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A companion diagnostic is a therapeutic device, frequently an in vitro gadget, which gives data that is crucial for the effective and safe utilization in comparing drug or organic products. The test helps a healthcare professional to figure out if a specific drug is advantages to patients will or exceed any potential genuine symptoms or risk. • Abbott Laboratories, Inc. (US) • Ventana Medical Systems, Inc. (US) • Agilent Technologies (US) • Dako (Denmark) • Qiagen (Germany) • f. Hoffmann-la Roche ltd (Switzerland) • Resonance Health (Australia) The report for Global Companion Diagnostics market of Market Research Future comprises of extensive primary research along with the detailed analysis of qualitative as well as quantitative aspects by various industry experts, key opinion leaders to gain the deeper insight of the market and industry performance. Taste the market data and market information presented through more than 50 market data tables and figures spread in 80 numbers of pages of the project report. Avail the in-depth table of content TOC & market synopsis on “Global Companion Diagnostics Market Research Report- Forecast To 2022" • To provide detailed analysis of the market structure along with forecast for the next 7 years of the various segments and sub-segments of the companion diagnostics market • To provide insights about factors affecting the market growth • To analyze the companion diagnostics market based on various factors- price analysis, supply chain analysis, porters five force analysis etc. • To provide historical and forecast revenue of the market segments and sub-segments with respect to four main geographies and their countries- Americas, Europe, Asia-Pacific, and Middle East & Africa. • To provide country level analysis of the market with respect to the current market size and future prospective • To provide country level analysis of the market for segments by type of treatment, by type of testing, and its sub-segments • To provide overview of key players and their strategic profiling in the market, comprehensively analyzing their core competencies, and drawing a competitive landscape for the market • To track and analyze competitive developments such as joint ventures, strategic alliances, mergers and acquisitions, new product developments, and research and developments in the global companion diagnostics market. Market Segments: Segmentation by types • Theranostics • Monitoring Tests Segmentation by applications • Cancer Diseases • Cardiovascular • Central Nervous Systems Segmentation by end-user • Hospital • Research Laboratories • Medical Institutes. The report gives the clear picture of current market scenario which includes historical and projected market size in terms of value and volume, technological advancement, macro economical and governing factors in the market. The report provides details information and strategies of the top key players in the industry. The report also gives a broad study of the different markets segments and regions Global Thymus Cancer Information, by types (type A, type AB, type B1, type B2, type B3 and thymic carcinoma), by treatment (surgery, radiotherapy, chemotherapy and others) By care centers (Hospitals, Clinics, Diagnostic centers, Research laboratories and others) - Forecast to 2024 About Market Research Future: At Market Research Future (MRFR), we enable our customers to unravel the complexity of various industries through our Cooked Research Report (CRR), Half-Cooked Research Reports (HCRR), Raw Research Reports (3R), Continuous-Feed Research (CFR), and Market Research & Consulting Services. MRFR team have supreme objective to provide the optimum quality market research and intelligence services to our clients. Our market research studies by products, services, technologies, applications, end users, and market players for global, regional, and country level market segments, enable our clients to see more, know more, and do more, which help to answer all their most important questions. For more information, please visit https://www.marketresearchfuture.com/reports/companion-diagnostics-market


DUBLIN--(BUSINESS WIRE)--Research and Markets has announced the addition of the "High-Resolution Melting Analysis Market by Product (Supermix Reagent, RT PCR Instrument, Software), Application (SNP Genotyping, Mutation Discovery, Epigenetics), Enduser (Research Laboratories, Hospital, Diagnostic Center) - Global Forecast to 2021" report to their offering. The global high-resolution melting analysis market is expected to reach USD 302.1 Million by 2021 from USD 259.4 Million in 2016, at a CAGR of 3.1% during the forecast period of 2016 to 2021. In this report, the global market is broadly segmented on the basis of product & service, application, end user, and region. Rising prevalence of infectious diseases and genetic disorders; increasing public-private investments, funds, and grants for research on genetic analysis technologies; and advantages of HRM over other genotyping technologies are the major factors driving market growth. The report maps each type of high-resolution melting analysis product in these geographic and regional segments. In 2016, North America (comprising the U.S. and Canada) accounted for the largest share of the global market, followed by Europe. The rising prevalence of infectious diseases, genetic disorders, & other chronic diseases and the large number of genotyping-based research and development projects in this region are the key growth drivers for the North American market. For more information about this report visit http://www.researchandmarkets.com/research/242fbx/highresolution


