IP, regulatory, and marketing strategy have to interfere for maximizing the lifetime of IP protection in pharmaceuticals. In contrast to mechanical inventions you can use special aspects of chemical /pharmaceutical patents like medical use or SPCs and PTE or variations in formulation to optimize your product protection. Using the example of an active ingredient it is shown how filing strategy, product development and finally IP life cycle management can be combined to achieve the maximum market success.
ICIC 2016: Mind the Gap: The novel benefits of human-curated substance locat...Dr. Haxel Consult
Identifying and locating chemical substances, which can be disclosed in patents by names, structures, variable tables, etc. presents a time-intensive challenge to chemical patent analysis. Though emerging technology can help, recently published research demonstrates that algorithmic identification of chemical substances alone successfully identifies only ~60% of the disclosed compounds, compared to intellectual compound identification. PatentPakTM addresses this gap by extending the efforts of CAS scientists, who have intellectually analyzed the global patent literature for claimed and exemplified compounds for more than 100 years, to also elucidate the location of the substances in the patent text. This presentation will explore a number of examples, including a case study on vitamin D metabolites, to demonstrate the significant time savings and enhanced comprehensiveness of this approach.
The Addition of Chemical Search Capabilities to PATENTSCOPE: Turning a Full-t...Dr. Haxel Consult
PATENTSCOPE is a free patent search system offered by the World Intellectual Property Organization (WIPO). Users can search in 52 million patent documents covering 2.9 million published international patent applications (PCT) and many patent collections from national IP authorities.
The system is being constantly enhanced, for example, by the addition of new patent collections, new functionality or additional languages in the user interface.
The last big step forward in this evolution was the addition of chemical search capabilities, accomplished using InfoChem’s text- and image-mining technologies. An automatic workflow was developed and put into operation allowing real-time, multi-modal chemical text annotation and image recognition.
This talk addresses the technical challenges encountered such as OCR quality, scalability, performance and parallelization.
ICIC 2016: Tutorial: Searching for Information – the Classical Way with Key W...Dr. Haxel Consult
Adding value to information through key words or classification is a long established practice. Using it is still common at least in professional information searching. Some years ago means for semantic searching emerged as additional search tools and were very much welcomed by the community of searchers. But were expectations fulfilled? The tutorial will try an answer demonstrating search paths for both methods and comparing results.
This thesis presents the development of computational methods and tools using as input three-dimensional structures data of protein-ligand complexes. The tools are useful to mine, profile and predict data from protein-ligand complexes to improve the modeling and the understanding of the protein-ligand recognition. This thesis is divided into five sub-projects. In addition, unpublished results about positioning water molecules in binding pockets are also presented. I developed a statistical model, PockDrug, which combines three properties (hydrophobicity, geometry and aromaticity) to predict the druggability of protein pockets, with results that are not dependent on the pocket estimation methods. The performance of pockets estimated on apo or holo proteins is better than that previously reported in the literature (Publication I). PockDrug is made available through a web server, PockDrug-Server (http://pockdrug.rpbs.univ-paris-diderot.fr), which additionally includes many tools for protein pocket analysis and characterization (Publication II). I developed a customizable computational workflow based on the superimposition of homologous proteins to mine the structural replacements of functional groups in the Protein Data Bank (PDB). Applied to phosphate groups, we identified a surprisingly high number of phosphate non-polar replacements as well as some mechanisms allowing positively charged replacements. In addition, we observed that ligands adopted a U-shape conformation at nucleotide binding pockets across phylogenetically unrelated proteins (Publication III). I investigated the prevalence of salt bridges at protein-ligand complexes in the PDB for five basic functional groups. The prevalence ranges from around 70% for guanidinium to 16% for tertiary ammonium cations, in this latter case appearing to be connected to a smaller volume available for interacting groups. In the absence of strong carboxylate-mediated salt bridges, the environment around the basic functional groups studied appeared enriched in functional groups with acidic properties such as hydroxyl, phenol groups or water molecules (Publication IV). I developed a tool that allows the analysis of binding poses obtained by docking. The tool compares a set of docked ligands to a reference bound ligand (may be different molecule) and provides a graphic output that plots the shape overlap and a Jaccard score based on comparison of molecular interaction fingerprints. The tool was applied to analyse the docking poses of active ligands at the orexin-1 and orexin-2 receptors found as a result of a combined virtual and experimental screen (Publication V). The review of literature focusses on protein-ligand recognition, presenting different concepts and current challenges in drug discovery.
