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00M-648 - IBM Rational IT Sales Mastery Test v2 - BrainDump Information

Vendor Name : IBM
Exam Code : 00M-648
Exam Name : IBM Rational IT Sales Mastery Test v2
Questions and Answers : 81 Q & A
Updated On : March 21, 2019
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00M-648 exam Dumps Source : IBM Rational IT Sales Mastery Test v2

Test Code : 00M-648
Test Name : IBM Rational IT Sales Mastery Test v2
Vendor Name : IBM
Q&A : 81 Real Questions

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IBM IBM Rational IT Sales

IBM (IBM) Up 3.9% given that ultimate profits file: Can It proceed? | killexams.com Real Questions and Pass4sure dumps

A month has passed by due to the fact the final salary file for IBM (IBM). Shares have brought about 3.9% in that time frame, underperforming the S&P 500.

Will the contemporary fine trend continue leading up to its subsequent salary unencumber, or is IBM due for a pullback? before we dive into how traders and analysts have reacted as of late, let's take a quick seem on the most contemporary revenue record as a way to get a stronger deal with on the critical drivers.

IBM q4 salary Beat Estimates, Revenues Decline Y/Y

foreign business Machines Corp delivered fourth-quarter 2018 non-GAAP revenue of $4.87 per share, which beat the Zacks Consensus Estimate of $four.81 per share. besides the fact that children, salary per share (EPS) decreased 5.9% from the yr-in the past quarter. The 12 months-over-yr decline in EPS may also be attributed to bigger tax rate.

Revenues of $21.76 billion have been pretty much in response to the Zacks Consensus Estimate of $21.seventy four billion and declined three.5% on a yr-over-yr groundwork. At consistent foreign money (cc), revenues dipped 1%. The yr-over-year decline can basically be attributed to currency fluctuation and headwinds from IBM Z product cycle.

above all, IBM pointed out that signings surged 21% on cc groundwork to $15.8 billion. features backlog declined 1% yr over yr and got here in at $116 billion.

Geographic salary particulars

Revenues from Americas had been down four%, reflecting the headwind from the IBM Z product cycle. despite the fact, continued increase in Latin america changed into a favorable.

Europe, middle-East and Africa expanded 2% from the year-in the past quarter principally because of growth in Spain, Germany, Italy and the U.k.

Asia-Pacific revenues declined 1% on a yr-over-12 months basis with modest increase in Japan.

Strategic Imperatives increase Continues

Strategic Imperatives (cloud, analytics, mobility and security) grew 5% at cc from the 12 months-ago quarter to $11.5 billion. with the exception of IBM Z product cycle affect Strategic Imperatives grew eleven% yr over 12 months.

safety revenues surged 17% (with the exception of IBM Z product cycle have an effect on) and declined three% on cc groundwork. On a trailing 12-month foundation, Strategic Imperatives revenues were $40 billion, up 9%.

Cloud revenues surged 6% from the year-ago quarter to $5.7 billion and 19% (aside from IBM Z product cycle influence). The annual run rate for cloud as-a-service revenues accelerated 21% at cc on a 12 months-over-yr foundation to $12.2 billion.

Cloud revenues of $19.2 billion on a trailing 12-month groundwork accelerated 12% yr over 12 months.

Cognitive Revenues Surge

Cognitive solutions’ revenues-exterior improved 2% year over year (on cc groundwork) to $5.5 billion. Revenues from Cognitive solutions (together with options utility and transaction processing) improved essentially because of growth in options application, including analytics and synthetic intelligence (AI).

Segmental revenues touching on Strategic Imperatives and Cloud increased 9% and 5%, respectively. Cloud as-a-provider salary annual run fee was $2 billion.

solutions software comprises offerings in strategic verticals like health, area-certain capabilities like analytics and protection, and IBM’s rising technologies of AI and blockchain. The section additionally comprises offerings that handle horizontal domains like collaboration, commerce and skill. within the pronounced quarter, options application revenues accelerated three% yr over yr.

IBM stated that the integration of AI into offerings like consumer adventure analytics in commerce area helped SaaS signings to develop in double digit in the mentioned quarter.

Transaction Processing application includes software that runs mission-important workloads, leveraging IBM’s hardware systems. Revenues have been up 1% on a 12 months-over-yr basis.

IBM witnessed increase in industry verticals like fitness, key areas of analytics and protection in the quarter. Watson fitness witnessed extensive-based mostly increase in Payer, company, Imaging and life Sciences domains.

all through the fourth quarter, IBM extended partnership with Vodafone community. Per the deal, IBM’s advanced hybrid cloud platform, AI, web of things (“IoT”) capabilities will assist Vodafone business with digital transformation initiatives.

IBM brought up that analytics carried out well within the quarter, driven through facts science choices and IBM Cloud deepest for statistics offering.

protection boom became driven via offerings in orchestration, records safety and endpoint management.

Story continues

In blockchain, IBM introduced addition of a couple of new customers all over the quarter, which includes “work with wise Dubai on the center East’s first government-recommended blockchain platform.” The business additionally unveiled an on-prem providing throughout the stated quarter, the IBM Blockchain Platform for IBM Cloud deepest. several new deal wins is also assisting IBM to reinforce its foothold in blockchain technology.

international business functions Revenues increase

Revenues from world company features-exterior section had been $four.3 billion, up 4% from the yr-in the past quarter (up 6% at cc). The yr-over-12 months boost changed into essentially because of increase across all three enterprise areas specifically consulting, utility administration and global technique functions.

Segmental revenues bearing on Strategic Imperatives grew 14%. Cloud practice surged 34%. Cloud as-a-carrier salary annual run rate become $2.1 billion.

application management revenues expanded four% from the year-in the past quarter. international system functions revenues climbed 5%. in addition, Consulting revenues multiplied 10% year over year, pushed through powerful efficiency from IBM’s digital business.

know-how services & Cloud platforms: Revenues Dip

Revenues from expertise capabilities & Cloud structures-exterior decreased 3% from the 12 months-in the past quarter (flat at cc) to $eight.9 billion. Segmental revenues touching on Strategic Imperatives advanced 13%, pushed via hybrid cloud features. Cloud surged 22% from the yr-in the past quarter. Cloud as-a-carrier salary annual run expense was $eight billion.

Integration application improved four% from the year-ago quarter. right through the suggested quarter, more than 100 corporations world wide selected IBM Cloud private offering. Infrastructure functions revenues had been flat on a yr-over-yr groundwork.

Technical guide features revenues diminished three% from the 12 months-ago quarter.

vigor & z14 drive programs Revenues

methods revenues diminished 21% on a 12 months-over-yr foundation (down 20% at cc) to $2.6 billion, essentially because of have an effect on of the IBM Z product cycle. Segmental revenues relating Strategic Imperatives plunged 22%, while Cloud revenues declined 31%.

IBM Z revenues decreased 44% year over yr. despite the fact, MIPS ability has increased around 20%, pushed by means of huge-based adoption of the z14 mainframe.

vigor revenues multiplied 10% from the 12 months-in the past quarter. The upside was principally because of Linux and robust adoption across the latest POWER9-primarily based structure.

during the fourth quarter, IBM completed the launch of its subsequent generation POWER9 processors for midrange and high-conclusion methods that are designed for dealing with superior analytics, cloud environments and information-intensive workloads in AI, HANA, and UNIX markets.

IBM additionally introduced new offerings optimizing both hardware and application for AI. management believes that products like PowerAI imaginative and prescient and PowerAI enterprise will assist drive new customer adoption.

besides the fact that children, storage hardware revenues declined as a result of vulnerable efficiency in the mid-range conclusion, partially offset by way of mighty growth in All Flash Arrays. IBM cited that pricing force within the immensely aggressive storage market is hurting revenues. The enterprise announced its new FlashSystems with next generation NVMe expertise all over the reported quarter.

working programs software revenues declined 3%, while techniques Hardware slumped 23% from the yr-ago quarter.

at last, global Financing (contains financing and used gadget income) revenues reduced 11% 12 months over year and 9% at cc to $402 million.

operating particulars

Non-GAAP gross margin remained unchanged from the 12 months-ago quarter at forty nine.5%. The gross margin benefited primarily by way of 190 basis elements (bps) growth in services margin. despite the fact, detrimental combine in IBM Z product cycle fully offset this enlargement.

operating expense declined 5.3% yr over 12 months, because of cognizance of acquisition synergies and enhancing operational efficiencies. IBM continues to invest in unexpectedly starting to be fields like hybrid cloud, synthetic intelligence (AI), protection and blockchain.

