Drug Repositioning Workshop
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The document discusses Signals' approach to drug repositioning using big data. It introduces Signals and their product intelligence expertise. Their solution automatically produces and delivers business analytics by collecting, integrating and analyzing big data from open web sources. The presentation discusses the challenges in drug development, need for repositioning, and Signals' evidence-based data model and methodology for characterizing a drug and generating queries to identify novel opportunities for increasing its ROI by detecting similar drugs, modifications, conditions and genomic data.
Drug Repositioning Workshop
- 1. Shlomi Madar, Ph.D. | Signals | www.signalsgroup.com Drug Repositioning and Repurposing: Leverage Relevant & External Big Data For Your Crucial Business Decisions
- 2. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE AGENDA 5:30 - 6:00 - Introduction & Drinks 6:00 - 6:10 - About Signals 6:10 - 7:00 - Drug Repositioning: Big Data to Big Opportunity Efficient, Algorithm-Drive Methods for Repeatable Repositioning Success 7:00 - 7:30 - Conclusion and Q&A Discussion 2
- 3. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE 3 INTRODUCTION TO SIGNALS
- 4. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE4 Meet Signals Founded in 2009, 60+ employees and growing Intelligence veterans, PhDs, data & computer scientists, industry experts Intelligence platform & professional service Serving over 30 Fortune 1000 clients HQ in Israel; Offices in NYC and Geneva
- 5. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE5 Product Intelligence Experts PRODUCT INNOVATION identify new product opportunities and build a business case PRODUCT RENOVATION modify existing products to capture market share OPEN INNOVATION select competitive technology strategies & partners PRODUCT LAUNCH Develop go-to-market plans and introduce new products to market PRODUCT EXPANSION grow market share via introduction to new consumers and geographies
- 6. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE6 Our Solution AUTOMATED PRODUCTION AND DELIVERY OF BUSINESS ANALYTICS BASED ON OPEN WEB INTELLIGENCE We collect, integrate and analyze big data from multiple sources, delivering concise findings at the decision point CLOUD BASED APPLICATION DESIGNED FOR DELIVERY OF ANALYTICS & INSIGHTS, SYNCED WITH THE ORGANIZATIONAL NPD PROCESS CORE PLATFORM FOR PRODUCING, MANAGING AND STORING ANALYTIC MODELS, DYNAMIC ONTOLOGIES AND COLLECTED BIG DATA
- 7. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Combine Multiple Source Types Into a Unified Decision Model 7
- 8. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE THE CHALLENGE Enhancing ROI on Drugs 8
- 9. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE The Need 90% of Phase I drugs will fail to be approved by the FDA. NATURE BIOTECHNOLOGY Average cost for launching a successful drug: ~$2 Billion. …and for a repositioned drug: ~$8.4 million Drug Discovery World 9 Patent Cliff. Drugs’ patents are expiring. In 2015, products worth $66 billion will lose IP protection2. Fierce Pharma
- 10. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE The Need 90% of Phase I drugs will fail to be approved by the FDA. NATURE BIOTECHNOLOGY Average cost for launching a successful drug: ~$2 Billion. …and for a repositioned drug: ~$8.4 million Drug Discovery World 10 Patent Cliff. Drugs’ patents are expiring. In 2015, products worth $66 billion will lose IP protection2. Fierce Pharma ROI on Any drug, either approved or under development – can be enhanced
- 11. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Drug Repositioning – Success Stories 1Thomson Reuters Drugs that have been successfully repositioned1 11
- 12. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Innovative Ideas Supported by New Technologies 12
- 13. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Innovative Ideas Supported by New Technologies 13
- 14. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE NEW APPROACH FOR DRUG REPOSITIONING 14
- 15. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Detection of Novel Opportunities For Drug-x Identifying similar drugs that already benefit from combination therapy and are potentially relevant for Drug X. Modifications of dosage, route of administration, etc. Research for conditions associated with a personalized medicine approach in relevant research literature. For example, an ‘Omics’- related finding associated with a certain disease that can later be targeted by specific drugs. Modifications Conditions Combinations Genomics Drug X Four approaches can be taken in order to detect novel opportunities for Drug X. Similar Drugs Predicted Adverse Drug Reactions A gauge is utilized for assessment of similarity level to Drug X. 15
- 16. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Methodology Breakdown of Drug X traits into several levels (pathway, mechanism of action, etc.) based on data mining and natural language processing. Queries are generated and applied onto the different resources. Applying queries to extract similar therapeutic entities and assess their similarity to Drug X. Similar Therapeutic Entities Drug X Characterization 16 Top Hits Identifying Novel Conditions, Combinations, Modifications, and Genomic Data - new opportunities for increasing ROI from drug X Conditions Ranking Model Establishing a ranking model which will reflect the market conditions and the client’s preferences and core capabilities. The end result will be a list of the most relevant conditions that could be potentially treated with the initial drug.