Looking Beyond Biosimilarity - Importance of Patient Safety: Presentation of...drsomduttprasad
Here is my presentation at FOCUS 2016, the XXIVth Annual Conference of the Bombay Ophthalmologists' Association held from August 19-21, 2016 at ITC Maratha, Hyatt Regency & Hilton, Sahar, Mumbai.
Requesting a complete biosensor system in phyto-sourced drug discovery and de...iosrphr_editor
The IOSR Journal of Pharmacy (IOSRPHR) is an open access online & offline peer reviewed international journal, which publishes innovative research papers, reviews, mini-reviews, short communications and notes dealing with Pharmaceutical Sciences( Pharmaceutical Technology, Pharmaceutics, Biopharmaceutics, Pharmacokinetics, Pharmaceutical/Medicinal Chemistry, Computational Chemistry and Molecular Drug Design, Pharmacognosy & Phytochemistry, Pharmacology, Pharmaceutical Analysis, Pharmacy Practice, Clinical and Hospital Pharmacy, Cell Biology, Genomics and Proteomics, Pharmacogenomics, Bioinformatics and Biotechnology of Pharmaceutical Interest........more details on Aim & Scope).
Bioinformatics in the Clinical Pipeline: Contribution in Genomic Medicineiosrjce
In this review report we like to focus on the new challenges in methodology of modern biology be
used in medical science. Today human health is a primary issue to cure disease, undoubtedly the answer to this
is bioinformatics or (In-silco) tools has change the concept of treating patients to understand the need of
genomic medicine in use. Those with new modes of action in clinical treatment, is a major health concern in
medical science. On global prospective scientific role in constructing new ideas to remediate health care to
treat disease exciting in nature is challenging task. So awareness needs to accelerate store clinical datasets for
scientific represents to design genomic drugs. This new outline will drive the medical to discover public data
and create a cognitive approach to use technology cheaper at cost effective mode.
Research trends in different pharmaceutical areas: Natural product chemistry
Imtiaj Hossain Chowdhury
B’Pharm (Jahangirnagar University), M’Pharm (Jahangirnagar University)
Master’s in Public Health (American International University Bangladesh)
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.
AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...Dr. Haxel Consult
Knowledge Graphs are an increasingly relevant approach to store detailed knowledge in many domains. Recent advances in NLP allow to enrich Knowledge Graphs through automated analysis of large volumes of literature, reducing a lot the efforts in traditional manual information capturing. In our presentation we report the approach taken in a project with partner Fraunhofer SCAI in the life sciences where a knowledge graph organising detailed facts about psychiatric diseases has been computed.
Information of cause-effect relations between proteins, genes, drugs and diseases has been encoded in the BEL (Biological Expression Language) and imported into a Graph database to approach an indication-wide Knowledge Graph for the selected therapeutic area. Ultimately, updating the graph will amount to just rerunning the analysis on the newly published literature.
AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...Dr. Haxel Consult
In 2019 the UK was the first major economy to embrace a legal obligation to achieve net zero carbon emissions by 2050. More broadly, the 2021 UK Innovation Strategy sets out the UK government’s vision to make the UK a global hub for innovation by 2035 with a target of increasing public and private sector R&D expenditure to 2.4% of GDP to support the UK being a science superpower with a world-class research and innovation system.