Pre-tax margin from carrying on with operations multiplied 50 bps on a 12 months-over-year foundation to 23.1%.

Cognitive options and global enterprise services section pre-tax margins increased 290 bps and 520 bps, respectively, on a year-over-yr foundation. despite the fact, expertise capabilities & Cloud systems segment pre-tax margin shriveled 20 bps.

Non-GAAP operating margins from carrying on with operations reduced in size ninety bps and came in at 20.3%.

steadiness Sheet & money circulate particulars

IBM ended fourth-quarter 2018 with $eleven.ninety nine billion in total cash and marketable securities in comparison with $14.70 billion on the end of third-quarter 2018. complete debt (together with present component) changed into $forty five.eight billion, down from $forty six.9 million from the outdated quarter.

IBM reported money move from operations (excluding world Financing receivables) of $7.3 billion and generated free cash stream of $6.5 billion in the quarter under evaluation.

within the mentioned quarter, the enterprise back $3.5 billion to shareholders via dividends and share repurchases. The enterprise back more than $10 billion to shareholders through dividends and share repurchases for the complete fiscal yr.

on the conclusion of the year, the company had $3.3 billion remaining beneath latest buyback authorization.

Fiscal 2018 Highlights

IBM said fiscal 2018 non-GAAP earnings of $13.eighty one per share, where as revenues came in at $79.6 billion, up 1% every year over yr.

Revenues from Cognitive solutions, international enterprise services, know-how features & Cloud platforms, systems and international Financing got here in at $18.forty eight billion, $16.eighty two billion, $34.forty six billion, $eight.03 billion and $1.fifty nine billion, respectively.


IBM expects non-GAAP EPS forecast for 2019 to be at least $13.ninety.

IBM still anticipates 2019 free money circulation of $12 billion.

How Have Estimates Been moving when you consider that Then?

It seems, sparkling estimates flatlined right through the past month.

VGM rankings

at the present, IBM has a subpar boom rating of D, however its Momentum ranking is doing lots better with a B. Charting a slightly an identical path, the inventory was allocated a grade of A on the price aspect, inserting it in the exact quintile for this funding method.

overall, the stock has an combination VGM ranking of B. in case you don't seem to be focused on one strategy, this score is the one be sure to be interested in.


IBM has a Zacks Rank #three (cling). We predict an in-line return from the stock within the next few months.

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Microsoft vs. IBM: what is the enhanced inventory buy? | killexams.com Real Questions and Pass4sure dumps

each Microsoft (NASDAQ:MSFT) and IBM (NYSE:IBM) have needed to shift their strategies in recent years to preserve providing boom for shareholders. however, despite slowing pc income and competitors from Apple, Microsoft has had a ways improved success than IBM in maintaining its business momentum going. Microsoft is customary for its dominance with its windows operating equipment and workplace application, however over the ultimate two years, it has emerged as probably the most largest cloud suppliers on earth.

IBM is investing heavily within the cloud, too, however it's struggling to keep up with quick-transforming into tech competitors, including Microsoft. Of course, the determination to purchase both of these stocks may still be based on more than simply who is growing faster within the cloud area. we will compare both organizations' fiscal positions, valuations, dividends, and most significantly, their competitive positions to check which is the superior buy today.

A man's hands typing on a laptop keyboard with white clouds hovering above the computer

image source: GETTY images.

financial fortitude

A assessment of an organization's monetary fitness tells buyers greater than in basic terms which business can hold up more desirable all the way through periods of softening in the financial system. a corporation with robust monetary fortitude has greater opportunities to convey returns to shareholders through constructing new items, making earnings-constructing acquisitions, or paying a rising dividend over time.

With that in intellect, here's a overview of how both organizations measure up on key monetary metrics: 

Metric Microsoft  IBM money $127.66 billion $12 billion Debt $73.17 billion $45.18 billion salary (TTM) $118.forty six billion $seventy nine.59 billion Free cash flow (TTM) $31.9 billion $11.fifty three billion Free cash circulation as a percentage of profits 26.9% 14.5%

records supply: YCharts. TTM = Trailing 12 months.

Microsoft is naturally the winner on this critical check. The application massive has about $54.5 billion of net cash, after subtracting debt, whereas IBM has extra debt than cash. 

Winner: Microsoft.

Valuation and dividends

a higher-buy assessment is never finished devoid of due to the fact that valuation. evaluating these two shares on quite a number universal metrics will help take care of against overpaying for an organization's profits. here's how shares of Microsoft and IBM stack up: 

Metric Microsoft IBM Trailing P/E 25.1 14.fifty one forward P/E 21.7 9.seventy four PEG ratio 1.seventy two 10.22 price-to-free money flow 26.four 10.97 Dividend yield 1.72% four.6% Dividend payout as a percentage of free money circulation 41.forty four% forty nine.14%

facts sources: YCharts and Yahoo! Finance.

at first glance, IBM looks just like the improved cost. however, keep in mind, analysts expect large Blue to develop profits by 1% per 12 months over the next 5 years, so the enterprise's low fee-to-revenue numerous may still include a warning label. even so, analysts are expecting Microsoft to develop revenue by means of 14% per yr going ahead -- that is why Microsoft has a lessen PEG (expense-to-profits-increase) ratio.

even so, any improvement in IBM's salary growth would probably trigger buyers to alter their expectations, which would send huge Blue's stock fee better. So, i'll provide IBM the benefit of the doubt.

taking a look at dividends, IBM seems just like the winner. It pays a juicy yield, which salary buyers should still find appealing. however once more, caution is warranted.

I lately made the argument that Microsoft is a stronger dividend boom inventory than IBM, and that i'm sticking to it. IBM's yield is tempting, but Microsoft has really grown its dividend at a sooner price than IBM in recent years. in the meantime, IBM hasn't grown its free cash circulation, and except that turns around, future dividend increases should be hard to come by using.

I give IBM the facet on valuation, but i'm sticking with my name that Microsoft is a much better dividend inventory. So, this one is a draw.

Winner: Tie.

competitive moat

Microsoft continues to bring strong consequences for shareholders stemming from its aggressive advantages, including community results, switching prices, and manufacturer. in the fiscal second quarter, income improved 12% year over year, pushed via 48% boom within the business cloud business. in the cloud enterprise, Azure grew 76% for the 2nd consecutive quarter as organizations continue partnering with Microsoft for his or her cloud-computing wants, including Kroger, Mastercard, and Walgreens Boots Alliance.

moreover, the software giant's shift to a subscription-based mostly mannequin for workplace continues to supply solid effects. Microsoft now has 33.3 million subscribers to office 365. revenue from productiveness and enterprise approaches (including workplace 365, Dynamics 365, and LinkedIn) grew 13% year over yr within the remaining quarter.

Microsoft has one of the precise manufacturers on the planet, which is because of the the familiarity thousands and thousands of people and corporations have with home windows and workplace application. The company is beginning to leverage that technological expertise and brand awareness in other pleasing areas, together with internet of things, artificial intelligence, and combined truth, besides cloud-computing. 

On the different side, IBM has been serving company shoppers for years. massive Blue has huge competencies in consulting organizations throughout many industries to aid them compete more simply. 

IBM's main difficulty is finding boom. while IBM isn't going anywhere, it's additionally now not more likely to grow lots within the next few years. About half of IBM's enterprise is caught in sluggish-starting to be markets like legacy IT features, hardware, and utility features. 

youngsters, as that you can see with Microsoft's contemporary boom, cloud spending is where all the motion is. IT spending is present process a massive to shift to the cloud, which would not play to IBM's strengths. while IBM noticed its cloud enterprise develop 12% ultimate 12 months, that's peanuts compared to Microsoft's increase within the cloud. IBM's cloud market share is ready 2%, while Microsoft noticed its share bounce from 8.7% in 2016 to 13.3% in 2017. 

Amazon.com and Microsoft are absorbing many of the cloud spending right now. IBM's contemporary acquisition of red Hat will assist, but normal, Microsoft is in a tons enhanced aggressive position.  