- 17. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Evidence-Based Data Model Converting Multiple Data Sources Into Meaningful Insights 17 DRUG DATA VOCABULARIES SCIENTIFIC RESOURCES • DrugBank • Drugs.com • FDA NDC • FDA Pharmacological Classes • FDA Product Labels • FDA UNII • RX Norm • WebMD.com • MeSH Descriptors • MeSH Tree • WHO ATC • FDA Structural Classes • FDA Mechanism of Action • FDA Physiological Effect • ClinicalTrials.gov • PubMed.gov PATENTS • Espacenet.org GENOMICS • GEO • KEGG • Pharmgkb • FINDbase • GMOD
- 18. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Input: “Drug X” Natural Language Processing Query Generation Keywords for Drug X Characterization • The input into Signals’ Drugbase includes Drug X with all of its synonyms. Search Drug X Converting Multiple Data Sources Into Meaningful Insights 18
- 19. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Query Generation Keywords for Drug X Characterization Input: “Drug X” Natural Language Processing • The list of terms undergoes a manual curation. The process produced >95% accuracy. Converting Multiple Data Sources Into Meaningful Insights 19 • The initial input undergoes natural language processing to generate an output of terms which characterize Drug X.
- 20. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Input: “Drug X” Natural Language Processing Query Generation Keywords for Drug X Characterization • The initial input undergoes natural language processing to generate an output of terms which characterize Drug X. 20 Converting Multiple Data Sources Into Meaningful Insights
- 21. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Hierarchy Tree of Search Terms Based on Mode of Action Similarities to Drug X Pro-Inflammatory/ Anti-Inflammatory Cell Type C Cytokines Immune Cells Protein X Cell B Path D Path CPath B Cell Type B Path A Cell Type A Cell A Cell Type C Markers Path D CDXX CDxx CDxxCDxxThXXThXThXThX Path HPath GIL-XXIL-X Path IIL-XXIL-XXIL-XIL-X Down-regulation Up-regulation Tier 2 affected by Drug X Tier 1 affected by Drug X Neuroprotection Cell Type E Cell Type G Cell Type F Cell Type H 21
- 22. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Queries are generated to include all terms, their synonyms, and the type of modifications undergone by Drug-X, which are then applied onto the different resources. Input: “Drug- X” Natural Language Processing Query Generation Keywords for Drug-X Characterization Converting Multiple Data Sources Into Meaningful Insights 22
- 23. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE IL-48 Path 1 Th-X TNFα NF-κB Downregulation Downregulation AND IL-48 Downregulation AND Path 1 Downregulation AND Th-X Downregulation AND TNFα Downregulation AND NF-κB Prevent Prevent AND IL-48 Prevent AND Path 1 Prevent AND Th-X Prevent AND TNFα Prevent AND NF-κB Barrier Barrier AND IL-48 Barrier AND Path 1 Barrier AND Th-X Barrier AND TNFα Barrier AND NF-κB Block Block AND IL-48 Block AND Path 1 Block AND Th-X Block AND TNFα Block AND NF-κB Decrease Decrease AND IL-48 Decrease AND Path 1 Decrease AND Th-X Decrease AND TNFα Decrease AND NF-κB Reduce Reduce AND IL-48 Reduce AND Path 1 Reduce AND Th-X Reduce AND TNFα Reduce AND NF-κB Diminish Diminish AND IL-48 Diminish AND Path 1 Diminish AND Th-X Diminish AND TNFα Diminish AND NF-κB Eliminate Eliminate AND IL-48 Eliminate AND Path 1 Eliminate AND Th-X Eliminate AND TNFα Eliminate AND NF-κB Anti Anti AND IL-48 Anti AND Path 1 Anti AND Th-X Anti AND TNFα Anti AND NF-κB Inhibit Inhibit AND IL-48 Inhibit AND