IP rights create an incentive for R&D which ultimately leads to innovation. Analysis and insights from IP data can therefore help provide a better understanding of how the IP system is being used and where and what innovation is taking place. Research and analysis of IP data is a key input to the ongoing work of the UKIPO’s Green Tech Working Group which seeks to:
further the UK’s status as a global leader by making the UK’s IP environment the best for innovating green technology;
develop and deliver IP policies to support government’s ambition on climate change and green technologies; and
to help innovators best protect and commercialise their green tech innovations both at home and internationally.
The UKIPO has been developing a broad portfolio of ‘green’ IP analytics research. A series of patent analytics reports have been published looking at green technologies, and analysis of how the UK’s Green Channel scheme for accelerated processing of green patent applications has been conducted. Patents have been used to identify technological comparative advantage within different green technologies at a country level, and new insights uncovered by mapping green technology patents to the UN Sustainable Development Goals (SDGs). Trade mark data provides a timeliness and closeness to market factor that patent data does not, and complementary trade mark analysis of UK ‘green’ trade marks, identified using a machine learning algorithm, provides a commercialisation angle to our research.
AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...Dr. Haxel Consult
Word embeddings, deep learning, transformer models and other pre-trained neural language models (sometimes recently referred to as "foundational models") have fundamentally changed the way state-of-the-art systems for natural language processing and information access are built today. The "Data-to-Value" process methodology (Leidner 2013; Leidner 2022a,b) has been devised to embody best practices for the construction of natural language engineering solutions; it can assist practitioners and has also been used to transfer industrial insights into the university classroom. This talk recaps how the methodology supports engineers in building systems more consistently and then outlines the changes in the methodology to adapt it to the deep learning age. The cost and energy implications will also be discussed.
AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...Dr. Haxel Consult
In the patent domain, all types of issues, from very specific search requirements to the linguistic characteristics of the text domain, are accentuated. Consequently, to develop patent text mining tools for scientists and patent experts, we need to understand their daily work tasks, as well as the linguistic character of the text genre (i.e., patentese). Patent text is a mixture of legal and domain-specific terms. In processing technical English texts, a multi-word unit method is often deployed as a word-formation strategy to expand the working vocabulary, i.e., introducing a new concept without the invention of an entirely new word. This productive word formation is a well-known challenge for traditional natural language processing tools utilizing supervised machine learning algorithms due to limited domain-specific training data. Deep learning technologies have been introduced to overcome the reduction in performance of traditional NLP tools. In the Artificial Researcher technologies, we have integrated explicit and implicit linguistic knowledge into the deep learning algorithms, essential for domain-specific text mining tools. In this talk, we will present a step-by-step process of how we have developed the mentioned text mining tools. For the final outline, we will also demonstrate how these tools can be integrated in a cross-genre passage retrieval system, based on a technology from 2016 that still holds the state-of-the-art within the patent text mining research community in 2022.
AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...Dr. Haxel Consult
In 2013 we witnessed an evolutionary change in the NLP field evolved thanks to the introduction of space embeddings that, with the use of deep learning architectures, achieved human-level performances in many NLP tasks. With the introduction of the Attention mechanism in 2017 the results were further improved and, as result, embeddings are quickly becoming the de facto standards in solving many NLP problems. In this presentation, you will learn how generate and use space embedding for search purposes and provide comparison metrics to more traditional relevance-based search engines. Moreover, I will provide some initial results on a paper currently under review that provides an insight on hyperparameter tuning during the generation of embeddings.
AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...Dr. Haxel Consult
10 years in the making. How real-world business cases have driven the development of CCC's deep search solutions, leading to the capabilities for web-crawling and delivery of targeted intelligence that helps R&D; intensive companies gain a competitive advantage.
