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 repurposing involves finding new uses for existing drugs to treat rare diseases. It has advantages over developing new drugs including being faster, cheaper, and leveraging existing safety and use data. Opportunities for repurposing can be identified through screening compound libraries, literature mining, and 'omics approaches. A example is using the epilepsy drug sodium valproate identified from screening as a potential treatment for Wolfram syndrome, which is now in clinical trials.
Drug repurposing involves finding new uses for existing drugs to treat different diseases. It provides a more efficient and lower cost alternative to traditional drug development. Computational approaches like network-based, text mining, and semantic methods are used to discover novel drug-disease relationships for drug repurposing. These include identifying modules in biological networks, propagating information across networks, extracting relationships from literature, and constructing semantic networks to predict new associations. Drug repurposing reduces costs and risks compared to de novo drug development.
Can target-based drug discovery be reconciled with phenotypic assays in the context of drug repurposing? One of the questions discussed at the SLAS Drug Repurposing SIG meeting at SLAS2013.
This document describes Dr Warehouse, a proposed biomedical data warehouse designed to facilitate clinical research and improve translational research. Dr Warehouse would integrate both coded and free-text clinical data from multiple sources into a single searchable repository. Key features would include a search engine optimized to identify relevant patient cohorts despite negation and family history context, aggregate data visualization tools, and high-throughput phenotyping of patient cohorts to enrich clinical descriptions. The goal is to enable researchers to easily find eligible patients for studies, gain insights from mining phenotypic data, and close the loop between clinical care and research to accelerate new discoveries.
Establishing other new medical usages for already known drugs, including approved drugs.
Drug repurposing lies in repurposing an active pharmaceutical ingredient for a new indication that is already on the market.
Drug repurposing is a promising approach and mainly applied for the treatment of both common and rare genetic diseases, and it also offers significant benefits to the pharmaceutical industries.
"At its simplest, drug repurposing is taking an existing drug and seeing whether it can be used as an effective treatment for another condition.“
“Repurposing generally refers to studying drugs that are already approved to treat one disease or condition to see if they are safe and effective for treating other diseases”.
Nick Brown Drug Repositioning InformaticsNick Brown
AstraZeneca is developing informatics tools and search solutions to identify new opportunities for drug repositioning. They are using approaches like structure-based predictive modelling, mining existing drug information, and mechanistic repositioning to systematically consider alternative disease indications for compounds. Key initiatives include building an asset repositioning matrix, extending data sources, capturing biological process maps, and launching consortiums to facilitate drug repositioning and combination efforts. The goal is to unlock the potential of existing compounds in new disease areas through both internal efforts and external partnerships.
Challenges for drug development jsr slides aug 2013CincyTechUSA
This document discusses the challenges facing the pharmaceutical industry in drug development in the 21st century. It notes that R&D productivity has remained flat despite increased spending. Factors like the patent cliff, rising healthcare costs, and increased regulatory demands mean the industry can no longer rely on the blockbuster drug model. Innovation is now focused on targeted therapies for niche markets. Pharmacologists must guide drug development to demonstrate a new drug's safety, efficacy, and economic value in order to gain approval and reimbursement.
Drug repurposing involves finding new uses for existing drugs to treat rare diseases. It has advantages over developing new drugs including being faster, cheaper, and leveraging existing safety and use data. Opportunities for repurposing can be identified through screening compound libraries, literature mining, and 'omics approaches. A example is using the epilepsy drug sodium valproate identified from screening as a potential treatment for Wolfram syndrome, which is now in clinical trials.
Drug repurposing involves finding new uses for existing drugs to treat different diseases. It provides a more efficient and lower cost alternative to traditional drug development. Computational approaches like network-based, text mining, and semantic methods are used to discover novel drug-disease relationships for drug repurposing. These include identifying modules in biological networks, propagating information across networks, extracting relationships from literature, and constructing semantic networks to predict new associations. Drug repurposing reduces costs and risks compared to de novo drug development.
Can target-based drug discovery be reconciled with phenotypic assays in the context of drug repurposing? One of the questions discussed at the SLAS Drug Repurposing SIG meeting at SLAS2013.
This document describes Dr Warehouse, a proposed biomedical data warehouse designed to facilitate clinical research and improve translational research. Dr Warehouse would integrate both coded and free-text clinical data from multiple sources into a single searchable repository. Key features would include a search engine optimized to identify relevant patient cohorts despite negation and family history context, aggregate data visualization tools, and high-throughput phenotyping of patient cohorts to enrich clinical descriptions. The goal is to enable researchers to easily find eligible patients for studies, gain insights from mining phenotypic data, and close the loop between clinical care and research to accelerate new discoveries.
Establishing other new medical usages for already known drugs, including approved drugs.
Drug repurposing lies in repurposing an active pharmaceutical ingredient for a new indication that is already on the market.