Thymus cancer is an uncommon tumor, best known for its association with the neuromuscular disorder myasthenia gravis and is found in 20% of patients with myasthenia gravis. It is a rare type of cancer which accounts for only 1 % of total cancers. The tumor occurs at the rate of only 1.5 cases in million people each year in the United States. Once diagnosed, thymus cancer can be removed surgically. The report for Global thymus cancer market of Market Research Future comprises of extensive primary research along with the detailed analysis of qualitative as well as quantitative aspects by various industry experts, key opinion leaders to gain the deeper insight of the market and industry performance. • Amgen Inc • Astellas Pharma Inc • Astrazeneca • Bristol-Myers Squibb • Celgene Corporation • Cellceutix Corporation • Eli Lilly and company • Johnson & Johnson services Inc • Merck & Co. Inc. • Novartis AG • Onxeo SA • Pfizer Inc • Sumitomo Dainippon Pharma Co. Ltd. • Taiwan Liposome Company Ltd. • Takeda pharmaceutical company • Tiziana Life Sciences Plc. Market Highlights: Thymus cancer is a tumor formed on the outer surface originating from the epithelial cells of the thymus. Thymus is a small organ located in the upper chest under the breast bone and makes specific type of white blood cells which help the body fight infection. There are no prominent causes or risk factors for thymus cancer. In the rare cases of a malignant tumor, chemotherapy may also be used. The market for thymus cancer is showing a limited growth. Taste the market data and market information presented through more than 50 market data tables and figures spread in 90 numbers of pages of the project report. Avail the in-depth table of content TOC & market synopsis on “Global Thymus Cancer Market Research Report- Forecast To 2024” • To provide detailed analysis of the market structure along with forecast for the next 8 years of the various segments and sub-segments of the thymus cancer market • To provide insights about factors affecting the market growth • To analyze the thymus cancer market based on various factors- price analysis, supply chain analysis, porters five force analysis etc. • To provide historical and forecast revenue of the market segments and sub-segments with respect to four main geographies and their countries- Americas, Europe, Asia-Pacific, and Middle East & Africa. • To provide country level analysis of the market with respect to the current market size and future prospective • To provide country level analysis of the market for segments by type, by treatment, care centers and its sub-segments. • To provide overview of key players and their strategic profiling in the market, comprehensively analyzing their core competencies, and drawing a competitive landscape for the market • To track and analyze competitive developments such as joint ventures, strategic alliances, mergers and acquisitions, new product developments, and research and developments in the global thymus cancer market. • Thymus cancer drug manufacturers • Thymus cancer drug suppliers • Research and Development (R&D) Companies • Government Research Laboratories • Independent Research Laboratories • Government and Independent Regulatory Authorities • Market Research and Consulting Service Providers • Medical Research Laboratories • Academic Medical Institutes and Universities Global thymus cancer market has been segmented on the basis of types which comprises of type A, type AB, type B1, type B2, type B3 and thymic carcinoma (type C). On the basis of treatment, which consist of surgery, radiotherapy, chemotherapy and others. On the basis of care centers, market is segmented into hospitals, clinics, diagnostic centers, research laboratories and others. The report gives the clear picture of current market scenario which includes historical and projected market size in terms of value and volume, technological advancement, macro economical and governing factors in the market. Global Medical Holography Information, by types (Reflection holography, Transmission holography, Hybrid Holography and others), by applications (Endoscopy, Medical Tomography, Ophthalmology, Dentistry, Otology, Orthopedics, X-Rays and others) By end users (Research Laboratories, Medical Academic Institutes, Hospitals and Clinics, Life Science