Winner: Microsoft.

Microsoft is the better purchase

IBM could be a fine contrarian guess, mainly if the enterprise begins to reveal signs of growth once more. but for now, i would fairly go with consistency. Microsoft has the financial fortitude, increase, and competitive advantages that make the king of utility a no brainer decide on.

John Mackey, CEO of total foods Market, an Amazon subsidiary, is a member of The Motley idiot's board of directors. Teresa Kersten, an employee of LinkedIn, a Microsoft subsidiary, is a member of The Motley fool's board of directors. John Ballard owns shares of Amazon and Mastercard. The Motley idiot owns shares of and recommends Amazon, Apple, and Mastercard. The Motley fool owns shares of Microsoft. The Motley idiot is short shares of IBM and has right here alternate options: long January 2020 $a hundred and fifty calls on Apple and short January 2020 $a hundred and fifty five calls on Apple. The Motley idiot has a disclosure policy.

Microsoft Vs. IBM: One Clear Winner | killexams.com Real Questions and Pass4sure dumps

No influence discovered, try new key phrase!it is especially true if a corporation overpays and IBM is paying a 63% premium for RHT. 10 and 30 instances income and free money movement is a rich expense to pay that skill IBM has little margin of error when ...

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IBM Certification Guide: Overview and Career Paths | killexams.com real questions and Pass4sure dumps

The International Business Machines Corporation, better known simply as IBM, is a world leader in IT products and services. It covers IT comprehensively, encompassing enterprise applications, middleware and operating systems, computing systems, storage, cloud computing, and business analytics.

IBM became known as Big Blue, most likely because of the color of its mainframes in the late 1960s. Some of IBM's best-known product brands include B2, Lotus, Tivoli and WebSphere. Today, the company is making its name known with Watson, IBM's cognitive technology.

IBM certification program overview

A company as large, widely followed and revered as IBM is bound to have a well-developed certification program, and indeed it does. The IBM Professional Certification Program boasts almost 300 credentials.

In the past, IBM classified its certifications according to software, hardware, IBM PureSystems, solutions and "other." While individual certifications may still fall into those general categories, certification classifications have been revamped to more closely align with the company's product portfolio. IBM currently classifies its certifications across 11 main categories:

  • Analytics
  • Cloud
  • Cognitive Solutions
  • Commerce
  • Global Financing
  • Global Technology Services
  • Security
  • Systems
  • Watson
  • Watson Health
  • Watson Internet of Things
  • Certifications are aimed at IT professionals who implement, support or sell IBM products at the Associate, Professional and Advanced Professional (including Expert) tiers. Most certifications can be achieved by passing one or two exams focused on a specific IBM application, system or service, although some expert-level certs require up to five exams.

    IBM exams and retake policy

    IBM certification exams are delivered through Pearson VUE testing centers. An exam may last 60 to 150 minutes, include anywhere from 22 to 97 questions, and cost $100 to $200. Exam details vary greatly across certifications, so we provide only high/low information here, and exam prices may change as of the first day of any calendar year. Exam prices also vary by geography, so candidates need to check prices for their localities.

    A candidate who fails an exam the first time may retake it as soon as possible but must wait 30 days before making subsequent attempts. To help defray costs, IBM occasionally offers a Take It Again promotion in which candidates can retake an exam for free if they fail the first attempt. IBM has also been known to offer exams for free at events such as InterConnect 2017. Seating is frequently limited, so interested professionals should check out event offerings and register early.

    IBM makes navigating certification easy with webpages dedicated to its certification process, along with one-stop shopping for test information (exam name and number, associated certification, number of questions, exam length, passing score requirements, plus links to the individual exam page) and easy-to-find exam pricing.

    The following sections provide a high-level view of IBM certifications in each of the main categories.

    IBM Analytics

    Featuring more than 100 certifications, IBM Analytics is IBM's largest certification category, reflecting the growing industry use of analytics and IBM's leadership in this area. Analytics certifications are designed for professionals working with IBM solutions for performance management and business intelligence.

    IBM offers Analytics certifications in four areas: Cloud Content Services, Cognos Analytics, Collaboration Solutions and Social Business, and Platform Analytics. While there is some overlap among products, each concentration area features credentials in different portions of the IBM Analytics product portfolio:

  • Analytics Cloud Content Services: Includes credentials for Content Manager onDemand, Datacap (Datacap Taskmaster Capture), Enterprise Records, FileNet (Business Process Manager and Content Manager), Case Manager, Content Collector, Content Navigator and Case Foundation
  • Cognos Analytics: Focused entirely on Cognos-related credentials, including Cognos TM1, Cognos TM1 Data Analysis, Risk Information Governance for BI, Cognos BI, BI Reports and Multidimensional Reports, BI Data Warehouse, BI Metadata Models, BI OLAP Models, BI Scorecards, and BI Controller
  • Analytic Platform: Includes credentials for DB2, Cognos, PureData System, Informix, SPSS, InfoSphere, Big Data and Apache Spark
  • IBM Collaboration Solutions and Social Business: Credentials focus on social business solutions such as Lotus Notes and Domino, Connections and Connections Cloud, Sametime, Social Business, OpenSocial, and SmartCloud Notes Hybrid
  • IBM offers Analytics credentials from entry level to expert.

    IBM Cloud

    Formerly IBM Cloud and Mobility, the IBM Cloud certification portfolio has grown exponentially and now offers more than 70 certifications, making it IBM's second largest certification portfolio. IBM Cloud credentials focus on six primary areas:

  • Cloud Integration – Application Platform: Includes credentials for Business Process Manager, WebSphere Application Server, Worklight Foundation, PureApplication System and WebSphere Application Server Network Deployment products
  • Cloud Integration – Dev Ops: Credentials focus on Rational, SmartCloud, Tivoli, Service Management, Control Desk and Workload Automation products
  • Cloud Integration – Hybrid Integration: Provides credentials for IBM Service Management Asset Management, CICS Transaction Server, API Management, MQ, Integration Bus, WebSphere, DataPower Gateway, API Connect and WebSphere DataPower SOA Appliances Firmware
  • Cloud Integration – Process Transformation: Includes credentials for WebSphere Business Modeler, Business Process Manager, Blueworks Live, Operational Decision Manager, and IBM BPM using Process Designer product families
  • Cloud Platform: Credentials in this category target Cloud Platform and SoftLayer.
  • Cloud Solutions: Includes credentials for Cloud Reference Architecture and Cloud Platform Solution
  • This portfolio features credentials for developers, administrators and solution architects.

    IBM Cognitive Solutions

    IBM Cognitive Solutions certifications focus mainly on the Cognos, OpenPages and Algo One products. Where Cognos is geared toward business intelligence, analytics and financial strategy management, OpenPages facilitates governance, risk and compliance management. Algo One is a tool used for analyzing risk factors and models. IBM's Cognitive Solutions certifications are available at the administrator, associate and advanced developer, solution designer, and specialist levels.

    IBM Commerce

    IBM Commerce certifications are all about the customer, and how professionals working with IBM technology can help the customer conduct and grow its business. Commerce certs come in three flavors: engaging the customer, partner and supplier relationships, and digital commerce. These certs cover a wide swath of credential roles, including business analysts, solution designers, system administrators, application developers, and deployment and implementation professionals.

    The Customer Engagement category features credentials that focus on maximizing the customer product experience for WebSphere Commerce, Digital Analytics, Tealeaf, Marketing Operations, Sterling (Configuration, Order Management), Campaign and Interact.

    Partner and Supplier Engagement certifications focus on professionals managing partner and supplier relationships. Products featured include Sterling Connect Direct, WebSphere Transformation Extender, Emptoris Contract Management and Sterling B2B Integrator.

    Digital Experience credentials target professionals charged with enhancing the customer's digital experience and focus on WebSphere Portal, Web Content Manager, Digital Experience, Forms, Forms Experience Builder and Web Experience Factory.

    IBM Global Financing

    IBM offers a single Global Financing credential, the IBM Global Financing Sales Master Specialist Professional certification. A single exam is required to earn the credential.

    IBM Global Technology Services

    IBM Global Technology Services is promoted as the IBM group that builds and manages "the backbone that powers the era of enterprise hybrid IT." Simply put, GTS is all about services (both outsourced and managed services) for Watson, hardware, software and general technical support.