Drug repurposing is a promising approach and mainly applied for the treatment of both common and rare genetic diseases, and it also offers significant benefits to the pharmaceutical industries.
"At its simplest, drug repurposing is taking an existing drug and seeing whether it can be used as an effective treatment for another condition.“
“Repurposing generally refers to studying drugs that are already approved to treat one disease or condition to see if they are safe and effective for treating other diseases”.
Nick Brown Drug Repositioning InformaticsNick Brown
AstraZeneca is developing informatics tools and search solutions to identify new opportunities for drug repositioning. They are using approaches like structure-based predictive modelling, mining existing drug information, and mechanistic repositioning to systematically consider alternative disease indications for compounds. Key initiatives include building an asset repositioning matrix, extending data sources, capturing biological process maps, and launching consortiums to facilitate drug repositioning and combination efforts. The goal is to unlock the potential of existing compounds in new disease areas through both internal efforts and external partnerships.
Challenges for drug development jsr slides aug 2013CincyTechUSA
This document discusses the challenges facing the pharmaceutical industry in drug development in the 21st century. It notes that R&D productivity has remained flat despite increased spending. Factors like the patent cliff, rising healthcare costs, and increased regulatory demands mean the industry can no longer rely on the blockbuster drug model. Innovation is now focused on targeted therapies for niche markets. Pharmacologists must guide drug development to demonstrate a new drug's safety, efficacy, and economic value in order to gain approval and reimbursement.
Repositioning Old Drugs For New Indications Using Computational ApproachesYannick Pouliot
Topiramate was identified as a potential drug candidate for inflammatory bowel disease (IBD) using a computational approach. Gene expression profiles of drugs and disease states were analyzed to find drugs that induced the reciprocal signature of IBD tissues compared to normal tissues. Topiramate decreased diarrhea in a rat model of IBD and counter-expressed genes observed in microarray data. This provides proof that drugs affecting gene expression anti-correlated to disease patterns may treat symptoms.
Re-Engineering Early Phase Cancer Drug Development: Decreasing the Time from ...mconghuyen
The document summarizes efforts to decrease the time required to develop novel cancer therapeutics from target identification to clinical use. It describes how most oncology drugs fail in late stages of development, particularly phases 2 and 3, due to lack of efficacy. To address this, the National Cancer Institute has created programs like the Experimental Therapeutics Program and Chemical Biology Consortium to streamline the discovery and development process. This includes providing resources from target validation through early clinical trials to support academic and biotech projects focusing on areas of unmet medical need. The goal is to rapidly translate discoveries into treatments to benefit public health.
Overcoming challenges in Drug DevelopmentCharles Oo
This document outlines strategies for overcoming challenges in drug development. It discusses the current long and expensive drug development process, as well as growing regulatory hurdles. It argues that innovation is needed, including open innovation models, a shift to personalized medicine, balancing drug toxicity and safety, leveraging technological advances like biomarkers, and using adaptive clinical trial designs. The key message is that new approaches are required to reduce costs, cycle times, and failure rates in drug development.
The document discusses the key stages in the drug discovery and development process including target selection, compound screening and hit optimization, selecting a drug candidate through further optimization of properties like absorption and metabolism, safety testing in animals and humans, proof of concept clinical trials in patients, large phase 3 clinical trials for registration and approval, and finally launch and life cycle management. It notes that the entire process from discovery to approval can take 12-16 years and cost over $1 billion.
GlobeImmune is a biotechnology company founded in 1995 by three University of Colorado faculty to commercialize their inventions from the lab. The company developed recombinant yeast-based immunotherapies and vaccines, with an initial focus on HIV. After hiring a professional CEO in 2002 and obtaining venture capital financing, the company shifted its focus to cancer immunotherapy. GlobeImmune has raised over $180 million in financing to date and completed multiple clinical trials. Its lead products are whole, heat-killed recombinant yeast immunotherapeutics for various cancer indications.
Overcoming obstacles to repurposing for neurodegenerative diseaseLona Vincent
This document discusses the challenges of repurposing FDA-approved drugs for neurodegenerative diseases. It notes that while repurposing can accelerate development timelines and reduce costs compared to new drug development, it still requires expensive clinical trials. It also notes that by the time a drug is approved, there is typically less than 10 years of patent life remaining, which is not enough time to generate efficacy data for a new indication and achieve commercial returns. Additionally, limited patent protection makes commercialization and reimbursement difficult. The document proposes that philanthropy, industry, and government need to address these challenges through policy changes and targeted funding to promote repurposing as a strategy to increase treatment options for patients.