Companies and others) - Forecast to 2027 About Market Research Future: At Market Research Future (MRFR), we enable our customers to unravel the complexity of various industries through our Cooked Research Report (CRR), Half-Cooked Research Reports (HCRR), Raw Research Reports (3R), Continuous-Feed Research (CFR), and Market Research & Consulting Services. MRFR team have supreme objective to provide the optimum quality market research and intelligence services to our clients. Our market research studies by products, services, technologies, applications, end users, and market players for global, regional, and country level market segments, enable our clients to see more, know more, and do more, which help to answer all their most important questions. For more information, please visit https://www.marketresearchfuture.com/reports/thymus-cancer-market


News Article | May 19, 2017
Site: phys.org

Automobile traffic in this "smart city" should move almost constantly, stopping or slowing as little as possible at traffic lights, on freeway ramps and in traffic circles, says Liu, a Ph.D. candidate in industrial engineering. Likewise, electricity should flow through power lines at an optimal rate, high enough to achieve maximum efficiency but not so high that wires overheat. These streamlined flows of people and power, says Liu, are made possible by machines that process large quantities of data in real time and learn to make intelligent decisions. Liu develops large-scale optimization algorithms, or mathematical models, and applies them to machine learning. His goal is to design a power-transmission system that meets the energy demands of a city with maximum efficiency and minimal cost. Liu recently received the IBM Ph.D. Fellowship Award to study power systems and data analytics at IBM Research-Ireland, one of 12 IBM research laboratories in the world. The fellowship is given each year to 50 outstanding students worldwide. IBM Research-Ireland conducts research into the Cognitive Internet of Things, cognitive integrated healthcare, interactive reasoning, data centric computing and the cloud and privacy. As part of the fellowship program, Liu has been assigned a mentor from IBM Research-Ireland. He will continue his research into power systems and data analytics and will likely spend part of the fall semester in Ireland or at the company's New York site. As an example of machine learning or signal processing, Liu points to E-ZPass, the electronic toll-collection system that serves motorists in the eastern half of the United States and in Ontario, Canada. E-ZPass photographs the license plates of passing cars and employs optimization techniques to read the letters and numbers of license plates, even in blurry photos. Machine learning is also used by online shopping sites such as Amazon to analyze a consumer's purchasing history and recommend similar products that the consumer might be interested in buying. Liu's research focuses on the buses, or intermediate power stations, which take electricity from a power plant and distribute it to homes and businesses in a utility company's service area. He develops models that seek to determine the optimal number, and optimal location, of intermediate stations. He is also working on the development of fast solvers for the popular deep neural networks and other graphical models. A utility company's goal, says Liu, is to transmit electricity from its intermediate stations with maximum efficiency. If a station's wires carry too much electricity, he says, they will exceed the station's voltage limits and overheat, with undesired consequences, shutting down or even igniting. If the wires carry too little electricity, the system loses efficiency. "We want to find a middle point," says Liu. "We can never reach the voltage limit. On the other hand, if the amount of electricity being transmitted is too low, efficiency is reduced. We want to be efficient but not get too close to the limit." A second goal, says Liu, is to solve problems that arise as quickly as possible. "We want to speed up optimization for power networks," he says. "Our goal is to transmit power efficiently while solving problems as quickly as possible." Power grids and other networks generate massive streams of data that must be processed and analyzed in real time. Liu and his group set up polynomial optimization problems (POPs) and solve them by randomly choosing coordinates of data, which can be solved in parallel by multiple machines at the same time to improve efficiency. This contrasts, he says, with the conventional technique, which is called the Newton method and is difficult to parallelize. "The Newton method processes all the data," says Liu, "but it is not possible to do this with a power system because it generates so much data. Our method doesn't process all the data; instead, we pick coordinates, or bits of data, randomly. This greatly reduces the total amount of time needed to solve a problem. "To solve a multidimensional problem using the