Path 1 Inhibit AND Th-X Inhibit AND TNFα Inhibit AND NF-κB Obstruct Obstruct AND IL-48 Obstruct AND Path 1 Obstruct AND Th-X Obstruct AND TNFα Obstruct AND NF-κB Against Against AND IL-48 Against AND Path 1 Against AND Th-X Against AND TNFα Against AND NF-κB Antagonist Antagonist AND IL-48 Antagonist AND Path 1 Antagonist AND Th-X Antagonist AND TNFα Antagonist AND NF-κB De-activate Deactivate AND IL-48 Deactivate AND Path 1 Deactivate AND Th-X Deactivate AND TNFα Deactivate AND NF-κB De-activate De-activate AND IL-48 De-activate AND Path 1 De-activate AND Th-X De-activate AND TNFα De-activate AND NF-κB Dysregulate Dysregulate AND IL-48 Dysregulate AND Path 1 Dysregulate AND Th-X Dysregulate AND TNFα Dysregulate AND NF-κB Suppress Suppress AND IL-48 Suppress AND Path 1 Suppress AND Th-X Suppress AND TNFα Suppress AND NF-κB Upregulation Upregulation AND IL-48 Upregulation AND Path 1 Upregulation AND Th-X Upregulation AND TNFα Upregulation AND NF-κB Promote Promote AND IL-48 Promote AND Path 1 Promote AND Th-X Promote AND TNFα Promote AND NF-κB Enhance Enhance AND IL-48 Enhance AND Path 1 Enhance AND Th-X Enhance AND TNFα Enhance AND NF-κB Increase Increase AND IL-48 Increase AND Path 1 Increase AND Th-X Increase AND TNFα Increase AND NF-κB Augment Augment AND IL-48 Augment AND Path 1 Augment AND Th-X Augment AND TNFα Augment AND NF-κB Induce Induce AND IL-48 Induce AND Path 1 Induce AND Th-X Induce AND TNFα Induce AND NF-κB Agonist Agonist AND IL-48 Agonist AND Path 1 Agonist AND Th-X Agonist AND TNFα Agonist AND NF-κB Activate Activate AND IL-48 Activate AND Path 1 Activate AND Th-X Activate AND TNFα Activate AND NF-κB Amplify Amplify AND IL-48 Amplify AND Path 1 Amplify AND Th-X Amplify AND TNFα Amplify AND NF-κB Amplification Amplification AND IL-48 Amplification AND Path 1 Amplification AND Th-X Amplification AND TNFα Amplification AND NF-κB An elaborate matrix is generated in order to produce queries with the utmost accuracy and coverage. Breadth and Depth of Search Queries 23
- 24. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE THE OUTCOME 24
- 25. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Drug Database Clinical Trial Publication Source Drug X's Most Similar Drugs – Shared Molecular Pathways Drug A Drug B Vitamin A Drug C Drug D Drug E Drug F Drug G Path-1 Path-2 Path-3 Path-4 Path-5 Path-6 Path-7 Path-8 Path-9 Gene1 Gene2 Gene3 Gene4 Gene5 Gene6 Gene7 Gene8 Gene9 25
- 26. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE No. of Data Points Novel Conditions by Similar Drugs Numbers represent the data collected from patents, publications, labels and clinical trials. 26 Condition A Condition B Condition C Condition D Condition E Condition F Condition G Condition H Condition I Condition J Condition K Condition L Condition M Condition N Condition O Condition P Condition Q Condition R Drug A Drug B Vitamin A Drug C Drug D Drug E Drug F Drug G Drug H Similar Drugs
- 27. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Predicted Adverse Events Stemming From Similar Drugs Injection Oral Topical Drug A Drug B Vitamin A Drug C Drug D Drug E Drug F Drug G Drug XDrug H 27
- 28. NEW APPROACH FOR DRUG REPOSITIONING PRODUCT INTELLIGENCE Signals’ Recommendations for Drug X Using Drug X in combination with Vitamin A1 2 3 4 Treating Rheumatoid Arthritis with Drug X Abdominal Pain, weight decrease, and a cough are predicted adverse events for Drug X 5 A-123 gene polymorphisms are potential pharmacogenetic markers for Drug X The client should follow up on their patents combining Drug X with Drug Y 28