Exploring Molecular Targets for Repositioning of Hypertensive DrugsYogeshIJTSRD
Drug repositioning or drug repurposing or drug profiling is the discovery of new applications for approved or failed drug.. Drug repositioning is the development of new approved drug applications. The cost of bringing a medicine to the market is around one million which include clinical and preclinical trials. Repositioning of drugs help in cutting down costs as well as time involve in intial validation and authorization. The procedure involved in Drug repositioning is generally performed during the drug development phase to modify or extend an active molecules distribution line. On a fundamental level, repositioning opportunities exist because drugs perturb multiple biological entities and engage themselves in multiple biological processes. Therefore, a drug can play multiple roles or perform a various mode of actions that are responsible for its pharmacology. Hypertension, is a condition that causes increase in the risk of cardiovascular diseases. In this study an attempt has been made to reposition hypertensive drugs for different diseases by exploring molecular targets of hypertensive drugs. Consider that they often need to be administered for long periods of time, often over whole life time Side effects although present, have been found safe enough to be used for such long durations, hence repurposing these drugs for other diseases may be beneficial with limited side effects. Bhawna Singh | Asmita Das "Exploring Molecular Targets for Repositioning of Hypertensive Drugs" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39910.pdf Paper URL: https://www.ijtsrd.com/biological-science/bioinformatics/39910/exploring-molecular-targets-for-repositioning-of-hypertensive-drugs/bhawna-singh
Toward semantic modeling of pharmacogenomic knowledge for clinical and transl...Richard Boyce, PhD
A project update describing the semantic annotation of pharmacogenomics statements in drug product labeling. An innovative aspect of the work is the use of the W3C Open Annotation standard for publishing semantic annotations.
This document provides an overview of careers in drug discovery and development. It discusses the multi-stage process of discovering new drugs, from identifying drug targets through clinical trials and regulatory approval. The document notes that drug development is a highly time-intensive and costly process involving many disciplines. It also aims to dispel common myths about careers in the pharmaceutical industry, emphasizing that industry scientists have opportunities for publication, innovation, and interesting work.
The document discusses the process and costs associated with drug development. It notes that the average cost to develop a new drug is $350 million to $5.5 billion and the process takes 6.5-7 years from discovery to approval. Key barriers to drug development include high financial costs, lengthy timelines for clinical trials, and regulatory hurdles. Approaches to reduce costs and timelines include greater use of electronic health records, simplifying clinical trial protocols, and utilizing decentralized clinical trial models.
Initial progress on the journey toward an open source potential drug-drug int...Richard Boyce, PhD
Presentation given at the 33rd VistA Community Meeting - George Mason University focusing on progress towards and open source potential drug interaction knowledge base
The slides from the keynote given by Dr. Dan Malone RPh, PhD at the First International Drug-Drug Interaction Knowledge Representation Workshop on October 6th 2014 (http://icbo14.com/sessions/drug-drug-interaction-knowledge-representation-workshop/). Posted with his permission.
Transitioning to Clinical Drug DevelopmentCharles Oo
This document discusses optimizing the transition from non-clinical to clinical phases in drug development. It notes that while drug design and discovery has advanced in non-clinical phases, application to clinical phases has not progressed as quickly. To improve success rates and reduce costs, the document recommends enhancing translational ability between phases by improving predictive models, biomarkers, and team experience. It also stresses characterizing exposure, binding, and target site pharmacology more thoroughly in non-clinical phases to improve predictability and verification in clinical trials. The goal is a smoother transition between research areas to facilitate early clinical development.
The document discusses the stages of clinical drug development, including preclinical testing, Phase I-III trials, and regulatory approval. Preclinical testing assesses safety in animals before human trials. Phase I trials primarily evaluate safety in small human groups. Phase II trials further assess safety and preliminary efficacy. Phase III trials are large-scale, placebo-controlled trials to prove efficacy and long-term safety for regulatory approval. The goal is to advance safely from preclinical to clinical testing and approval.
Piloting a Comprehensive Knowledge Base for Pharmacovigilance Using Standardi...Richard Boyce, PhD
A presentation of a new adverse drug event evidence base (Laertes - http://goo.gl/nZSqVw) within a standard framework for clinical research (OHDSI - www.ohdsi.org) made at the American Medical Informatics Association Joint Summits on Translational Research on 3/26/2015
Basics of Drug Discovery and DevelopmentJhony Sheik
The document outlines the process of drug discovery and development from initial screening of chemicals to determine biological activity through clinical trials and regulatory approval. It notes that of 10,000 initially screened chemicals, only 1 may reach the market place due to the high costs, risks and regulatory hurdles. The key stages discussed are preclinical testing in animals, filing an Investigational New Drug application for human trials, conducting clinical trials in four phases, filing a New Drug Application providing trial results for regulatory review and approval, large-scale manufacturing, and filing an Abbreviated New Drug Application for generic approvals relying on previously approved drugs.
Drug Development Life Cycle - Costs and RevenueRobert Sturm
Presentation explains the Drug Development Process in terms of time/costs from initial research to final manufacturing. It presents strategies for increasing profits/decreasing costs, shows the impact of generics and details how Information Technology fits into this equation. It uses research from DiMasi and Grabowski to identify drug costs and product revenue.