traditional method took days and did not always yield a feasible solution. With our method, we can arrive at a feasible solution in several minutes to half an hour." Liu and his group reported their results recently in an article titled "Hybrid Methods in Solving Alternating-Current Optimal Power Flows." The article was coauthored with Alan C. Liddell, Jakub Mareček and Martin Takáč. Takáč, an assistant professor of industrial and systems engineering, is Liu's Lehigh Ph.D. adviser. Mareček is with IBM-Ireland, and Liddell is with Notre Dame University. Liu enrolled at Lehigh in 2013 after completing his M.S. in mathematics from the State University of New York at Buffalo. He holds a B.S. in mathematics from Nankai University in Tianjin, China. His other honors include the Dean's Doctoral Assistantship and Dean's Fellowship from Lehigh's P.C. Rossin College of Engineering and Applied Science, the Gotshall Fellowship from Lehigh, and the American Express Machine Learning Contest Award. At Lehigh, Liu is part of a research group called Optimization and Machine Learning (OptML), which includes Takáč; Katya Scheinberg, the Harvey E. Wagner Endowed Chair Professor of Industrial and Systems Engineering; and Frank Curtis, associate professor of industrial and systems engineering. Students in the OptML group receive support to present their work at international conferences. Liu's papers and posters have been accepted at conferences of Neural Information Processing Systems (NIPS), the Institute for Operations Research and the Management Sciences (INFORMS), the International Conference on Machine Learning (ICML); and the Machine Learning Symposium in New York City. Liu and his fellow students are also encouraged to do industrial internships. Liu has completed internships with Siemens Corporate Research and IBM. This summer he will work in Boston with Mitsubishi's Electricity Research Laboratories (MERL) in data analytics. In 2012, he worked with Argonnes National Laboratory near Chicago. "These are amazing opportunities," Liu says. "These are different companies, totally different. These internships connect us to industry. They give us the chance to do something we're interested in and to learn new knowledge at the same time. "The professors in our group are very supportive. They really help us learn how we can contribute and make an impact." Explore further: Scientists propose better battery system for smart home use


News Article | May 19, 2017
Site: www.eurekalert.org

The modern city, says Jie Liu, can be considered a web of networks that should run like a healthy, well-tuned circulatory system. Automobile traffic in this "smart city" should move almost constantly, stopping or slowing as little as possible at traffic lights, on freeway ramps and in traffic circles, says Liu, a Ph.D. candidate in industrial engineering. Likewise, electricity should flow through power lines at an optimal rate, high enough to achieve maximum efficiency but not so high that wires overheat. These streamlined flows of people and power, says Liu, are made possible by machines that process large quantities of data in real time and learn to make intelligent decisions. Liu develops large-scale optimization algorithms, or mathematical models, and applies them to machine learning. His goal is to design a power-transmission system that meets the energy demands of a city with maximum efficiency and minimal cost. Liu recently received the IBM Ph.D. Fellowship Award to study power systems and data analytics at IBM Research-Ireland, one of 12 IBM research laboratories in the world. The fellowship is given each year to 50 outstanding students worldwide. IBM Research-Ireland conducts research into the Cognitive Internet of Things, cognitive integrated healthcare, interactive reasoning, data centric computing and the cloud and privacy. As part of the fellowship program, Liu has been assigned a mentor from IBM Research-Ireland. He will continue his research into power systems and data analytics and will likely spend part of the fall semester in Ireland or at the company's New York site. As an example of machine learning or signal processing, Liu points to E-ZPass, the electronic toll-collection system that serves motorists in the eastern half of the United States and in Ontario, Canada. E-ZPass photographs the license plates of passing cars and employs optimization techniques to read the letters and numbers of license plates, even in blurry photos. Machine learning is also used by online shopping sites such as Amazon to analyze a consumer's purchasing history and recommend similar products that the consumer might be interested in buying. Liu's research focuses on the buses, or intermediate power stations, which take electricity from a power plant and distribute it to homes and businesses in a utility company's service area. He develops models that seek to determine the optimal number, and optimal location, of intermediate stations. He is also working on the development of fast solvers