    IBM offers a single cert in this category: the IBM Certified Specialist – IBM U.S. Technical Support Services V2. This certification is only available in the U.S. and is geared toward business partners who provide Level 1 or 2 technical support. Candidates must pass a single exam to earn the credential.

    IBM Security

    In today's cognitive era, IT infrastructure security is essential to ensuing IT services are not only predictable but compliant and secure as well. An individual with an IBM Security certification has proven skills in designing, implementing, configuring, testing and/or supporting specific IBM security products. Many IBM Security certifications target professionals who process and analyze specialized data geared toward law enforcement, government agencies and municipalities (utility-related).

    IBM security products include IBM Security Guardium, Security QRadar, i2 Analysts Notebook, Security SiteProtector, Endpoint Manager, MobileFirst Protect and many others. The IBM Security certification portfolio offers IT professionals 32 different options to hone and validate their security skills.

    Depending on the certification, available credentials include administrator and associate administrator, analyst and associate analyst, associate, deployment professional, integration professional, solution advisor, security intelligence, and specialist. Deployment professional certs make up approximately one-third of the available security credentials (11 total).

    IBM Systems

    IBM currently offers 29 different IBM Systems certifications aimed at users, advanced users, implementers and sellers. IBM Systems certs fall into five categories:

  • Power Systems: IBM offers five Power Systems certs. The three Sales credentials include certified sales specialist and technical sales specialist for professionals working with solutions for Power Systems with POWER8. Two certified system administrator credentials focus on either AIX or IBM i. Candidates for any of the IBM certified system administrator certifications should have two or more years of experience working with Power Systems server running AIX 7 or IBM i 7.1/7.2, and are required to pass a single exam.
  • Storage Software: There are nine different Storage Software certs, six of them targeting Spectrum products (Storage Management, Cloud, Protect, Scale, Computing and Storage Family Solutions). The three remaining certs focus on Tivoli Storage Manager and Cloud Object Storage. Candidates may earn administrator, deployment professional or solution advisor credentials.
  • Storage Systems: There are nine certified specialist credentials in this category, with solutions targeting midrange and enterprise storage systems, as well as flash technical solutions, XIV storage systems and high-end tape technical solutions.
  • z Systems: IBM offers four certified specialist credentials for z Systems. Two are focused on sales, while two target technical support for z Systems.
  • Other: This category encompasses certs for systems that don't readily meet the criteria for the other areas. There are two credentials in this category: Certified Database Administrator – IMS and Certified System Programmer – IMS.
  • IBM Watson

    You may remember the now-famous bout where IBM's Watson supercomputer won the "Jeopardy" game show challenge, ushering in a new era in cognitive computing, big data and analytics. Since that time, IBM kick-started the IBM Watson Group with a healthy $1 billion in startup funding. Today, IBM Watson is rapidly becoming an industry leader for technology platforms that leverage the power of natural language and machine learning.

    Eighteen IBM Watson certs are available. Seven certifications focus on Maximo Asset Management solutions, while the remaining certs are divided between TRIRIGA, Collaborative Lifecycle Management, Rhapsody, Predictive Maintenance and Quality, and Rational. Available credentials include associate, consultant, solutions (specialist, expert and advisor), deployment (infrastructure and advanced) and application developer.

    IBM Watson Health

    A brainchild of The Watson Group, Watson Health is one of the newest rising stars at IBM. Watson Health boasts numerous partnerships with healthcare industry leaders.

    There are currently two Watson Health certs available: IBM Certified Application Developer – Curam V604 and IBM Certified Associate Business Process Analyst – Curam V605. The Certified Application Developer – Curam is an intermediate credential that targets Java professionals who also work as Curam developers. The Associate Business Process Analyst – Curam is an entry-level credential for testers, business analysts or consultants seeking to establish foundation-level Curam skills or implement Curam projects. A single test is required for each certification. Note: IBM Business Partner candidates who've purchased a Value Package qualify for IBM's You Pass, We Pay (YPWP) Program. Under the YPWP program, candidates are reimbursed for exams and some preparatory courses.

    IBM Watson: Internet of Things

    The internet of things, or IoT, is certainly changing the way we connect, interact and conduct business. The IBM Watson: Internet of Things portfolio is a new addition to the IBM family. Like IBM Watson certs, the IBM IoT certs focus primarily on Maximo Asset Management, Rational and TRIRIGA products. Credentials include specialists, associates, deployment professionals and more.

    Related jobs, careers and training resources

    You'll find IBM-certified professionals employed in a variety of job roles that span all industry sectors. A simple job search for "IBM professionals" on Simply Hired turned up more than 40,000 job postings. For example, we found these postings:

  • A major telecom company looking for a senior data scientist experienced in building predictive modeling tools, including IBM SPSS
  • A company in Illinois seeking a certified WebSphere system administrator
  • An Arizona-based solution team with an opening for an experienced IBM sales and marketing account executive
  • A New Jersey healthcare company seeking a systems analyst
  • Other common job roles included developers, business analysts, technical solution engineers, platform support engineers and integration leads. Career choices are limited only by your personal interests and aspirations.

    IBM maintains a list of training resources for each exam on the individual exam webpage. Here, candidates will find test objectives, sample exams and assessment tests, as well as links to more formal training and other resources. Additional training materials, including books and e-books, may be purchased from the IBM Professional Certification Marketplace. On the IBM Training and Skills webpage, candidates will find links to blogs, articles, learning opportunities, events, Redbooks and PartnerWorld.

    Software automates Java GUI testing. | killexams.com real questions and Pass4sure dumps

    Press Release Summary:

    Based on WindowTester technology, WindowTester(TM) Pro v2.0 Eclipse-based software development tool streamlines testing of Java client applications, facilitating creation of consistent and reliable user interfaces. Supporting automated GUI testing for both Swing and SWT frameworks, software is compatible with Microsoft Windows and Linux (GTK) and installs into any Eclipse-based development environment and automated build systems like Ant, Cruise Control, or Maven.

    Original Press Release: Instantiations WindowTester Pro Automates Java GUI Testing

    Eclipse-based tool virtually eliminates hand-coding GUI tests for popular Java Swing and SWT frameworks

    SANTA CLARA, Calif., March 6 / -- EclipseCon 2007 -- Instantiations, Inc., a leading provider of software quality and productivity solutions, today announced the release of WindowTester(TM) Pro 2.0. An Eclipse-based software development product, the new product streamlines the testing of Java client applications making it easier to create richer, more consistent and reliable user interfaces. The new product is based on the market-proven WindowTester technology contained in Instantiations' RCP Developer.

    As software development cycles shrink from months to weeks, automated, reliable GUI testing becomes increasingly necessary to meet customer expectations and software quality goals. Manual GUI testing is time-consuming, labor-intensive and expensive and is usually left until the end of the development process. Manual testing depends on individuals following a set of complex directions, making the results inconsistent and often unrepeatable. Finding software "bugs" late in the development cycle is no longer a choice. It delays product rollout and increases the cost of enterprise and shrink- wrapped software products.

    "Since we started using WindowTester, tests that took 2-3 weeks to write previously can now be done in 2-3 days," said Steve Tocco, director of quality assurance Workshop unit at BEA Systems.

    "Developers resist GUI testing because it's complex, time-consuming and diffuses their focus on product development," said Dan Rubel, chief technology officer, Instantiations, Inc. "WindowTester reduces both the testing complexity and time needed. And it frees them to build quality applications because it automates recording, test generation, code coverage and playback of GUI to application interactions rather than requiring time-consuming, hand- crafted and high-maintenance test code."

    "In terms of our investment in the WindowTester tool, we believe the cost of the licensing is greatly worth the enhancement and efficiency gained so far," said Bill Roth, vice president Workshop unit, BEA Systems.

    The WindowTester approach is based on the JUnit standard so it takes advantage of the native Eclipse test framework. By offering greater flexibility in test development, maintenance and access to Java code, WindowTester is superior to existing alternatives, such as Abbot or the Eclipse Test and Performance Tools Platform (TPTP) that only support a single Java platform. WindowTester Pro supports Microsoft Windows, Linux (GTK) and installs easily into any Eclipse-based development environment. It's equally easy to integrate with automated build systems like Ant, Cruise Control or Maven.