- 29. See More of Our Work Here | www.signalsgroup.com | [email protected] THANK YOU
Editor's Notes
- #3: So what are we going to talk about today? I’m going to use the 25 minutes I have to share with you how big data can be used to support innovation. First, we are going to start off talking about something you all probably sick of hearing about : “Big Data” What is it? What are the challenges with it? Then we will move into what it means for all of you in this room. What is the opportunity for big data to impact the work of innovators? Finally, we will talk about what it means. We will review some real life examples of how big data was utilized to make smarter innovation choices. (faster and based on evidence) in short: product intelligence.
- #7: Present the solution: Playbook: cloud based platform to run the selected app and the SiGraph: the intelligence engine behind allows the connection of the dots in a way that could not be done before
- #10: So what are we going to talk about today? I’m going to use the 25 minutes I have to share with you how big data can be used to support innovation. First, we are going to start off talking about something you all probably sick of hearing about : “Big Data” What is it? What are the challenges with it? Then we will move into what it means for all of you in this room. What is the opportunity for big data to impact the work of innovators? Finally, we will talk about what it means. We will review some real life examples of how big data was utilized to make smarter innovation choices. (faster and based on evidence) in short: product intelligence.
- #11: So what are we going to talk about today? I’m going to use the 25 minutes I have to share with you how big data can be used to support innovation. First, we are going to start off talking about something you all probably sick of hearing about : “Big Data” What is it? What are the challenges with it? Then we will move into what it means for all of you in this room. What is the opportunity for big data to impact the work of innovators? Finally, we will talk about what it means. We will review some real life examples of how big data was utilized to make smarter innovation choices. (faster and based on evidence) in short: product intelligence.
- #12: So what are we going to talk about today? I’m going to use the 25 minutes I have to share with you how big data can be used to support innovation. First, we are going to start off talking about something you all probably sick of hearing about : “Big Data” What is it? What are the challenges with it? Then we will move into what it means for all of you in this room. What is the opportunity for big data to impact the work of innovators? Finally, we will talk about what it means. We will review some real life examples of how big data was utilized to make smarter innovation choices. (faster and based on evidence) in short: product intelligence.
- #13: Regardless of the trend and the perceptions, the problems you guys are faced with are real: None of us would be here today if bringing innovation was an easy task Constant tension between risk averse corporations and the need to innovate and show future
- #14: Regardless of the trend and the perceptions, the problems you guys are faced with are real: None of us would be here today if bringing innovation was an easy task Constant tension between risk averse corporations and the need to innovate and show future
- #16: Oral Care
- #18: Oral Care
- #26: Oral Care
- #27: Oral Care