for the popular deep neural networks and other graphical models. A utility company's goal, says Liu, is to transmit electricity from its intermediate stations with maximum efficiency. If a station's wires carry too much electricity, he says, they will exceed the station's voltage limits and overheat, with undesired consequences, shutting down or even igniting. If the wires carry too little electricity, the system loses efficiency. "We want to find a middle point," says Liu. "We can never reach the voltage limit. On the other hand, if the amount of electricity being transmitted is too low, efficiency is reduced. We want to be efficient but not get too close to the limit." A second goal, says Liu, is to solve problems that arise as quickly as possible. "We want to speed up optimization for power networks," he says. "Our goal is to transmit power efficiently while solving problems as quickly as possible." Power grids and other networks generate massive streams of data that must be processed and analyzed in real time. Liu and his group set up polynomial optimization problems (POPs) and solve them by randomly choosing coordinates of data, which can be solved in parallel by multiple machines at the same time to improve efficiency. This contrasts, he says, with the conventional technique, which is called the Newton method and is difficult to parallelize. "The Newton method processes all the data," says Liu, "but it is not possible to do this with a power system because it generates so much data. Our method doesn't process all the data; instead, we pick coordinates, or bits of data, randomly. This greatly reduces the total amount of time needed to solve a problem. "To solve a multidimensional problem using the traditional method took days and did not always yield a feasible solution. With our method, we can arrive at a feasible solution in several minutes to half an hour." Liu and his group reported their results recently in an article titled "Hybrid Methods in Solving Alternating-Current Optimal Power Flows." The article was coauthored with Alan C. Liddell, Jakub Mareček and Martin Takáč. Takáč, an assistant professor of industrial and systems engineering, is Liu's Lehigh Ph.D. adviser. Mareček is with IBM-Ireland, and Liddell is with Notre Dame University. Liu enrolled at Lehigh in 2013 after completing his M.S. in mathematics from the State University of New York at Buffalo. He holds a B.S. in mathematics from Nankai University in Tianjin, China. His other honors include the Dean's Doctoral Assistantship and Dean's Fellowship from Lehigh's P.C. Rossin College of Engineering and Applied Science, the Gotshall Fellowship from Lehigh, and the American Express Machine Learning Contest Award. At Lehigh, Liu is part of a research group called Optimization and Machine Learning (OptML), which includes Takáč; Katya Scheinberg, the Harvey E. Wagner Endowed Chair Professor of Industrial and Systems Engineering; and Frank Curtis, associate professor of industrial and systems engineering. Students in the OptML group receive support to present their work at international conferences. Liu's papers and posters have been accepted at conferences of Neural Information Processing Systems (NIPS), the Institute for Operations Research and the Management Sciences (INFORMS), the International Conference on Machine Learning (ICML); and the Machine Learning Symposium in New York City. Liu and his fellow students are also encouraged to do industrial internships. Liu has completed internships with Siemens Corporate Research and IBM. This summer he will work in Boston with Mitsubishi's Electricity Research Laboratories (MERL) in data analytics. In 2012, he worked with Argonnes National Laboratory near Chicago. "These are amazing opportunities," Liu says. "These are different companies, totally different. These internships connect us to industry. They give us the chance to do something we're interested in and to learn new knowledge at the same time. "The professors in our group are very supportive. They really help us learn how we can contribute and make an impact." Story by Kurt Pfitzer, Editor and Writer, Lehigh University Office of Communications and Public Affairs


News Article | May 22, 2017
Site: www.businesswire.com

BOSTON--(BUSINESS WIRE)--Analysis Group, one of the largest private economics consulting firms, announces the promotion of 41 consultants and welcomes seven new affiliates to the firm. “ We are pleased to recognize the outstanding efforts of our consultants, as well as the addition of such impressive new affiliates, all of whom are recognized leaders in their respective fields,” said CEO and Chairman Martha S. Samuelson. Shannon W. Anderson, a professor of management at the UC Davis Graduate School of Management, conducts research on the design of cost accounting systems and on how firms use management control practices to mitigate risk and facilitate collaboration in inter-firm transactions. This research includes performance measurement, incentive