AI-SDV 2022: Machine learning based patent categorization: A success story in...Dr. Haxel Consult
Machine learning based patent categorization: A success story in monitoring a complex technology with high patenting activity
Susanne Tropf (Syngenta, Switzerland)
Kornel Marko (Averbis, Germany)
AI-SDV 2022: Machine learning based patent categorization: A success story in...Dr. Haxel Consult
Machine learning based patent categorization: A success story in monitoring a complex technology with high patenting activity
Susanne Tropf (Syngenta, Switzerland)
Kornel Marko (Averbis, Germany)
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...Dr. Haxel Consult
It is relatively easy for a human to read a document and quickly figure out which concepts are important. However, this task is a difficult challenge for a machine. During the past few decades, there have been two main approaches for concept identification: Natural Language Processing and Machine Learning. During the early part of this century, Machine Learning made great strides as new techniques came into wider use (SVM’s, Topic Modeling, etc..). Sensing the competition, Natural Language Processing responded with deployment of new emerging techniques (sematic networks, finite state automata, etc..). Neither approach has completely solved the WHAT problem. Advances in Artificial Intelligence have the potential to significantly improve the situation. Where AI is making the most impact is as an enhancement to make Machine Learning and Natural Language Processing work better and, more importantly, work together. This presentation looks at some of this history and what might happen in the future when we blend the interpretation of language with pattern prediction.
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...Dr. Haxel Consult
Trademarks serve as key leading indicators for innovation and economic growth. As the vanguards of new and expanding enterprises, trademarks can be used to study entrepreneurship and shifting market demands in response to varying economic factors. This responsiveness has been seen as recently as the COVID-19 pandemic, where trademark research revealed key insights about business reaction to the global upheaval.
At CIPO, we have been delving more deeply than ever before into trademark analysis by leveraging cutting-edge natural language processing (NLP) tools to derive actionable business intelligence from trademark data. In this presentation, we present a survey of NLP in use at CIPO and the insights we have learned applying them. These insights include COVID-19 responses, line-of-business trends based on firm characteristics, and more.
We also discuss ongoing and future trademark research projects at CIPO. These projects include emerging technology detection methods and high-resolution trademark classification systems. We conclude that artificial intelligence-enhanced tools like NLP are key components of future exploitation of trademark data for business and economic intelligence.
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...Dr. Haxel Consult
In our customer projects involving automated document processing, we often encounter document types providing crucial data in the form of tables. While established text analytics algorithms are usually optimized to operate on running text, they tend to produce rather poor results on tables as they do not capture the non-sequential relations inside them (e.g. interpret the content of a table cell relative to its column title, interpret line breaks inside a cell differently from line breaks between cells or rows). While there are elaborate information extraction products in the market for a few highly specific types of tabular documents, there is no general approach out there. The main cause for this is the fact that table structures can be encoded by a heterogenous range of layout means (e.g. column boundaries can be signaled by lines vs. aligned text vs. white space). In this talk, we will illustrate several solutions that we have developed for a range of challenges occurring in this context, both for scanned and digitally generated documents.
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...Dr. Haxel Consult
Most scientific journals request, that the complete set of research data is published simultaneously with the peer-reviewed paper. The publication of the research data usually is carried out as so-called "Supplementary Material", attached to the original paper, or on a "Research Data Repository". Both forms have in common, that the data is published usually unstructured and not in an uniform machine processable format. This makes its further use in electronic tools for AI or data mining unnecessarily difficult or even impossible. A concept is presented, in which the data is digitally recorded, following the principle of FAIR data, as part of the publication process. This digital capture makes the data available to the scientific community for easy use in data mining and AI tools. The data in the repository contains links to the publication to document its origin. The concept is applicable for preprints, peer-review papers, diploma and doctoral theses and is particularly suitable for open access publications. Moreover, the presentation highlights correspondent activities, which were released in scientific publications recently.
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...Dr. Haxel Consult
How do you find video when you only have sparse data? While you can wander the stacks (if you can still find open stacks) for inspiration, video either physical or digital, is difficult to discover. Wandering the virtual stacks is, well, virtually impossible. Discovery platforms on the whole have not replicated the inspirational experience of wandering the stacks.
More companies are using archivable video for internal communication of the various research projects, product developments, test results, and more that are being considered, in progress, or completed. Showing how an experiment was conducted can convey considerably more information that is very difficult to communicate via text. How do you find a company video that might be helpful for your project?