Introduction to the drug discovery processThanh Truong
This document discusses the drug discovery process from target identification through FDA approval. It describes methods used for target identification such as genomics, bioinformatics, and proteomics. The stages of lead identification through high-throughput screening and structure-based drug design are outlined. Key aspects of lead optimization like characterizing potency, efficacy, pharmacokinetics, and toxicity are summarized. Details are provided on preclinical and clinical trial phases from Phase 0 through Phase IV post-marketing surveillance. Factors contributing to the declining drug approval rate like increased safety demands are noted. The high costs and failure rates associated with drug development are highlighted.
Drug discovery process style 3 powerpoint presentation templatesSlideTeam.net
The document summarizes the key steps in the drug discovery process. It involves:
1) Identifying a biological target molecule through genomic research and functional analysis of genes.
2) Discovering seed lead compounds through high-throughput screening and combinatorial chemistry.
3) Scrutinizing drug candidates through estimation of efficacy, safety evaluation, pharmacokinetics studies, and manufacturing development.
4) Conducting clinical studies and applying for a new drug approval.
Systems Pharmacology 1: Drug re-positioning predictionAli Kishk
This document discusses drug repositioning prediction through systems pharmacology. It describes obtaining gene expression profiles from drugs in the LINCS database and using enrichment analysis to predict new disease indications. Specifically, it provides steps to get downregulated genes for a drug from LINCS Canvas Browser, then use Enrichr to analyze enriched diseases based on those genes. A demo is shown obtaining salbutamol's gene list and analyzing enriched diseases. The output includes top enriched diseases and shared genes between the input list and each disease.
Repositioning Old Drugs For New Indications Using Computational ApproachesYannick Pouliot
Topiramate was identified as a potential drug candidate for inflammatory bowel disease (IBD) using a computational approach. Gene expression profiles of drugs and disease states were analyzed to find drugs that induced the reciprocal signature of IBD tissues compared to normal tissues. Topiramate decreased diarrhea in a rat model of IBD and counter-expressed genes observed in microarray data. This provides proof that drugs affecting gene expression anti-correlated to disease patterns may treat symptoms.
Re-Engineering Early Phase Cancer Drug Development: Decreasing the Time from ...mconghuyen
The document summarizes efforts to decrease the time required to develop novel cancer therapeutics from target identification to clinical use. It describes how most oncology drugs fail in late stages of development, particularly phases 2 and 3, due to lack of efficacy. To address this, the National Cancer Institute has created programs like the Experimental Therapeutics Program and Chemical Biology Consortium to streamline the discovery and development process. This includes providing resources from target validation through early clinical trials to support academic and biotech projects focusing on areas of unmet medical need. The goal is to rapidly translate discoveries into treatments to benefit public health.
Overcoming challenges in Drug DevelopmentCharles Oo
This document outlines strategies for overcoming challenges in drug development. It discusses the current long and expensive drug development process, as well as growing regulatory hurdles. It argues that innovation is needed, including open innovation models, a shift to personalized medicine, balancing drug toxicity and safety, leveraging technological advances like biomarkers, and using adaptive clinical trial designs. The key message is that new approaches are required to reduce costs, cycle times, and failure rates in drug development.
The document discusses the key stages in the drug discovery and development process including target selection, compound screening and hit optimization, selecting a drug candidate through further optimization of properties like absorption and metabolism, safety testing in animals and humans, proof of concept clinical trials in patients, large phase 3 clinical trials for registration and approval, and finally launch and life cycle management. It notes that the entire process from discovery to approval can take 12-16 years and cost over $1 billion.
GlobeImmune is a biotechnology company founded in 1995 by three University of Colorado faculty to commercialize their inventions from the lab. The company developed recombinant yeast-based immunotherapies and vaccines, with an initial focus on HIV. After hiring a professional CEO in 2002 and obtaining venture capital financing, the company shifted its focus to cancer immunotherapy. GlobeImmune has raised over $180 million in financing to date and completed multiple clinical trials. Its lead products are whole, heat-killed recombinant yeast immunotherapeutics for various cancer indications.
Overcoming obstacles to repurposing for neurodegenerative diseaseLona Vincent
This document discusses the challenges of repurposing FDA-approved drugs for neurodegenerative diseases. It notes that while repurposing can accelerate development timelines and reduce costs compared to new drug development, it still requires expensive clinical trials. It also notes that by the time a drug is approved, there is typically less than 10 years of patent life remaining, which is not enough time to generate efficacy data for a new indication and achieve commercial returns. Additionally, limited patent protection makes commercialization and reimbursement difficult. The document proposes that philanthropy, industry, and government need to address these challenges through policy changes and targeted funding to promote repurposing as a strategy to increase treatment options for patients.