    "WindowTester Pro operates similarly to the window testing function in RCP Developer that our customers are familiar with," said Rubel. "However, WindowTester Pro supports automated GUI testing for both popular Java GUI frameworks, Swing and SWT, and promises to be a more complete Eclipse GUI testing environment for enterprises."

    Price and Availability

    WindowTester Pro 2.0 is available immediately and in several configurations to meet different customer needs. For users who prefer more flexibility or a lower initial investment, the company offers a per developer subscription price of $319 (USD) a year for the WindowTester Tools Library(TM). The yearly subscription provides access to all the product tools available in the library -- including WindowTester Pro, WindowTester SWT and WindowTester Swing -- as well as upgrades and technical support.

    For users who prefer a standard software license agreement, Instantiations offers WindowTester Pro separately for $799 (USD) per seat license. WindowTester SWT and WindowTester Swing are each available separately for a $499 (USD) per seat license. Annual support for these products costs 25 percent of the first year's price.

    For additional information or pricing on this product, please contact our sales department at (800) 808-3737 or by email at sales@instantiations.com. The products and free 14-day evaluations may be downloaded immediately from the company's web site at http://instantiations.com/windowtester/.

    About Instantiations

    Instantiations, Inc. provides leading-edge software products, services and technologies for Eclipse, Java and Smalltalk. The company offers high-value, high-ROI professional development environments and engineering consulting services that focus on improving software quality and developer productivity. Instantiations is a member of the Eclipse Foundation and offers a line of products for Eclipse, IBM Rational and WebSphere Studio, and MyEclipse. Based in Portland, Ore., Instantiations was founded in 1997 by a team of internationally recognized pioneers in component software technology. For more information, visit www.instantiations.com/. Or call the company at (800) 808-3737.

    Source: Instantiations, Inc.

    CONTACT: Mark Johnson of Instantiations, Inc., +1-503-598-4909, mark_johnson@instantiations.com;

    Web site: http://www.instantiations.com/

    Related Thomas Industry Update Thomas For Industry

    Drug repurposing: progress, challenges and recommendations | killexams.com real questions and Pass4sure dumps

    Typically, a drug repurposing strategy consists of three steps before taking the candidate drug further through the development pipeline: identification of a candidate molecule for a given indication (hypothesis generation); mechanistic assessment of the drug effect in preclinical models; and evaluation of efficacy in phase II clinical trials (assuming there is sufficient safety data from phase I studies undertaken as part of the original indication). Of these three steps, step 1 — the identification of the right drug for an indication of interest with a high level of confidence — is critical, and this is where modern approaches for hypothesis generation could be most useful. These systematic approaches can be subdivided into computational approaches and experimental approaches (Fig. 1), both of which are increasingly being used synergistically. Drug repurposing based on clinical data is encompassed within these two broad areas.

    Figure 1: Approaches used in drug repurposing. Figure 1

    Various computational approaches can be used individually or in combination to systematically analyse different types of large-scale data to obtain meaningful interpretations for repurposing hypotheses. Challenges for such analyses are discussed in Box 5. Experimental approaches can also be used to identify repurposing opportunities. EHR, electronic health record.

    Computational approaches

    Computational approaches are largely data-driven; they involve systematic analysis of data of any type (such as gene expression, chemical structure, genotype or proteomic data or electronic health records (EHRs)), which can then lead to the formulation of repurposing hypotheses11 (Fig. 1). The most commonly used computational approaches, together with drug repurposing examples, are discussed below.

    Signature matching. Signature matching is based on the comparison of the unique characteristics or 'signature' of a drug against that of another drug, disease or clinical phenotype12,13. The signature of a drug could be derived from three general types of data: transcriptomic (RNA), proteomic or metabolomic data; chemical structures; or adverse event profiles, which we discuss in turn below.

    Matching transcriptomic signatures can be used to make drug–disease comparisons (estimating drug–disease similarity)14 and drug–drug comparisons (drug–drug similarity)15. In the first case, the transcriptomic signature of a particular drug is derived by comparing the gene expression profile of biological material, such as a cell or a tissue, before and after treatment with the drug; the resultant differential gene expression signature (the molecular signature of the drug) is then compared with a disease-associated expression profile that has been similarly obtained through differential expression analysis of disease versus healthy conditions. The extent of negative correlation between the gene expression signature of the drug and that of the disease (that is, the genes upregulated in the disease are downregulated with the drug and vice versa) would then allow inference of whether the drug may have a potential effect on the disease16,17 (see the case study of topiramate in Box 2). This computational approach relies on the signature reversion principle (SRP), where it is assumed that if a drug can reverse the expression pattern of a given set of genes that are a hallmark for a particular disease phenotype (that is, the drug signature will be closer to that obtained for the healthy state), then that drug might be able to revert the disease phenotype itself. Despite this principle being quite simplistic, it has been demonstrated for metabolic disorders18 and successfully exploited to identify novel drug repositioning opportunities in a wide range of therapeutic areas19,20,21,22,23,24. The SRP has also been successfully employed to identify drugs that could be repositioned as chemo-sensitizers based on anticancer drug-resistance signatures25.

    Box 2: Drug–disease similarity approach to identify topiramate in IBD

    Dudley and colleagues16 compared the gene expression signature of inflammatory bowel disease (IBD) derived from publicly available data obtained from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus with the gene expression profile of 164 drugs obtained from the Connectivity Map (cMap). Therapeutic predictions for drug–disease pairs were derived based on the extent of negative correlation between the gene expression signature of the drug and that of the disease. One of the strongest therapeutic predictions they obtained for IBD was the corticosteroid prednisolone, which is widely used to reduce inflammation associated with IBD. Another drug that showed a stronger correlation with both Crohn's disease and ulcerative colitis — two important clinical manifestations of IBD — was topiramate, an antiepileptic drug with GABA agonistic activity.

    The authors validated the potential efficacy of topiramate in IBD using a trinitrobenzenesulfonic acid-induced rat model of IBD, in which it significantly reduced diarrhoea, visual manifestations of colitis on endoscopy and microscopic manifestations of disease on colonic biopsy. Functional enrichment analysis indicated that genes involved with gastrointestinal disease, inflammatory response and other immune-related functions were divergently expressed between the drug-affected and disease-affected conditions, further highlighting some of the potential mechanisms by which topiramate may act in IBD. However, a recent retrospective cohort study using administrative claims data from the MarketScan databases in the US failed to show a beneficial effect of topiramate in IBD110. Nevertheless, it is interesting to note that GABA has been recently suggested to play a potential role in gastrointestinal inflammation111. Thus, an appropriately designed and powered randomized clinical trial would be required to definitively answer the question of whether topiramate can be used therapeutically in IBD.

    Drug–drug similarity approaches aim to identify shared mechanisms of action of otherwise dissimilar drugs (drugs that belong to different classes or that are structurally dissimilar). This principle is called guilt by association26 and can aid the identification of alternative targets of existing drugs and uncover potential off-target effects that can be investigated for clinical applications12. A shared transcriptomic signature between two drugs could therefore imply that they also share a therapeutic application, regardless of the similarity or dissimilarity in their chemical structures27 (see the case study of fasudil in Box 3). This principle has proved effective even when comparing transcriptional signatures that are reflective of a secondary mode of action, which could be shared, for example, by a group of pharmacologically diverse mild correctors of a given disease phenotype28,29.

    Box 3: Drug–drug similarity approach to identify the potential use of fasudil in amyotrophic lateral sclerosis

    Iorio and colleagues27,112 used the 'guilt by association' principle to construct a drug network using publicly available transcriptomic profiles of drugs, which allowed them to identify drugs with a similar transcriptional signature and therefore a perceived similar mechanism of action. Using gene expression profiles of each drug across multiple treatments on different cell lines and/or at different dosages obtained from the Connectivity Map (cMap), they computed a representative transcriptional response for each drug. A drug network was then constructed in which two drugs were connected to each other if their optimal transcriptional responses were similar according to a similarity measure developed by the authors (called drug distance). This resulted in a drug network of 1,302 nodes (drugs) and 41,047 edges (indicating similarities between pairs of drugs) purely based on transcriptomic profiles of drugs within this network consisting of drugs with a similar transcriptional signature and therefore a perceived similar mechanism of action.