A case study is presented of the problems and the solutions that were implemented by a large, multinational chemical company. A suite of content discovery technologies was used including a video to text to tagging system connected to their documents database and automatically indexed using several chemical as well as conceptual systems (rule-based, NLP, inference engine). To build the system and support the manuscript and video submission there is a metadata extraction program which pulls and inserts the metadata into the submission forms so the author can move quickly through that process.
Copyright Clearance Center
A pioneer in voluntary collective licensing, CCC (Copyright Clearance Center) helps organizations integrate, access, and share information through licensing, content, software, and professional services. With expertise in copyright and information management, CCC and its subsidiary RightsDirect collaborate with stakeholders to design and deliver innovative information solutions that power decision-making by helping people integrate and navigate data sources and content assets. CCC recently acquired the assets and technology of Deep SEARCH 9 (DS9), a knowledge management platform that leverages machine learning to help customers perform semantic search, tag content, and discover new insights.
Lighthouse IP is the world’s leading provider of intellectual property content. The core business of Lighthouse IP is sourcing and creating content from the world’s most challenging authorities. Specialized in IP data, Lighthouse IP provides over 160 countries coverage for patents, over 200 authorities for trademarks and over 90 authorities for designs. Lighthouse IP data is available via several partners. The company is headquartered in Schiphol-Rijk in the Netherlands and has offices in the United States, China, Thailand, Vietnam, Egypt, Indonesia and Belarus. Globally a team of 150 experts works on the creation of this unique data collection.
CENTREDOC was created in 1964 as the technical information center of the swiss watchmaking industry. Building on a strong team of engineers, CENTREDOC now offers a complete range of services and solutions for the monitoring of strategic, technological and competitive information. CENTREDOC is also a leader in the research of patent, technical and business intelligence, and offers consulting expertise in the implementation of monitoring solutions.
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...Dr. Haxel Consult
The everyday use of AI-driven algorithms for data search, analysis and synthesis comes with important time savings, but also reveals the need to understand and accept the limitations of the technology. Practical deployments on concrete topics are inevitable to assess and manage the challenges of neuronal network based AI. A workshop report.
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...Dr. Haxel Consult
What if there was a platform where literature, conference abstracts, patents, clinical trials, news, grants and other sources were fully integrated? What if the data would be harmonized, enriched with standardized concepts and ready for analysis? After building our patent analytics platform we didn’t stop dreaming and built our big data analytics platform by semantically integrating text-rich, scientific sources. In my presentation I will talk about what we built and why we built it. And, of course, I will also address the challenges and hurdles along the way. Was it worth it and what comes next? Let’s talk about it!
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
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.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
3. GVK BIO INFORMATICS
COMPLETE SOLUTION FROM KNOWLEDGE MANAGEMENT TO PREDICTIVE ANALYTICS
- Patents, Journals
- Public Domain Information
- Client’s Proprietary data
Annotation &
Scientific
Data
Management
- Predictive Biology
- Drug Repurposing
- Clinical Pharmacology
- Application Development
- Application Integration
- Application Management
Knowledge
Base
Predictive
Analytics
BIO IT
- Small Molecules SAR
- Biomarker
- Clinical Trial Outcome
Environmental
Modelling and
Eco-Tox Risk
Assessment
IPR
- Prior Art search