Exploring Molecular Targets for Repositioning of Hypertensive DrugsYogeshIJTSRD
Drug repositioning or drug repurposing or drug profiling is the discovery of new applications for approved or failed drug.. Drug repositioning is the development of new approved drug applications. The cost of bringing a medicine to the market is around one million which include clinical and preclinical trials. Repositioning of drugs help in cutting down costs as well as time involve in intial validation and authorization. The procedure involved in Drug repositioning is generally performed during the drug development phase to modify or extend an active molecules distribution line. On a fundamental level, repositioning opportunities exist because drugs perturb multiple biological entities and engage themselves in multiple biological processes. Therefore, a drug can play multiple roles or perform a various mode of actions that are responsible for its pharmacology. Hypertension, is a condition that causes increase in the risk of cardiovascular diseases. In this study an attempt has been made to reposition hypertensive drugs for different diseases by exploring molecular targets of hypertensive drugs. Consider that they often need to be administered for long periods of time, often over whole life time Side effects although present, have been found safe enough to be used for such long durations, hence repurposing these drugs for other diseases may be beneficial with limited side effects. Bhawna Singh | Asmita Das "Exploring Molecular Targets for Repositioning of Hypertensive Drugs" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39910.pdf Paper URL: https://www.ijtsrd.com/biological-science/bioinformatics/39910/exploring-molecular-targets-for-repositioning-of-hypertensive-drugs/bhawna-singh
Toward semantic modeling of pharmacogenomic knowledge for clinical and transl...Richard Boyce, PhD
A project update describing the semantic annotation of pharmacogenomics statements in drug product labeling. An innovative aspect of the work is the use of the W3C Open Annotation standard for publishing semantic annotations.
This document provides an overview of careers in drug discovery and development. It discusses the multi-stage process of discovering new drugs, from identifying drug targets through clinical trials and regulatory approval. The document notes that drug development is a highly time-intensive and costly process involving many disciplines. It also aims to dispel common myths about careers in the pharmaceutical industry, emphasizing that industry scientists have opportunities for publication, innovation, and interesting work.
The document discusses the process and costs associated with drug development. It notes that the average cost to develop a new drug is $350 million to $5.5 billion and the process takes 6.5-7 years from discovery to approval. Key barriers to drug development include high financial costs, lengthy timelines for clinical trials, and regulatory hurdles. Approaches to reduce costs and timelines include greater use of electronic health records, simplifying clinical trial protocols, and utilizing decentralized clinical trial models.
Initial progress on the journey toward an open source potential drug-drug int...Richard Boyce, PhD
Presentation given at the 33rd VistA Community Meeting - George Mason University focusing on progress towards and open source potential drug interaction knowledge base
The slides from the keynote given by Dr. Dan Malone RPh, PhD at the First International Drug-Drug Interaction Knowledge Representation Workshop on October 6th 2014 (http://icbo14.com/sessions/drug-drug-interaction-knowledge-representation-workshop/). Posted with his permission.
Transitioning to Clinical Drug DevelopmentCharles Oo
This document discusses optimizing the transition from non-clinical to clinical phases in drug development. It notes that while drug design and discovery has advanced in non-clinical phases, application to clinical phases has not progressed as quickly. To improve success rates and reduce costs, the document recommends enhancing translational ability between phases by improving predictive models, biomarkers, and team experience. It also stresses characterizing exposure, binding, and target site pharmacology more thoroughly in non-clinical phases to improve predictability and verification in clinical trials. The goal is a smoother transition between research areas to facilitate early clinical development.
The document discusses the stages of clinical drug development, including preclinical testing, Phase I-III trials, and regulatory approval. Preclinical testing assesses safety in animals before human trials. Phase I trials primarily evaluate safety in small human groups. Phase II trials further assess safety and preliminary efficacy. Phase III trials are large-scale, placebo-controlled trials to prove efficacy and long-term safety for regulatory approval. The goal is to advance safely from preclinical to clinical testing and approval.
Piloting a Comprehensive Knowledge Base for Pharmacovigilance Using Standardi...Richard Boyce, PhD
A presentation of a new adverse drug event evidence base (Laertes - http://goo.gl/nZSqVw) within a standard framework for clinical research (OHDSI - www.ohdsi.org) made at the American Medical Informatics Association Joint Summits on Translational Research on 3/26/2015
Basics of Drug Discovery and DevelopmentJhony Sheik
The document outlines the process of drug discovery and development from initial screening of chemicals to determine biological activity through clinical trials and regulatory approval. It notes that of 10,000 initially screened chemicals, only 1 may reach the market place due to the high costs, risks and regulatory hurdles. The key stages discussed are preclinical testing in animals, filing an Investigational New Drug application for human trials, conducting clinical trials in four phases, filing a New Drug Application providing trial results for regulatory review and approval, large-scale manufacturing, and filing an Abbreviated New Drug Application for generic approvals relying on previously approved drugs.