    Using this network, the authors correctly predicted the previously known mechanism of action of nine anticancer compounds, thereby validating this predictive model. Importantly, they also predicted previously unknown mechanisms for drugs such as fasudil, a Rho-kinase (ROCK) inhibitor, based on its proximity to known autophagy enhancers such as 2-deoxy-d-glucose and tamoxifen, and validated their prediction using an in vitro fibroblast model112. Autophagy plays a key role in the pathogenesis of amyotrophic lateral sclerosis (ALS)113, a neurodegenerative disease with no cure. Preclinical studies in animal models of ALS showed that fasudil can increase motor neuron survival in transgenic mice expressing mutant superoxide dismutase 1 (SOD1), the causal gene for congenital forms of ALS114. The beneficial effects of fasudil in preclinical models of ALS were also confirmed in other preclinical studies115,116. This has now led to an open-label, single-centre clinical trial in China to investigate the efficacy and safety of fasudil in ALS (NCT01935518).

    Both drug–disease and drug–drug similarity approaches involve matching of transcriptomic signatures and therefore rely heavily on publicly accessible gene expression data. The Connectivity Map (cMap), which was established in 2006 by the Broad Institute, consists of gene expression profiles generated by dosing of more than 1,300 compounds in a number of cell lines30 (Connectivity Map; see Related links). cMap information can be considered as a proxy phenotypic screen for a large number of compounds and has been successfully used to make drug repurposing predictions for a number of disease conditions. The third instalment of the cMap data repository (cMap 3.0) is now available within the US National Institutes of Health (NIH) Library of Integrated Network-based Cellular Signatures (LINCS; see Related links). It encompasses transcriptional signatures generated with tens of thousands of compounds upon treatment of hundreds of human cell lines. This enormous resource can be used along with other important public repositories of transcriptomic data, such as the Gene Expression Omnibus (see Related links) and Array Express (see Related links), which contain raw gene expression data from hundreds of disease conditions in humans and animal models. Manual curation or dedicated computational tools31 can then be used to interrogate these disease signatures in association with the cMap data to identify novel drug–disease connections and potential drug repositioning opportunities32,33.

    The second type of signature matching used in drug repurposing is based on chemical structures and their relationship to biological activity34; comparing the chemical signature of one drug with that of another drug to see whether there are chemical similarities could suggest shared biological activity. The process involves selecting a set of chemical features for each drug and then constructing networks based on the shared chemical features. This is exemplified by the statistics-based cheminformatics approach undertaken by Keiser and colleagues12 to predict new targets for 878 US Food and Drug Administration (FDA)-approved small-molecule drugs and 2,787 pharmaceutical compounds. Using a similarity ensemble approach (SEA) to evaluate the 2D structural similarity of each drug to each target's ligand set, they were able to identify 23 new drug–target associations.

    Chemical similarity approaches have their pitfalls: errors in chemical structures as well as physiological effects that exist beyond the structural relationship (for example, a metabolite of the original drug with a modified structure could be the active molecule) could limit the use of this approach in drug repurposing14.

    Finally, every drug has a relatively unique adverse effect profile that could be used as a proxy for its phenotype. Matching the adverse effect signature of drugs is based on the hypothesis that two drugs that cause the same adverse effects may be acting on a shared target or protein or on the same pathway14. It is also possible that the adverse effect phenotype of a particular drug may resemble that of a disease; this would suggest shared pathways and physiology by both the drug and the disease. Peer Bork's group used the adverse effect similarity approach to identify novel drug–target relationships for 746 approved drugs35. They used the Unified Medical Language System (UMLS) ontology for medical symptoms and extracted relevant adverse effect profiles from drug package inserts, weighted them based on frequency and scored these drugs based on adverse effect similarities. This approach not only confirmed previously known drug–drug pairs that shared the same protein target but also identified new shared targets for 754 drug pairs. A different approach was used by Yang and Agrawal to match adverse drug effects with disease36; they combined adverse effect information derived from drug labels with drug–disease relationships obtained from the PharmGKB database and were able to predict repurposing indications for 145 diseases.

    Although this is a logical approach to use for identifying repurposing opportunities, the difficulty in mining adverse effect information from drug package inserts and the lack of well-defined adverse effect profiles and causality assessments for a number of drugs14 could limit its use. However, artificial intelligence technologies that can undertake text mining and natural language processing represent potential future opportunities to overcome these limitations.

    Computational molecular docking. Molecular docking is a structure-based computational strategy to predict binding site complementarity between the ligand (for example, a drug) and the target (for example, a receptor)37. If there is prior knowledge of a receptor target involved in a disease, then multiple drugs could be interrogated against that particular target (conventional docking: one target and multiple ligands). Conversely, drug libraries could be explored against an array of target receptors (inverse docking: several targets and one ligand) to identify novel interactions that can be taken forward for repurposing. Using high-throughput computational docking, Dakshanamurthy and colleagues38 performed molecular fit computations on 3,671 FDA-approved drugs across 2,335 human protein crystal structures. They discovered that mebendazole, an anti-parasitic drug, has the structural potential to inhibit vascular endothelial growth factor receptor 2 (VEGFR2), a mediator of angiogenesis; this was also confirmed experimentally.

    However, there are several issues with the use of molecular docking for drug repurposing. First, 3D structures for some protein targets of interest may not be available, particularly because drug targets are often membrane proteins, such as G protein-coupled receptors (GPCRs), although substantial progress has recently been made in GPCR crystallography39. Second, there is a lack of well-curated macromolecular target databases that provide accurate structural information40, although this is getting better41. Finally, the utility of docking algorithms to predict the affinity of binding has been questioned42 and, while it is improving, there can be differences between different software packages, and some limitations in predictability (for instance, mode of binding and entropic effects) still remain43.

    Genome-wide association studies. There has been a large increase in the number of genome-wide association studies (GWAS) conducted over the past 10 years following advances made in genotyping technology, the completion of the Human Genome Project and dwindling genotyping costs. GWAS aim to identify genetic variants associated with common diseases and thereby provide insights into the biology of diseases; the data obtained may also help identify novel targets, some of which could be shared between diseases treated by drugs and disease phenotypes studied by GWAS and thereby lead to repositioning of drugs44. Sanseau and colleagues44 refined the catalogue of published GWAS traits from the US National Human Genome Research Institute (NHGRI) and found that genes that were associated with a disease trait were more likely to code for proteins that are 'druggable' or 'biopharmable' than the rest of the genome, with the GWAS gene set enriched by 2.7-fold in targets being pursued by the pharmaceutical industry. They also found 92 individual genes with a GWAS trait that was different from the original drug indication, suggesting that it is possible to evaluate drugs that target the products of these 92 genes for a new disease indication (see the case study for denosumab in Box 4). Another recent study by Grover and colleagues45 used a bioinformatics approach to match gene targets identified for coronary artery disease with drug information obtained by integration of three different drug–target databases (DrugBank, Therapeutic Target Database and PharmGKB) to identify potential repositioning opportunities.

    Box 4: Use of GWAS-identified targets for potential repurposing of denosumab in Crohn's disease

    Denosumab (Prolia, Amgen), which is marketed for the treatment of postmenopausal women at high risk of fracture with osteoporosis, is an antibody that targets tumour necrosis factor ligand superfamily member 11 (TNFSF11), also known as RANKL. TNFSF11 has also been shown to be activated in Crohn's disease, in which a substantial proportion of patients have osteopenia and osteoporosis117. Moreover, a TNFSF11 genetic variant (rs2062305) has also been associated with Crohn's disease by genome-wide association studies (GWAS)118.

    This prompted Sanseau and colleagues44 to speculate about a potential role for denosumab in Crohn's disease. Using human B-lymphoblastoid cells and osteoblasts, they found that the Crohn's disease-associated TNFSF11 variant was associated with the differential expression of TNFSF11 and was able to explain population variation in TNFSF11 expression in both cell types representing distinct cellular lineages relevant for both inflammatory and bone disease. This provided further support to postulate a causal link between TNFSF11 and Crohn's disease and the potential for repurposing denosumab in Crohn's disease. A recent preclinical study explored the efficacy of daily denosumab injection in a mouse model of colitis induced by dinitrobenzenesulfonic acid119. Denosumab was found to decrease pro-inflammatory cytokines and modify the gut microbiota diversity in this animal model, further supporting its potential use in treating manifestations of inflammatory bowel disease. The same investigators are currently conducting an open-label phase I/II trial of denosumab in patients with active Crohn's disease (NCT02321280). The study is due for completion in July 2019.

