life science

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Published By: SAS     Published Date: Jun 27, 2019
In the quest to understand how a therapeutic intervention performs in actual use – in real medical practice outside the controlled environment of clinical trials – many life sciences organizations are stymied. They rely on one-off processes, disconnected tools, costly and redundant data stores, and ad hoc discovery methods. It’s time to standardize real-world data and analytics platforms – to establish much-needed consistency, governance, repeatability, sharing and reuse. The organizations that achieve these goals will formalize their knowledge base and make it scalable, while significantly reducing turnaround times, resources and cost. Learn the seven key components for putting that structure to real-world evidence – and four ways to take it to the next level.
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SAS
Published By: SAS     Published Date: Jun 27, 2019
The potential for analytics to transform health care – to make it more personalized, intelligent, cost-efficient and effective – is immense. The question is, how will you move your organization forward to exploit the power of analytics? In this paper, explore recommendations and best practices from experts at UnitedHealth Group, Eli Lilly and Company, and Mercy Virtual who are operationalizing SAS analytics across their enterprises and realizing impressive results.
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SAS
Published By: SAS     Published Date: Jun 27, 2019
Imagine: Your pharmaceutical or medical device has been tested in carefully designed clinical trials and shown to meet required standards of efficacy and safety. It has gained regulatory approval and has gone to market. Now you want to know, does it measure up to its promise when used in the real world? Does it materially improve patient outcomes? Does it outperform alternative therapies? Does it achieve these outcomes at an appropriate value? Do you know which patients are most likely to benefit from it? Can you prove it, with statistical rigor? As the health care system moves toward a patient-centric, value-based approach, questions such as these are getting heightened scrutiny from all angles – from regula- tors, payers, providers and patients. And they should. Real-world evidence (RWE) can provide new insight into the benefits, risks and cost effectiveness of medicines and medical devices in actual use – evidence that can enable life sciences companies to develop better therapies
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SAS
Published By: SAS     Published Date: Jun 27, 2019
Hear about real-world use cases that demonstrate how data, advanced analytics, AI and IoMT are helping life sciences companies increase efficiency.
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SAS
Published By: SAS     Published Date: Jun 27, 2019
Learn more about where these two industries intersect as the application of AI and advanced analytics matures, including several use case examples.
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SAS
Published By: Group M_IBM Q3'19     Published Date: Jun 25, 2019
In the Garage, you work side by side with IBM experts to create first-of-a-kind MVPs, experiment with emerging technologies and quickly learn from failures. In this webinar hear from Ed Forman, Partner of Cognitive Process Transformation at IBM. Ed has partnered with organizations across industries including automotive, life sciences, financial services and telecommunications. In his work with the IBM Garage he has helped shape an award-winning method for innovation that has transformed business models for Fortune 500 clients. Listen to this 30-minute presentation to find out more.
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Group M_IBM Q3'19
Published By: Group M_IBM Q2'19     Published Date: May 31, 2019
In the Garage, you work side by side with IBM experts to create first-of-a-kind MVPs, experiment with emerging technologies and quickly learn from failures. In this webinar hear from Ed Forman, Partner of Cognitive Process Transformation at IBM. Ed has partnered with organizations across industries including automotive, life sciences, financial services and telecommunications. In his work with the IBM Garage he has helped shape an award-winning method for innovation that has transformed business models for Fortune 500 clients. Listen to this 30-minute presentation to find out more.
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Group M_IBM Q2'19
Published By: Domino Data Lab     Published Date: May 23, 2019
As data science becomes a critical capability for companies, IT leaders are finding themselves responsible for enabling data science teams with infrastructure and tooling. But data science is much more like an experimental research organization than the engineering and business teams that IT organizations support today. Compounding the challenge, data science teams are growing fast, often by 100% a year. This guide will quickly help you understand what data science teams do to build their predictive models and how to best support them. Learn how to modernize IT’s approach to ensure your company’s data science teams perform their best, and maximize impact to the business. Some highlights include: Why data science should not be treated like engineering. How to go beyond simple infrastructure allocation and give data science teams capabilities to manage their workflows and model lifecycle. Why agility and special hardware to support burst computing are so important to data science break
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Domino Data Lab
Published By: Seismic     Published Date: May 14, 2019
Seventy percent of healthcare and life sciences companies are looking to digitize their operations to facilitate growth, but only 2% have completed a digital transformation. To remain compliant and improve engagement you need to develop a core infrastructure that’s more effective and efficient and incorporate modern technologies to do so. This e-book reviews the basics of digital transformation, the tools and resources you need to get started, and the plays you’ll need for game time success: ? Play #1: Understand your customers ? Play #2: Evaluate where you stand today ? Play #3: Research modern technology ? Play #4: Plan and implement for game time ? Play #5: Measure your success
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Seismic
Published By: MuleSoft     Published Date: Apr 15, 2019
Healthcare organizations across the care continuum, from hospitals and health systems, to health insurers, to life sciences companies, must digitally transform in order to address legislative and market disruption. Driving digital transformation in healthcare requires connectivity across an ever-increasing number of applications, data and devices. Because of this, connectivity has emerged as a bottleneck that slows the development of new applications and the adoption of new technologies. In response, leading healthcare organizations have adopted API-led connectivity, which eliminates this connectivity bottleneck and enables 2-5X IT project delivery. Download this eBook to learn: How leading healthcare organizations like Sutter Health, Premera Blue Cross and Hologic are leveraging API-led connectivity to accelerate IT project delivery speed How APIs can be used to address the unique business and IT challenges faced by health systems, health insurers and life sciences companies How Mu