Drug Development Life Cycle - Costs and RevenueRobert Sturm
Presentation explains the Drug Development Process in terms of time/costs from initial research to final manufacturing. It presents strategies for increasing profits/decreasing costs, shows the impact of generics and details how Information Technology fits into this equation. It uses research from DiMasi and Grabowski to identify drug costs and product revenue.
Introduction to the drug discovery processThanh Truong
This document discusses the drug discovery process from target identification through FDA approval. It describes methods used for target identification such as genomics, bioinformatics, and proteomics. The stages of lead identification through high-throughput screening and structure-based drug design are outlined. Key aspects of lead optimization like characterizing potency, efficacy, pharmacokinetics, and toxicity are summarized. Details are provided on preclinical and clinical trial phases from Phase 0 through Phase IV post-marketing surveillance. Factors contributing to the declining drug approval rate like increased safety demands are noted. The high costs and failure rates associated with drug development are highlighted.
Drug discovery process style 3 powerpoint presentation templatesSlideTeam.net
The document summarizes the key steps in the drug discovery process. It involves:
1) Identifying a biological target molecule through genomic research and functional analysis of genes.
2) Discovering seed lead compounds through high-throughput screening and combinatorial chemistry.
3) Scrutinizing drug candidates through estimation of efficacy, safety evaluation, pharmacokinetics studies, and manufacturing development.
4) Conducting clinical studies and applying for a new drug approval.
Systems Pharmacology 1: Drug re-positioning predictionAli Kishk
This document discusses drug repositioning prediction through systems pharmacology. It describes obtaining gene expression profiles from drugs in the LINCS database and using enrichment analysis to predict new disease indications. Specifically, it provides steps to get downregulated genes for a drug from LINCS Canvas Browser, then use Enrichr to analyze enriched diseases based on those genes. A demo is shown obtaining salbutamol's gene list and analyzing enriched diseases. The output includes top enriched diseases and shared genes between the input list and each disease.
Drug discovery process powerpoint presentation slides ppt templatesSlideTeam.net
The document describes the drug discovery process. It involves 10,000 to 20,000 candidate drugs undergoing discovery and screening. Promising candidates then undergo lead optimization using combinatorial chemistry and structure-based drug design. Finally, drugs must pass ADMET studies and clinical trials to receive FDA approval and reach the market.
The document discusses the hit to lead (H2L) stage of drug discovery. In this stage, small molecule hits identified from high-throughput screening undergo limited optimization to identify lead compounds with improved binding affinity, selectivity, metabolic properties, and other qualities. The goal is to progress compounds from the micromolar binding range to nanomolar binding through synthetic analogs before advancing to the lead optimization stage. Key aspects of H2L include hit confirmation, expansion through synthetic analogs, and selection of lead series based on various criteria for further exploration.
This document discusses the process of finding a lead compound in drug discovery. It describes the key steps as: 1) Choosing the disease to target. Factors like prevalence and market size are considered. 2) Choosing a drug target like a receptor or enzyme involved in the disease. Specificity and selectivity are important. 3) Identifying a bioassay or test to evaluate compounds, including in vitro and in vivo tests. High throughput screening allows testing many compounds quickly. 4) Finding a lead compound through various methods like screening natural products, existing drugs, combinatorial libraries, or computer-aided design. The goal is to discover compounds with the desired activity to use as a starting point for drug development.
In Vitro ADMET Considerations for Drug Discovery and Lead GenerationOSUCCC - James
This document provides an overview of in vitro ADMET (absorption, distribution, metabolism, excretion, toxicity) assays that are used during drug discovery and development. Key points:
- In vitro assays are designed to mimic what happens to a compound in vivo and provide early data on absorption, distribution, metabolic transformations, potential toxicity, and more.
- Common assays examine solubility, permeability, protein binding, metabolic stability, metabolism pathways, toxicity, and effects of transporters and drug-drug interactions.
- The data generated from these assays are used throughout the drug development process to inform compound selection, design better candidates, and identify liabilities early. Understanding a compound's properties helps optimize the likelihood of success
This document discusses the key principles and processes involved in drug discovery and drug-receptor interactions. It outlines the steps of choosing a disease target, identifying a bioassay to test potential drug candidates, finding and isolating lead compounds, determining a drug's structure and effects, and identifying forces that cause drug-receptor binding such as covalent bonding, hydrogen bonding, and hydrophobic interactions. The goal is to discover and develop safe and effective therapeutic drugs through a scientific process.
The document provides an overview of the drug discovery and development process. It discusses the various stages involved, including target selection using genomics, proteomics and bioinformatics; lead discovery through synthesis, isolation and high-throughput screening; medicinal chemistry such as structure-activity relationships studies; in vitro and preclinical in vivo testing in animal models; and clinical trials in humans. The timeline for this process can span over 10-15 years from drug target identification to regulatory approval. Key techniques and approaches at each stage are also summarized.