    However, there are challenges in the use of GWAS information for drug repositioning, and its utility at present is unclear. GWAS signals in gene-rich loci with strong linkage disequilibrium may make identification of causal gene and/or gene variants difficult44. Another issue is the lack of information on the direction of effect of the gene variant; functional studies will need to be conducted to ascertain this before deciding whether an activator or a suppressor is required to control the disease44. GWAS data do not provide detailed pathophysiological information, and hence, rational use of GWAS data is advocated before predicting repurposing targets46. It should also be noted that the current understanding of the human genome is not final and there may be many more new genes discovered47.

    Pathway or network mapping. Pathway-based or network-based approaches have been widely used to identify drugs or drug targets that may have potential in repurposing48. As discussed above, even though some of the potential targets found by GWAS or other means may make themselves directly amenable as drug targets, quite often, these genes may not be ideal druggable targets. In such circumstances, a pathway-based strategy may provide information on genes that are either upstream or downstream of the GWAS-associated target and could be exploited for repurposing opportunities49. Network analysis involves constructing drug or disease networks based on gene expression patterns, disease pathology, protein interactions or GWAS data in order to aid identification of repurposing candidates. Some of the signature matching studies discussed earlier also make use of the network analysis approach27,50. A recent study by Greene and colleagues51 combined genetic variant information arising from GWAS with tissue-specific functional interaction networks using a technique termed network-wide association study (NetWAS) to identify disease–gene associations much more accurately than GWAS alone. By applying this strategy to hypertension and by querying the resultant data against drug–target data from DrugBank, they observed that targets of antihypertensive drugs were enriched to a greater extent among the top genes from NetWAS than with GWAS. Pathway analysis of gene expression data sets from studies involving a wide range of respiratory viruses in human host infection models identified 67 common biological pathways that may be important in respiratory viral infections48. Interrogation of these pathways against the DrugBank database identified several drugs with a potential effect against host-viral targets. These included pranlukast, a leukotriene receptor 1 antagonist used in asthma, and amrinone, a phosphodiesterase inhibitor used in the treatment of congestive heart failure. It has been postulated that both of these drugs could be useful in treating viral infections owing to their potential ability to alter the immune response.

    Retrospective clinical analysis: use of electronic health records. The best example of retrospective clinical analysis leading to repurposing (or rescue if the drug had otherwise failed for its primary indication) of a candidate molecule is sildenafil1. Other examples for repurposing opportunities arising from retrospective clinical and/or pharmacological analyses include aspirin in colorectal cancer (the US Preventive Services Task Force released draft recommendations in September 2015 regarding the use of aspirin to help prevent cardiovascular disease and colorectal cancer52), raloxifene in breast cancer (Evista; approved by the FDA to reduce the risk of hormone-receptor-positive breast cancer in postmenopausal women who have not been diagnosed but are at higher-than-average risk of disease) and propranolol in osteoporosis53. However, the above cited examples did not arise as a result of a systematic analysis of clinical data. A systematic approach for analysing clinical data is now increasingly suggested for identifying drug repurposing opportunities54.

    Retrospective clinical data can be obtained from various sources, including EHRs, post-marketing surveillance data and clinical trial data. EHRs contain an enormous amount of data on patient outcomes, both structured and unstructured. The diagnostic and pathophysiological data, including the results of laboratory tests as well as drug prescribing data, are more structured; however, EHRs also contain considerable amounts of unstructured information, such as clinical descriptions of patient symptoms and signs (which are important in defining disease phenotype) and imaging data. This wealth of data present in EHRs could be used as a source for identifying signals for drug repurposing11; in addition, the enormous amount of EHR data also provides high statistical power55. Paik and colleagues55 extracted clinical signatures from over 13 years of EHRs from a tertiary hospital, including >9.4 million laboratory tests from half a million patients, in addition to diverse genomics signatures to identify over 17,000 known drug–disease associations; this approach led to the identification of terbutaline sulfate, an anti-asthmatic, as a promising candidate for the treatment of amyotrophic lateral sclerosis (ALS).

    The UK Clinical Practice Research Datalink (CPRD), the Yellow Card scheme of the Medicines and Healthcare Products Regulatory Agency (MHRA), EudraVigilance (a European database of suspected adverse drug reaction reports managed by the European Medicines Agency (EMA)), the FDA Adverse Event Reporting System (FAERS) and the World Health Organization (WHO) global database for adverse drug reactions (VigiBase) all contain valuable patient, disease and drug data that could serve as important sources for drug repurposing analyses. However, great challenges still lie ahead in accessing and using EHR data, including ethical and legal obstacles that limit access to the data and difficulty in extracting the unstructured information present in these databases. Building more research capability into EHR databases could help improve their utility for various downstream opportunities such as drug repurposing. Natural language processing and machine-learning techniques could also prove valuable.

    Post-marketing surveillance data and clinical trial data are two other important big data sources, but access may be limited for commercial or confidentiality reasons. However, there is increasing realization that opening up access to such wealth of information can aid further drug development research. In October 2016, the EMA started providing direct public access to clinical trial data submitted by pharmaceutical companies and has published reports on six different drugs to date (European Medicines Agency Clinical Data; see Related links). The data can be used for independent reanalysis by academics and researchers and may indicate drug repurposing leads.

    Novel sources of data for drug repurposing. Immortalized human cancer cell lines (CCLs) have been used in high-throughput drug screens against hundreds of compounds (both approved and experimental) to test their effect on cell viability56,57. In a number of studies, the pharmacological data sets resulting from these screens have been paired with comprehensive genomic characterization of the probed CCLs, thereby allowing identification of interactions between molecular features of the cell and drug response (pharmacogenomic interactions)58,59,60,61. Mining such publicly available data sets containing paired genomic and pharmacological data on large panels of CCLs has been suggested as a novel resource for identifying drug repositioning opportunities. CCLs are of course imperfect models: they might have acquired molecular alterations providing selective advantages for in vitro culture and are often biased towards certain molecular subtypes. However, despite these limitations, studies have shown how identifying pharmacogenomic interactions recapitulate therapeutic genomic markers already in clinical use, with a strength of association that is comparable to that observed in the clinic58,59,60,61.

    More recently, CCL studies have also been integrated with the genomic characterization of large cohorts of primary tumours to prioritize the identified pharmacogenomic interactions on the basis of the clinical prevalence of the involved genomic alterations60. Strikingly, many of the novel identified pharmacogenomic interactions were specific to cancers of a given tissue type and involved drugs that are already in clinical use for other diseases or for cancers of other tissue types. The data arising from these types of study could be used to identify drug repurposing opportunities. Furthermore, this novel investigative avenue would offer an additional advantage: identification of the genomic alteration involved in a pharmacogenomic interaction with a repurposable drug would allow it to be prescribed to a very well-defined subpopulation of patients, thus advancing personalized cancer therapy.

    EHR-linked large DNA biobanks could be another frontier in accelerating drug repurposing research62. GlaxoSmithKline utilized China Kadoorie Biobank (CKB)63, a prospective cohort of half a million individuals, to examine the role of PLA2G7 gene variants in major vascular disease64 following the failure of two consecutive phase III trials for darapladib (an inhibitor of the PLA2G7 gene product Lp-PLA2) in coronary heart disease and acute coronary syndrome65,66. PLA2G7 gene variants did not show any association with major vascular disease, providing further support for findings from the phase III trials. Although a biobank resource was used to confirm the lack of efficacy of a drug in this case, the same approach could be used to confirm gene targets for drug repurposing. Tapping into resources offered by large biobanks that are linked to EHRs, such as the UK Biobank, may be a valuable approach for assessing potential drug targets.