contracting, supply chain contracting, and operations management. Professor Anderson uses empirical analysis of firm-level accounting and operational data to test economic theories about firm performance. She also has experience designing and administering surveys and analyzing survey data. Her published work has employed data from many industries, including automotive, electronics manufacturing, office furniture manufacturing, commercial airlines, consumer retail, coal extraction, transportation, and warehousing and distribution. Professor Anderson coauthored the award-winning book Implementing Management Innovations and the textbook Fundamentals of Cost Accounting (now in its 5th edition). Her research has been published in leading research journals, including The Accounting Review, Management Science, and Contemporary Accounting Research, and has been funded by the American Institute of Certified Public Accountants, the Institute of Internal Auditors, and the National Science Foundation, among others. Jacques Crémer, research faculty at the Toulouse School of Economics, is an expert in industrial organization with a focus on competition, contracting, auction and planning theory, and the economics of organization. His recent research examines these issues with applications to the economics of two-sided platforms, industries with network effects, and the Internet. Professor Crémer has testified before the European Commission in relation to the AOL-Time Warner merger, and consulted to clients including Microsoft, Google, Sucre Saint Louis, Intel, GTE, and Time Warner. He has published on such topics as the consequences of mergers on competition and policy, the costs and benefits of vertical integration, and the value of switching costs. Professor Crémer’s work has appeared in peer-reviewed journals such as American Economic Review and The Quarterly Journal of Economics. He is a Fellow of the European Economic Association and the Econometric Society. From 2011 to 2014, Professor Crémer was the Scientific Director at the Toulouse School of Economics (TSE), and was previously Director of Institut d’Economie Industrielle (IDEI), a TSE research institute focused on partnerships with government and industry. Randal S. Milch, a Distinguished Fellow at the New York University School of Law's Center on Law and Security, has extensive expertise in corporate governance, cybersecurity, and data privacy issues. Over his 21 years at Verizon Communications Inc. (where he was EVP and General Counsel to the Chair and CEO), Mr. Milch was deeply involved in the deregulation and transformation of the telecommunications industry. He oversaw the public policy, legal, regulatory, government affairs, and security groups at Verizon, testified before committees of Congress, and organized and led significant public policy campaigns relating to state and federal legislation and transactional approvals. He also managed national security matters, set cyber-policy, and served as the senior cleared executive. Mr. Milch is currently chair of the Board of Equal Justice Works and serves as a trustee of New York University School of Law. He is a former partner in the Washington, D.C. office of Donovan, Leisure, Newton & Irvine. Michael D. Mitzenmacher, the Thomas J. Watson, Sr. Professor of Computer Science at Harvard University’s John A. Paulson School of Engineering and Applied Sciences, researches the design and analysis of algorithms, networks and data transmission, computer security, information theory, and use of encryption. He has consulted to numerous technology companies and research laboratories, including Adverplex (Cogolabs), Akamai, AT&T, Digital Fountain, eHarmony, Fluent Mobile (Fiksu), Google, Huawei, ITA Software, JobSync, Microsoft, Mitsubishi Research Laboratories, and Yahoo. In addition, he has served as an expert witness on software and intellectual property issues in several cases, including testimony in multiple trials. Professor Mitzenmacher has authored or coauthored over 200 conference and journal publications on various topics, including algorithms for the Internet; efficient hash-based data structures; erasure; and error-correcting codes, power laws, and compression. His work on low-density parity-check codes shared the 2002 IEEE Information Theory Society Best Paper Award and won the 2009 ACM SIGCOMM Test of Time Award. Prior to joining Harvard, he worked as a research scientist at Digital Systems Research Center on information retrieval on the Web, erasure codes, error-correcting codes, on-line algorithms, and load balancing. Nathan Novemsky, a professor of marketing in the Yale School of Management and a professor of psychology at Yale University, is an expert in the psychology of judgment and decision-making, an area that overlaps heavily with behavioral economics and consumer behavior. His area of specialization is examining how consumers are affected by information in their environments, including how particular types of information impact their