The document discusses the process of drug discovery, including target selection, lead discovery, medicinal chemistry, in vitro and in vivo studies, and clinical trials. Target selection involves identifying cellular or genetic targets involved in disease through techniques like genomics, proteomics, and bioinformatics. Lead discovery focuses on identifying small molecule modulators of protein function through methods like synthesis, combinatorial chemistry, assay development, and high-throughput screening. Medicinal chemistry then works to optimize these leads. [/SUMMARY]
This document discusses balancing pharmaceutical innovation and public health. It notes that while the current patent system incentivizes drug development, it can compromise access and public health goals in some cases. Problems include inappropriate patents, patents not rewarding true discoverers, and manipulation of regulations. Some areas like antibiotics face misaligned incentives as short courses are unlikely to be blockbusters. Proposed reforms address patent and regulatory abuse while ensuring important new drugs are created.
The drug development process takes 10-15 years and costs over $800 million on average to develop a new drug. Only about 1 in 5,000-10,000 compounds tested make it to consumers, and only 3 of 10 drugs that reach the market earn back their R&D costs. The process involves extensive research, pre-clinical testing on animals, and clinical trials on humans in 3 phases before the FDA reviews the new drug application. If approved, large-scale manufacturing must be developed to produce the drug.
The report enhances decision making capabilities and help to create effective counter strategies to gain competitive advantage. It strengthens R&D pipelines by identifying new targets and MOAs to produce first-in-class and best-in-class products.
Slides presented by me at the Korean-American Professional Association in Life Sciences (KAPAL) 5th Annual Meeting in Rockville, MD. Slides discuss the recent reorganization of the Center for Drug Evaluation and Research at the FDA
This document summarizes an opportunity for an initial public offering (IPO) of a pharmaceutical startup focused on women's health. The startup has a portfolio of four clinically advanced products targeting large markets with unmet needs, including two phase III-ready oral contraceptives. The summary seeks $5-10 million in funding to support research and development activities over the next 15 months in preparation for an IPO with a target valuation exceeding $180 million. Key activities include advancing two products into phase III trials, opening two investigational new drug applications, and completing commercial assessments. The portfolio addresses major issues in contraception, uterine fibroids, endometriosis, and painful periods, with potential to generate billions in annual sales and provide
Non alcoholic steatohepatitis - pipeline review, h1 2014Ambikabasa
This report provides comprehensive information on the therapeutic development for Non-Alcoholic Steatohepatitis, complete with comparative analysis at various stages, therapeutics assessment by drug target, mechanism of action (MoA), route of administration (RoA) and molecule type, along with latest updates, and featured news and press releases. It also reviews key players involved in the therapeutic development for Non-Alcoholic Steatohepatitis and special features on late-stage and discontinued projects.
Presentation by Andreas Grauer, MD, Executive Medical Director, Global Development Leader, Amgen at the marcus evans Evolution Summit Fall 2015 in Las Vegas
This report provides comprehensive information on the therapeutic development for Brain Cancer, complete with comparative analysis at various stages, therapeutics assessment by drug target, mechanism of action (MoA), route of administration (RoA) and molecule type, along with latest updates, and featured news and press releases. It also reviews key players involved in the therapeutic development for Brain Cancer and special features on late-stage and discontinued projects.
http://www.researchmoz.us/brain-cancer-pipeline-review-h1-2015-report.html
Drug discovery and development is a long, expensive, and complex process averaging about 12 years and $500 million to bring a new prescription medication to market. Only 1 in 10,000 compounds eventually becomes an approved drug. The process involves discovery, preclinical research, clinical trials, and regulatory approval. Discovery aims to identify candidate drug molecules, while preclinical research studies their safety and efficacy in animal models before human testing. Clinical trials then evaluate new drugs with patients for safety and effectiveness over several phases before regulatory approval and marketing.
Introduction to Regulatory Affairs - Pauwels Consulting AcademyPauwels Consulting
On Tuesday, June 14, our colleagues Fiorenzo Savoretti, Senior Regulatory and Quality Consultant at Pfizer and Nick Deschacht, Senior RA Consultant at GSK, gave an interesting “Introduction to Regulatory Affairs”.
Fiorenzo and Nick talked about RA and their projects, each from their unique angle. They delivered their presentations for ## attendees at our Brussels office at the Lambroekstraat 5a in Diegem.
Commercial considerations in early drug developmentSunil Ramkali
It is important in the drug development process that marketers and researchers collaborate early to ensure that products being developed are truly innovative and deliver brand value to the different end users in a way that the product and the subsequent brand messaging is relevant, compelling and differentiating compared to the competition. T
In the market place that is heavily cost constraint, innovation is no longer about a unique mode of action or a new formulation, but more about the incremental brand value offered by new pharmaceutical products over existing treatments (standard of care) and how much healthcare systems are prepared to pay for these incremental benefits. My lecture at the Department of Innovation, Lund University, Sweden explored the importance of R&D functions getter closer to external stakeholders to really understand their needs, how they define brand value and the importance of considering this early in the drug development process.