- FTO search
- Novelty search
- PEC Assessment Reports
- Environmental Fate Registration Report
- Eco toxicological Risk Assessment
4. KNOWLEDGE BASE
CTOD
Clinical Trial Outcome Database
A web-based application
A web based biomarker
database
Key Differentiators
6.3 million small
26,000 biomarkers
~ 1 Mn patients
molecules
17 therapeutic
2,200 trials
areas
19 Indications
16 million SAR points
(2.9 million Patents,
840 indications
350,000 Journals)
(100,000
references)
(150,000 references)
•
•
•
•
•
Comprehensiveness
Current-ness
Usability
Comprehendability
Credibility
5. KNOWLEDGE BASE DEVELOPMENTCUSTOM DATA CURATION FOR FIVE LEADING DATABASE PROVIDERS
REACTIONS
CURATION FROM
JOURNAL ARTICLES
3 Million Reactions
throughput per year
Curation and Indexing
of Life Sciences and
Toxicology Journals
Developed Advanced
Curation Tools to
Improve Productivity
CLINICAL DATA
CURATION
Throughput of
600,000 Journals per
annum
Throughput of 50,000
Key Differentiators
Trials per annum
200,000 Journals per
annum
•
•
•
•
•
Comprehensiveness
Current-ness
Usability
Comprehendability
Credibility
7. Multi dimensional relational data
With One
Of
You Can Explore Data from
CLICK
Chemical
space
Pharmaco
logical
Space
Literature
Space
Chemical Structures
6.3 million
SAR Activities
~ 16 million
Literature Screened
3.5 million
Scaffolds
Pharmacokinetics/Metabo
lism
1.4 million
Patents
0.07 million
(3.2 M Screened)
Targets
6200+
Articles
0.3 million
~1.1 million
Frameworks or Cores
150,000
Clinical,
Marketed
& Toxic
Area
Clinical Compounds
~ 24,500
Drugs
~4750
Toxic Compounds
26,100
8. Data Sources
Pharmacological
Journals
Patents
(US, WO, EP, GB, JP)
Company web sites,
Conferences
Medicinal Chemistry
Journals
FDA/EMEA Docs
Scientific Reviews
Clinical Trail Registries
Manual curation with three levels of quality check
Standard Ontology for the data fields
Regular monthly data updates
9. DatabasesIntegrated in GOSTAR
Databases Integrated in GOSTAR
Records curated from
medicinal chemistry
journals
Contains data on the
toxicity, routes of
metabolism, organspecies-effects of toxicity
Med-Chem
Database
Natural Product
Database
Target
Databases
Mechanism
based
Toxicity
Database
Drug
Database
Clinical
Candidate
Database
Records curated from journals and
patents.
Popular target families like GPCR,
Kinase, NHR,
Peptidases etc
Contains information
on launched drugs
Compounds that have crossed
the IND phase and either ARE
or WERE in the Clinical Phase
10. Many publications using GOSTAR database
S.No
Title
1
Systematic exploration of dual-acting modulators
from a
combined medicinal chemistry and biology
perspective
2
Molecular clinical safety intelligence:
a system for bridging clinically focused
safety knowledge to early-stage drug
discovery – the GSK experience
Drug Discovery Today Volume 16,
Numbers 15/16 August 2011
3
What Do Medicinal Chemists Actually Make? A
50-Year Retrospective
Journal Of Medicinal Chemistry
April 25, 2011
4
Analysis of in vitro bioactivity data extracted from
drug discovery literature and patents: Ranking
1654 human protein targets by assayed
compounds and molecular scaffolds
Journal of Cheminformatics
2011, 3:14
5
Publication
Journal Of Medicinal Chemistry
Jan 3, 2013
Are There Differences between Launched Drugs,
Kazuki Ohno, Yuichi Nagahara,
Clinical Candidates, and Commercially Available
Kazuhisa Tsunoyama, and Masaya Orita
Compounds?
Company
11. GOSTAR database- list of publications
S.no
1
2
3
4
5
6
7
8
Title
Publication
Authors
Systematic exploration of dual-acting
Journal Of Medicinal Chemistry Aurelie Bornot, Udo Bauer, Alastair
modulators from a
Jan 3, 2013
Brown, Mike Firth, Caroline
combined medicinal chemistry and biology
Hellawell, and Ola Engkvist
perspective
Dana E. Vanderwall, Nancy Yuen,*,
Molecular clinical safety intelligence:
Mohammad Al-Ansari, James Bailey,
Drug Discovery Today Volume
a system for bridging clinically focused
David Fram,
16, Numbers 15/16 August
safety knowledge to early-stage drug
Darren V.S. Green, Stephen Pickett,
2011
discovery – the GSK experience
Giovanni Vitulli, Juan I. Luengo and
June S. Almenoff
W. Patrick Walters,* Jeremy Green,
What Do Medicinal Chemists Actually
Journal Of Medicinal Chemistry
Jonathan R. Weiss, and Mark A.