choices and judgments. He is a member of the Yale Center for Customer Insights, and has consulted on numerous legal cases (e.g., deceptive advertising, defamation) related to how individuals interpret information they see in the media and other contexts. Professor Novemsky has published widely on the topics of judgment and decision-making, and regularly teaches these concepts to executives around the world. Paul Oyer, the Fred H. Merrill Professor of Economics at the Stanford Graduate School of Business, is an expert in the economics of organizations and human resource practices. In the field of personnel economics, he has undertaken several studies on how organizations pay and provide incentives for their workers. He has also examined how salespeople and executives react to incentive systems, and why some firms use broad-based stock option programs. In addition, he has conducted research on how firms have adjusted their human resource practices in response to legal barriers for dismissing workers. His current research focuses on how companies identify and recruit workers in highly-skilled and competitive labor markets. His research has been published in numerous peer-reviewed journals, including The Quarterly Journal of Economics, American Economic Review, and The Journal of Finance. Professor Oyer is a research associate with the National Bureau of Economic Research and the editor-in-chief of the Journal of Labor Economics. Prior to joining Stanford, he was on the faculty of the Kellogg School of Management at Northwestern University. He also previously worked for Booz, Allen & Hamilton; 3Com Corporation; and ASK Computer Systems. John E. Ware, the Professor and Chief of Outcomes Measurement Science in the Department of Quantitative Health Sciences at the University of Massachusetts Medical School, is an internationally recognized leader in measuring Patient Reported Outcomes (PRO). His substantial contributions to the outcomes research field have focused on developing, standardizing, and applying health metrics to assess patient reported outcomes. His work has led to the development of a set of standardized, generic PRO measures, including the SF-36® Health Survey, as well as disease-specific measures such as the Headache Impact Test (HIT-6™) survey. Professor Ware frequently provides guidance on evidence support for PRO labeling, and he has been the invited expert for testimony on PRO topics at hearings held by the U.S. Food and Drug Administration. His current research interests also include applying modern psychometric methods to construct more actionable measures, including the first disease-specific quality-of-life (QOL) impact scale standardized across conditions and normed in representative chronically-ill populations. Professor Ware is a member of the National Academy of Medicine (formerly the Institute of Medicine). The firm promoted one consultant to managing principal. Richard A. Mortimer specializes in health economics, industrial organization, microeconomic theory, and econometrics. He has provided economic analyses in numerous antitrust matters involving questions of market power, pricing, and market exclusion and foreclosure in a variety of industries, with a focus on healthcare. He has also provided analyses and expert testimony on behalf of clients in the healthcare industry on litigation and government investigations involving allegations of improper promotion and kickback payments. Dr. Mortimer's experience includes leading analyses of large data sets to assess questions of market definition, class certification, liability, and damages. In addition to work in litigation, Dr. Mortimer has undertaken research in the area of health care policy, and he has authored several public policy studies related to pharmaceutical and general health care legislation. His research has been published in leading peer-reviewed journals, including Health Affairs, Nature Reviews Drug Discovery, The Journal of Industrial Economics, and Journal of Medical Economics. In Boston, Ryan Booth specializes in applying microeconomic theory, antitrust economics, and econometric methods to a range of issues that include assessing the competitive effects of firm conduct, the implications of mergers and acquisitions on consumer welfare, and the effects of government policy on consumer and firm behavior. Emily Cotton has extensive experience conducting complex quantitative and qualitative analyses of data in both mergers and litigation matters, including antitrust, bankruptcy, class certification, intellectual property, securities, survey design, tax, and transfer-pricing matters. Chris Feige specializes in the areas of finance, securities, and financial systems. He has developed complex valuation models, including discounted cash flow models, and has analyzed asset-backed securities and credit ratings in support of expert testimony in a number of bankruptcy and damages matters. Lauren Hunt specializes in providing analyses in finance cases involving complex