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MuleSoft
Published By: MuleSoft     Published Date: Apr 15, 2019
The healthcare industry has been affected by disruption and the need for healthcare innovation. Legislative, market, and technology pressures make it imperative for healthcare organizations — including hospitals and health systems, payers, and life sciences companies — to become more agile. IT teams in the industry are considering a microservices-based architecture as a means of accelerating healthcare innovation and increasing project delivery speed. MuleSoft research suggests that application development productivity increases of up to 10x are possible. Healthcare specifically stands to benefit from this architectural paradigm. This whitepaper will address: Why microservices matter for healthcare IT teams and for healthcare innovation Design principles for a microservices architecture How Anypoint Platform can help you implement microservices best practices
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MuleSoft
Published By: MuleSoft     Published Date: Apr 15, 2019
Life sciences companies are facing increasing pressure to provide new products to market faster than ever before while adhering to the growing number of safety and regulatory needs. Pfizer, one of the world's largest pharmaceutical companies, is transforming its business with an application network that enables the scale and speed necessary to compete in the digital economy. Read this whitepaper to learn: How Pfizer achieved a 69% decrease in IT project delivery costs with API-led connectivity. How Pfizer’s application network enabled omnichannel physician engagement and secure clinical data sharing. How Pfizer’s Center for Enablement (C4E) unlocked speed and agility through API reuse across the enterprise.
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MuleSoft
Published By: Domino Data Lab     Published Date: Feb 08, 2019
As data science becomes a critical capability for companies, IT leaders are finding themselves responsible for enabling data science teams with infrastructure and tooling. But data science is much more like an experimental research organization than the engineering and business teams that IT organizations support today. Compounding the challenge, data science teams are growing fast, often by 100% a year. This guide will quickly help you understand what data science teams do to build their predictive models and how to best support them. Learn how to modernize IT’s approach to ensure your company’s data science teams perform their best, and maximize impact to the business. Some highlights include: Why data science should not be treated like engineering. How to go beyond simple infrastructure allocation and give data science teams capabilities to manage their workflows and model lifecycle. Why agility and special hardware to support burst computing are so important to data science break
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Domino Data Lab
Published By: Infosys     Published Date: Dec 03, 2018
Data is a truly inexhaustible resource for an organization. It creates endless possibilities to make data do more. As a technology partner of hundreds of organizations around the world, Infosys helps clients navigate the journey from their current state to the next. Facilitating clients’ transition into data-native enterprises is a crucial part. To understand how companies are using data analytics today and their expectations in a world of endless possibilities with data, we recently commissioned an independent survey of 1,062 senior executives from organizations with annual revenues exceeding US$ 1 billion, in the United States, Europe, Australia, and New Zealand. The respondents were from business and technology roles, who were decision makers, program managers and external consultants; represented 12 industries, grouped into seven industry clusters, such as, consumer goods, retail and logistics, energy and utilities, financial services and insurance, healthcare and life sciences, h
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Infosys
Published By: Fitbit     Published Date: Nov 12, 2018
The secret to employee health and happiness. It's a fact: positive social interactions at work have been shown to boost employee health. Social connections are just as important in the workplace as they are in other aspects of life. Being surrounded by compassionate, friendly coworkers can boost productivity and commitment to the workplace. Check out our white paper on social connectedness to explore: ? The science of being social. ? How social behaviors impact our health. ? Key takeaways on driving social engagement as part of your wellness program.
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Fitbit
Published By: AWS     Published Date: Nov 08, 2018
In this webinar, you’ll learn how Reltio and IQVIA provide holistic data management solutions for traditional pharma, as well as for emerging biotech and consumer health companies, on Amazon Web Services (AWS).
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AWS
Published By: AWS     Published Date: Nov 08, 2018
In this webinar, you will learn how Allergan used Druva and AWS during the acquisition of ZELTIQ Aesthetics. You will hear how Allergan protected against accidental and purposeful data loss, and how backup data can be used for eDiscovery and forensic analysis.
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AWS
Published By: AWS     Published Date: Nov 08, 2018
In this webinar, you’ll learn how a major Healthcare organization is using integrated, reliable, and secure cloud-based solutions from Commvault and Amazon Web Services (AWS) to help address significant data growth while reducing infrastructure costs.
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AWS
Published By: Cognizant     Published Date: Oct 23, 2018
Value-based care is the predominant model for enabling the healthcare industry to control costs and deliver better information to consumers. The basic idea is that reimbursements are based on the quality of the outcome of a procedure, episode of care, use of a device or therapy. Under this model, life sciences companies are rewarded for improving health outcomes and/or reducing the costs to achieve those outcomes. It requires life sciences companies to rethink many of their processes, from R&D through the commercial phase. Navigating those momentous shifts requires that life sciences companies embrace a range of digital technologies which will enable a holistic approach to value-based care. This white paper will examine the drive for value-based care, its impact on life sciences companies and how technology platforms can address the challenges the industry is facing.
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cognizant, life sciences, digital
    