    Advances in sequencing technologies are enabling the collection of large quantities of comprehensive genomic data from many individuals that could be useful for drug repurposing. For example, the HiSeq X Ten system developed by Illumina (San Diego, California) is able to sequence more than 18,000 whole human genomes per year (the volume of which will be 3.6 petabytes or 3,600 terabytes)67. Large-scale projects harnessing such technologies include the 100,000 genome project launched in the UK in 2014 (Ref.68), which has a focus on rare diseases and cancer, and the All of Us research programme in the United States (formerly called the Precision Medicine Initiative69), which will genotype 1 million individuals. This is in addition to various initiatives by other countries (for example, China has announced its own precision medicine genome sequencing initiative, with an estimated cost of $9.2 billion70) and private consortia (for example, AstraZeneca's genome sequencing initiative in drug discovery (see Related links) in collaboration with Human Longevity in the US, the Wellcome Trust Sanger Institute in the UK and The Institute for Molecular Medicine in Finland, which will involve 2 million individuals). Data from these projects could provide new insights into the genetic basis of disease and indicate therapeutic targets for both new drug discovery and opportunities for drug repurposing, as with GWAS discussed above. This could be particularly valuable for rare diseases (Box 1) if causative genetic variations are identified in proteins for which potential candidates for drug repurposing are already available. For example, the phosphatidylinositol 3-kinase α-selective inhibitor, alpelisib (BYL719), which has been developed for the treatment of PIK3CA-altered tumours71, was recently shown to be effective in a mouse model of, and in 19 human subjects with, PIK3CA-related overgrowth syndromes (PROS) based on the fact that affected patients have somatic, mosaic gain-of-function mutations in the PIK3CA gene72.

    Nevertheless, it should be noted that the nature of the big data from such projects and from the use of other high-throughput technologies poses considerable challenges for analysis and effective application, both in new drug discovery and drug repositioning (Box 5).

    Box 5: The challenges of big data

    Advances in technology such as next-generation sequencing and continuously reducing costs mean that researchers can generate large quantities of experimental data; these include data generated by high-throughput DNA and RNA sequencing, mass spectrometry, metabolomics and transcriptomic data, phenotyping and many more. Added to this are large amounts of clinical data that are increasingly becoming available from electronic health records (EHRs), clinical trials and biobanks. Such data are often referred to as big data — data sets that are so large or complex that traditional data processing methods are inadequate120.

    Big data are important for improving our understanding of disease and developing strategies for disease prevention and treatment. However, we are facing an increasing gap between our ability to generate big biomedical data and our ability to integrate, analyse and interpret the data67. This is further compounded by our ability to generate large amounts of data in a minimal amount of time. Another problem with big data is that they are disparate and heterogeneous, which makes data integration extremely difficult120,121. Integrating multiple types of data has proved to increase the power of analysis122, and there are already some examples in drug repurposing where this strategy has been utilized at a limited scale123,124. However, much of the data generated are unstructured, such as imaging and structural data, and this adds another layer of complexity. There is an urgent need for technology solutions that can combine heterogeneous data sets and integrate, analyse and interpret them.

    Finally, another bottleneck lies in accessing various types of data120,121. Although the publicly available databases for transcriptomic data are well known and contain standardized data, such databases are rare for other types of data, such as clinical trial data and structural, in vitro or imaging data. For example, access to clinical trial data is limited at the moment, and even if access is obtained, this may involve mining of enormous amounts of data (for example, the clinical trial data published by the European Medicines Agency for only two drugs, carfilzomib and lesinurad, constitutes ~260,000 pages of information in over 100 clinical reports). Therefore, it is important to have publicly accessible repositories that hold data in a standardized format and have the necessary tools to mine such data.

    Finally, online self-reported patient data have been suggested as another new potential source for drug repurposing11,73. One example is self-reported data on the usage of lithium carbonate by patients with ALS, which were used to derive useful conclusions about the efficacy of usage73. Even though no effect of lithium on disease progression was identified, the approach suggests that data reported by patients over the Internet may be useful for accelerating clinical discovery and evaluating the effectiveness of drugs already in use. Use of patient-reported outcome data collected over the Internet offers advantages such as faster data collection, reduced cost and enhanced patient engagement; however, this approach also carries considerable risks in terms of bias and, potentially, patient safety if it involves patient self-prescribing.

    Experimental approaches

    Binding assays to identify target interactions. Proteomic techniques such as affinity chromatography and mass spectrometry have been used as approaches to identify binding partners for an increasing number of drugs74. In an era of chemical biology for target validation, analyses of the targets and off-targets of drugs and drug repurposing have become natural bedfellows. For example, the Cellular ThermoStability Assay (CETSA) technique has been introduced as a way of mapping target engagement in cells using biophysical principles that predict thermal stabilization of target proteins by drug-like ligands that possess the appropriate cellular affinity75.

    Examples of early successes with this technique include the confirmation of cellular targets for the tyrosine kinase inhibitor (TKI) crizotinib76 and the detection of quinone reductase 2 (NQO2) as a cellular off-target of acetaminophen (paracetamol)77. A need to address the promiscuity of protein kinase inhibitors has long been recognized78, and the prediction that protein kinases will represent the major drug targets of the 21st century79 may still be fulfilled. This has increased efforts to develop better probe compounds for preclinical research that can inform clinical drug development and repurposing through an evidence-based pharmacological 'audit trail' in cells80. It is also important to note that the 'mistakes' made in various kinase drug discovery approaches have much to contribute, and early-stage unbiased affinity approaches are particularly useful for understanding the likely effects of compounds in cells, which include paradoxical kinase activation by inhibitors81 that underlie mechanistic off-target tumour initiation in patients82. For example, to understand the complexity of compound effects, Brehmer and colleagues incubated HeLa cell lysate extracts with a matrix containing covalently attached gefitinib; mass spectrometry of the resultant elutes identified more than 20 different protein kinases as putative gefitinib targets74. Broader efforts have also been employed to evaluate kinase inhibitors by employing affinity matrices containing 'kinobeads', which capture proteins before analytical quantification83, often revealing interesting novel off-targets for well-known drugs84,85. Similar approaches have now revealed many of the molecular on and off targets for important clinical agents, such as the first-to-market (and relatively specific) BCR–ABL inhibitor imatinib86, which has been successfully repurposed to treat KIT-driven gastrointestinal stromal tumours87, the newer BCR–ABL inhibitors nilotinib and dasatinib, and the very promiscuous kinase inhibitor ponatinib.

    Chemical genetics can also provide a better understanding of the relationship between binding and efficacy in the cellular context88. In turn, these findings can be rapidly translated into new clinical areas or to address drug-resistance outcomes of prolonged exposure that are near-inevitable phenotypic responses to kinase inhibitor therapy in cancer89,90. Many of these studies stem from industry-driven high-throughput direct binding or catalytic assays, in which small-molecule–kinase binding is analysed in a kinome-wide fashion using a variety of in vitro and increasingly organism-based assays to generate heat maps of biologically important interactions91,92. In one such study, Karaman and colleagues92 used an in vitro competition binding assay to evaluate 38 kinase inhibitors against a panel of 317 distinct human protein kinases; their analysis identified a total of 3,175 binding interactions. Interestingly, some kinase inhibitors such as sorafenib and dasatinib showed higher affinity to secondary kinase targets than their known primary target, potentially informing (or invalidating) their use in patient populations. In the kinase field in particular, non-kinase targets of small molecules originally designed to inhibit protein kinases are increasingly recognized93 and are leading to repurposing opportunities in cancer19, as Zika virus modulators94 and as potential agents to treat antibiotic-resistant microorganisms95.

    Phenotypic screening. Phenotypic screening can identify compounds that show disease-relevant effects in model systems without prior knowledge of the target(s) affected96. In the context of drug repurposing, if the compounds screened are approved or investigational drugs, this may indicate repurposing opportunities that can readily be pursued. Typically, in vitro phenotypic screens use a wide range of cell-based assays in a 96-well format. For example, Iljin and colleagues97 conducted high-throughput cell-based screening of a library of 4,910 drug-like small-molecule compounds in four prostate cancer and two non-malignant prostate epithelial cell lines with proliferation as the primary end point. They identified disulfiram, a drug used for alcohol abuse, to be a selective antineoplastic agent, which was then validated using genome-wide gene expression studies. Whole-organism phenotypic assays are also utilized in drug repurposing; Cousin and colleagues98 used a zebrafish model to evaluate 39 FDA-approved medications for use in tobacco dependence and found that compounds such as apomorphine and topiramate modified nicotine-induced and ethanol-induced behaviour in this model.

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