securities, including mortgage-backed securities (MBS). She has supported experts in numerous litigations involving class action claims, allegations of violations of Sections 10b-5 and 11, and damages claims relating to the underwriting of mortgage loans. Kenneth Weinstein specializes in the application of quantitative methods to real-world problems involving decision-making, strategy, risk management, and litigation. He has managed the analysis of large transaction-level and claims databases, helped clients mitigate the risks associated with distributing controlled substances, and developed flexible damages models for negotiating high-stakes settlements. Hongbo Yang, a specialist in health economics and outcomes research, has directed and conducted numerous studies in a variety of therapeutic areas, including autoimmune diseases, infectious diseases, diabetes, blood disorders, oncology, women's health, and central nervous system diseases. She has led the submission of economic models to multiple health technology assessment agencies (HTAs), including NICE, CADTH, INESSS, and OHTAC. In Denver, Carletta Wong has a decade of experience applying economic consulting expertise to a variety of litigation matters involving securities, accounting, antitrust, corporate governance, off-label pharmaceutical marketing, and intellectual property and trade secrets. In Los Angeles, Keith Betts specializes in the application of advanced biostatistics techniques in the field of health economics and outcomes research. He has broad experience developing research strategies in a range of disease areas, including immunology, hematology, oncology, psychiatry, and virology. In Menlo Park, Anjali D. Oza specializes in the application of economic, statistical, and market research methods to litigation and strategy matters. She is an expert in designing and evaluating qualitative and quantitative surveys, including conjoint analysis and experiments. In Montréal, François Laliberté applies his distinctive competencies in biostatistics and economics to the field of health outcomes research. He has investigated different facets of health research including safety, cost of illness, resource utilization, adherence to therapies, cost-effectiveness, and treatment outcomes. Markus von Wartburg specializes in the application of econometric methods and microeconomic theory to complex problems in antitrust and competition, commercial litigation, media and telecommunications, finance, and intellectual property. In New York City, Duncan Fung specializes in commercial litigation matters involving securities, finance, valuation, corporate governance, and statistics. He has supported clients on consulting engagements involving structured finance products, hedge funds, market microstructure, employee stock options, equity financing trades, and liquidity in money markets. Stephanie Lee’s litigation and advisory experience includes analyses of municipal bonds and interest rate swaps, auction-rate securities, student loan asset-backed securities, residential mortgage-backed securities, hedge funds, and mutual funds. She has provided testimony to Financial Industry Regulatory Authority (FINRA) arbitration panels. In Washington, D.C., F. Michael Nolan has extensive experience applying microeconomic, financial, and accounting principles to complex business litigation matters involving automobiles, agricultural products, high-technology products, telecommunications, consumer electronics, medical equipment, and pharmaceuticals. Federico Temerlin specializes in the application of economics, finance, and statistical theory to the analysis of complex legal and business disputes. He has evaluated issues related to misrepresentation of information, damages modeling, business and asset valuation, complex financial structures, tax shelters, and corporate restructurings. The firm promoted 25 consultants to manager or senior economist. In Beijing: Simeng Han. In Boston: Anya Blank, Konstantin A. Danilov, Katie Franklin, Olga Korolev, Elizabeth Milsark, Jeremy Smith, Yan Song, Todor Stoyanov, David Toniatti, and Kristof Zetenyi. In Chicago: Mark Berberian and David Smith. In Dallas: Jeffrey Hulbert. In Denver: Stacey Chan. In Los Angeles: Maral DerSarkissian, Anne LaRue, Jinlin Song, Nathan Trujillo, and Joel Wiles. In Menlo Park: Daniel Deisenroth and Ruoding Tan. In Montréal: Dominic Pilon. In San Francisco: Tracy Danner. In Washington, D.C.: Anna Gumen. Analysis Group is one of the largest private economics consulting firms, with more than 700 professionals across 11 offices in the United States, Canada, and China. Since 1981, we have provided expertise in economics, finance, health care analytics, and strategy to top law firms, Fortune 500 companies, and government agencies worldwide. Our internal experts, together with our network of affiliated experts from academia, industry, and government, offer our clients exceptional depth of expertise.

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