Cognizant
Published By: Cognizant     Published Date: Oct 23, 2018
A group of emerging technologies is rapidly creating numerous opportunities for life sciences companies to improve productivity, enhance patient care and ensure regulatory compliance. These technologies include robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), blockchain, the Internet of Things (IoT), 3-D printing and augmented reality/ virtual reality (AR/ VR). This whitepaper presents a preview of five pivotal technology trends remaking the life sciences industry: AI and automation, human augmentation, edge analytics/ processing, data ownership and protection, and the intermingling of products and services.
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cognizant, life sciences, patient care
    
Cognizant
Published By: SAP     Published Date: Oct 11, 2018
Life sciences is an industry on the move. Driven by regulatory changes, manufacturing capacity, and margin pressures, the industry’s supply chain and procurement leaders are relying heavily on contract manufacturing organizations (CMOs). These relationships require new ways of managing product quality and costs across the supply network. Learn how a true digital strategy can optimize internal and external processes – and extend them beyond the enterprise – so you can excel in today’s complex market.
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SAP
Published By: SAP Ariba     Published Date: Oct 11, 2018
Life sciences is an industry on the move. Driven by regulatory changes, manufacturing capacity, and margin pressures, the industry’s supply chain and procurement leaders are relying heavily on contract manufacturing organizations (CMOs). These relationships require new ways of managing product quality and costs across the supply network. Learn how a true digital strategy can optimize internal and external processes – and extend them beyond the enterprise – so you can excel in today’s complex market.
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SAP Ariba
Published By: Infosys     Published Date: May 21, 2018
Every player in the life sciences sector knows it: the future of healthcare delivery lies in digital disruption. Their objective, therefore, is to positively disrupt their own business model before the competition beats them to it. They need to offer a digitally-enabled patient experience that improves clinical outcomes while also bringing benefits to all the other stakeholders, as seen in the hugely complex value chain of our client - a large pharmaceutical company.
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digital, disruption, technology, science, life, healthcare
    
Infosys
Published By: MarkLogic     Published Date: May 07, 2018
Executives, managers, and users will not trust data unless they understand where it came from. Enterprise metadata is the “data about data” that makes this trust possible. Unfortunately, many healthcare and life sciences organizations struggle to collect and manage metadata with their existing relational and column-family technology tools. MarkLogic’s multi-model architecture makes it easier to manage metadata, and build trust in the quality and lineage of enterprise data. Healthcare and life sciences companies are using MarkLogic’s smart metadata management capabilities to improve search and discovery, simplify regulatory compliance, deliver more accurate and reliable quality reports, and provide better customer service. This paper explains the essence and advantages of the MarkLogic approach.
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agile, enterprise, metadata, management, organization
    
MarkLogic
Published By: MarkLogic     Published Date: May 07, 2018
Learn how Life Sciences organizations can accelerate Real World Evidence by achieving faster time to insight with a metadata-driven, semantically enriched operational platform. Real World Evidence (RWE) is today’s big data challenge in Life Sciences. Medical records, registries, consultation reports, insurance claims, pharmacy data, social media, and patient surveys all contain valuable insights that Life Sciences organizations need to ascertain and prove the safety, efficacy, and value of their drugs and medical devices. Learn how Life Sciences organizations can accelerate RWE with a metadata-driven, semantically enriched operational platform that enables them to: • Unify, harmonize and ensure governance of information from diverse data sources • Transform information into evidence that proves product efficacy and safety • Identify data patterns, connections, and relationships for faster time to insight
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data, integration, drug, device, manufacture, science
    
MarkLogic
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