The document provides an overview of the therapeutic pipeline for travelers diarrhea as of the first half of 2015. It details over 20 companies and universities developing treatments across various stages. Key late stage products include rifamycin SV MMX and prulifloxacin. The report analyzes the pipeline by target, mechanism of action, route of administration, and molecule type. It provides profiles for the major pipeline products along with recent updates and featured news stories on developments.
Discovery of Drug and Introduction to Clinical Trial__Katalyst HLSKatalyst HLS
This document provides an overview of the drug discovery and clinical trials process. It discusses the goals of drug discovery which include identifying new chemical entities and developing medicines to address unmet medical needs. The drug discovery process involves target identification, validation, lead generation, and optimization. Pre-clinical testing is then conducted to evaluate safety and effects. If successful, an investigational new drug application is filed with the FDA prior to beginning clinical trials. Clinical trials involve 4 phases to test safety and efficacy in humans. Upon completion, a new drug application can be filed for FDA review and potential approval.
This document discusses personalized medicine and pharmacogenomics. It begins by noting that current drug treatment is only effective for 60% of patients, with 40% experiencing poor effects or no effect at all. It then introduces pharmacogenomics as the application of genomics to understand how genes influence individual responses to drugs. The document outlines several ways that pharmacogenomic research could improve drug development and clinical practice, such as identifying genetic variants that influence drug metabolism and toxicity. It envisions that in the future, pharmacogenomic testing may allow for "made-to-order" drugs tailored to a patient's genetic profile. However, it also notes some bioethical challenges will need to be addressed for personalized medicine to be realized.
Epilepsy Drugs Market PPT: Growth, Outlook, Demand, Keyplayer Analysis and Op...IMARC Group
The global epilepsy drugs market size reached US$ 2.3 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 4.4 Billion by 2032, exhibiting a growth rate (CAGR) of 7.16% during 2024-2032.
More Info:- https://www.imarcgroup.com/epilepsy-drugs-market
This document provides an overview of nanoparticle-based drug delivery technologies. It discusses how nanoparticles can help address challenges in traditional drug formulations by improving water solubility and targeting specificity. While only a few nanoparticle therapies have been FDA-approved so far, the author argues that these technologies are already impacting medicine and their impact will likely grow in the coming years. The document also reviews the drug development process and pressures facing pharmaceutical companies to improve success rates and reduce costs. Nanotechnology may help address these challenges through miniaturization, automation, high-throughput screening and other techniques.
This document provides an overview of nanoparticle-based drug delivery technologies. It discusses how nanoparticles can help address challenges in traditional drug formulations by improving water solubility and targeting specificity. While only a few nanoparticle therapies have been FDA-approved so far, the author argues that these technologies are already impacting medicine and their impact will likely accelerate in coming years. The document also reviews the drug development process and pressures facing pharmaceutical companies to improve success rates and reduce costs. Nanotechnology may help address these challenges through miniaturization, automation, high-throughput screening and other techniques.
The document discusses the complex and unpredictable nature of the FDA drug approval process. While the steps of drug development may seem formulaic, including discovery, preclinical testing, and clinical trials, success is not guaranteed as programs face many risks and intangible factors. Understanding these challenges is important for mitigating risks and strategizing development approaches. The FDA approval process aims to ensure new drugs are safe and effective for patients.
Post marketing surveilance, outsourcing BA and BE to CROJahnabi Sarmah
This document discusses post-marketing surveillance, outsourcing bioavailability and bioequivalence studies to contract research organizations. It provides an introduction to post-marketing surveillance, describing its role in monitoring drug safety after market approval. A brief history is given of pivotal drug safety issues that led to the establishment of formal post-marketing surveillance systems. Common sources of post-marketing information are also outlined. The document defines outsourcing, bioavailability, bioequivalence, and contract research organizations. It explains how outsourcing is used to reduce costs and improve efficiency through utilizing external partners for certain studies and services.
PAIN MANAGEMENT- NEW DISCOVERIES AND TREATMENT OPTIONS IN ABUSE DETERRENT ...Jagdish Gohil
This document provides an overview of pain management technologies and treatments, with a focus on abuse-deterrent formulations of opioids. It discusses the FDA's efforts to address the opioid epidemic through new guidelines for abuse-deterrent drugs and formulations. Several approved and pipeline abuse-deterrent opioid formulations are described, along with their drug delivery technologies. Emerging non-opioid treatments for pain including new drug targets and mechanisms of action are also reviewed, which may help reduce opioid use. The document aims to analyze the impact of regulatory changes and new technologies on the opioid drug market in both the US and Europe.
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
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 | info@signalsgroup.com
THANK YOU
Editor's Notes
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.
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
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.
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.
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.
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
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