Make? A 50-Year Retrospective
April 25, 2011
Murcko
Analysis of in vitro bioactivity data
extracted from drug discovery literature
Christopher Southan, Kiran
Journal of Cheminformatics
and patents: Ranking 1654 human protein
Boppana, Sarma A.R.P. Jagarlapudi,
2011, 3:14
targets by assayed compounds and
Sorel Muresan
molecular scaffolds
Physicochemical property profiles of
Christian Tyrchan, Niklas Blomberg,
Bioorg. Med. Chem. Lett. 2009,
marketed drugs, clinical candidates and
Ola Engkvist, Thierry Kogej, Sorel
19 (24), 6943-6947
bioactive compounds
Muresan
Escape from Flatland: Increasing Saturation
J. Med. Chem., 2009, 52, 6752Frank Lovering, Jack Bikker,
as an Approach to Improving Clinical
6756
Christine Humblet
Success
Quantitative assessment of the expanding
complementarity between public and
Journal of Cheminformatics,
Christopher Southan, Peter
commercial databases of bioactive
2009, 1:10, 1-17
Varkonyi, Sorel Muresan
compounds
Josefin Rosen, Johan Gottfries, Sorel
Novel Chemical Space Exploration via
J. Med. Chem., 2009, 52 (7),
Muresan, Anders Backlund, Tudor I.
Natural Products
1953-1962
Oprea
Company
12. Contd..
9
10
11
12
13
14
15
16
17
Hongming Chen, Ulf Borjesson,
Ola Engkvist, Thierry Kogej, Mats
ProSAR: A New Methodology for
J. Chem. Inf. Model., 2009, 49
A. Svensson, Niklas Blomberg, Dirk
Combinatorial Library Design
(3), 603-614
Weigelt, Jeremy N. Burrows, Tim
Lange
Josef Scheiber, Bin Chen, Mariusz
Milik, Sai Chetan K. Sukuru,
Gaining insight into off-target mediated
Andreas Bender, Dmitri Mikhailov,
effects of drug candidates with a
J. Chem. Inf. Model., 2009, 49,
Steven Whitebread, Jacques
comprehensive systems chemical biology
308-317
Hamon, Kamal Azzaoui, Laszlo
analysis
Urban, Meir Glick, John W. Davies,
Jeremy L. Jenkins
Visual exploration of structure-activity
J Comput Aided Mol Des., 2008,
relationship using maximum common
Sung Jin Cho, Yaxiong Sun
22, 571-578
framework
Kinase-likeness and Kinase-Privileged
Alex M. Aronov, Brian McClain,
J. Med. Chem., 2008, 51, 1214Fragments: Toward Virtual
Cameron Stuver Moody, Mark A.
1222
Polypharmacology
Murcko
The influence of drug-like concepts on
Nature Reviews: Drug
Paul D. Leeson, Brian
decision-making in medicinal chemistry
Discovery, 2007, 6, 881-890
Springthorpe
Complementarity Between Public and
Current Topics in Medicinal
Christopher Southan, Peter
Commercial Databases: New Opportunities
Chemistry, 2007, 7, 1502-1508
Varkonyi, Sorel Muresan
in Medicinal Chemistry Informatics
Drug Discovery Today, Vol. 12,
Outsourcing lead optimization: constant
No. 1/2, 2007, 62-70
David E. Clark
change is here to stay
Shape Signatures: speeding up computer Drug Discovery Today, Vol. 11,
aided drug discovery
No. 19/20, 2006, 895-904
Peter J. Meek, ZhiWei Liu, LiFeng
Tian, Ching Y. Wang, William J.
Welsh, Randy J. Zauhar
Dependence of Molecular Properties on J. Med. Chem., 2006, 49, 3451Michal Vieth, Jeffrey J. Sutherland
Proteomic Family for Marketed Oral Drugs
3453