Data Sciences – The New Analytics Paradigm

Life Sciences, Clinical Trials, Pharmaceutical, Medical Device, Healthcare, Medical Device Clinical Trials,
  • Wednesday, February 10, 2016


Exciting New Opportunities and Challenges in the Analytics & Reporting Space Mean that Timely Access to Information for the Purposes of Insight, Trending and Decision-making is Taking on a Key Role Across the Health Care and Life Sciences Industries


Access to data and key information for the purpose of Analytics has been a constant in the Pharmaceutical / Life Sciences / Health Care industries, and this has been true for a great deal of time. Recent industry challenges such as declining R&D productivity, increased levels of regulatory and payer scrutiny, declining sales, blockbusters going off patent, and the need to reduce healthcare costs while improving patient care etc. have only served to dramatically increase the importance of Data Sciences Analytics as a prerequisite for efficient delivery of Life Sciences and Health Care products and services.

Existing industry IT applications and tools supporting the Data Sciences Analytics function typically operate in a reactive, not proactive manner. They can produce reports and visualizations on “what happened”, but lack sufficient ability to provide crucial insights to help organizations anticipate future business opportunities and issues. In addition, both industries are blurring boundaries and are at a stage of exploiting a potential of variety and volume of data not only from within each individual industry but also across both industries, with the overall focus is moving towards “Patient-centricity”.

Looking at this further, there has been a realization that the process of Analytics, aided by Big Data initiatives, is evolving from Descriptive Analytics to Predictive Analytics and from controlled “Straight-Line” Analytics to less structured “Real World” and “Data Sciences” Analytics. There has also been a corresponding awareness that Data Sciences Analytics & Reporting is no longer a “one size fits all” business process, and that providing a single Data Sciences Analytics environment intended to be used to meet the diverse needs of the Data Science Analytics & Reporting stakeholder community is no longer sufficient

The new Analytics & Reporting paradigm expects to be able to access additional types of data such as Claims Data, EMRs, patient behavior data, Imaging data, Cost Data etc. which have recently emerged alongside the “traditional” forms of Clinical Data produced by R&D processes. These new types of formats are available for integration and aggregation across the entire Data Sciences Analytics spectrum.

To execute this new breed of Analytics, the Role of the Data Scientist has surfaced and become more visible and important within Health Care & Life Sciences organizations. Data Scientists expand upon the more-familiar Business Analyst role by exploring and examining data located in disparate standardized and non-standardized, structured and non-structured, and internal / external data sources, with the intention of looking at data from many perspectives in order to uncover a previously hidden insight, which in turn can lead to a competitive advantage or address a pressing business problem.

This webinar discusses Data Sciences Analytics and the new Analytics Paradigm from an overall industry perspective along with a discussion of the MaxisIT Common Services Analytics Framework and Data Sciences Analytics Workbench functionality which MaxisIT will be implementing within its CTRenaissance suite of tools and how the functionality is used to oversee the presentation and availability of data that will support and drive Data Sciences initiatives across the Health Care & Life Sciences industries, including Predictive Analytics.

Key Takeaways of the webinar include:


  • Understanding the various types and formats of Analytics for the Health Care & Life Sciences industries
  • Reviewing the role and function of the Data Scientist in carrying out new and expanded Analytics projects
  • Discuss the concept and infrastructure of an overall environment to support Data Sciences Analytics
  • Discuss how adoption of Data Sciences Analytics initiatives, coupled with Big Data initiatives, can provide crucial insights to help organizations anticipate future business opportunities




Patrick Zbyszewski, Executive Director of Project and Data Management, Onconova Therapeutics

Patrick Zbyszewski, Executive Director of Project and Data Management, Onconova Therapeutics
Patrick Zbyszewski has more than 15 years of clinical/Pharmaceutical experience in the areas of clinical operations, data management and marketing. He has been employed at small biotechnology firms including Corixa Corporation, clinical research organizations such as Quintiles and INC Research and is currently Executive Director of Project and Data Management at Onconova Therapeutics. In the past 5 years, Patrick’s team was responsible for organization and presentation of data leading to development partnerships in Pan Asia and Europe, a successful IPO, as well as the execution of several clinical studies.

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Vipul Kashyap, Ph.D., Head, Product Strategy and Management, MaxisIT

Vipul Kashyap, Ph.D., Head, Product Strategy and Management, MaxisIT
Vipul Kashyap, Ph.D., leads Product Strategy and Management at Maxis IT responsible for the design and development of data integration and analytics products targeted at Pharma, Life Science organizations and CROs – to help them monetize their data assets by enabling value added functions such as clinical research and translational medicine. He is a seasoned professional with more than 20 years of experience in information management, analytics, and healthcare and deep knowledge of the healthcare ecosystem – especially with a deep background in both Provider and Payer contexts. Vipul has worked at prestigious providers such as NYU Langone and Partners Healthcare and a leading payer – Cigna Healthcare. He was actively in the Healthcare and Life Sciences Interest Group at W3C where he collaborated with various Pharma organizations on re-using EMR Data for Clinical Trials Prior to working in healthcare and life sciences, Vipul has worked at prestigious R&D organizations such as Bellcore/Telcordia and Micro-electronics and Computer Technology Corporation (MCC); and has a Ph.D. in Computer Science from Rutgers University. He has published three books on Semantics in Information Brokering and Integration; authored more than 50 articles in prestigious conferences and journals; and presented keynotes at prestigious conferences and workshops and currently serves on the editorial boards of three journals.

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Who Should Attend?

Business users in the functional areas of:

  • Clinical Operations
  • Data Management
  • Standards
  • Biostatistics
  • Analytics
  • Reporting

from pharmaceutical, biotechnology, medical device companies, healthcare organizations, and CROs

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MaxisIT is a premier provider of a true cloud-based integrated Platform solution and functional outsourcing services, which are focused on the entire end-to-end life cycle of Clinical Trials and healthcare delivery. Our purpose is to improve how Pharmaceutical and life sciences companies and academia leverage information and make decisions in support of clinical research and development. Our technology platform optimizes the information flow across the entire clinical value stream, from the technologies, processes, and departments to external CROs, vendors and partners. This facilitated integration across the ecosystem offers huge time & cost savings with in-time decision support for potential risks and opportunities.

From its inception in 2003, MaxisIT® has quickly grown into a completely integrated platform that is available as an enterprise cloud, software as a service, and also via our Global Clinical Services Umbrella. The Global Clinical Services Umbrella delivers both clinical functional and software expertise under one seamless, distributed framework leveraging software-driven delivery processes.

MaxisIT® leverages a rich worldwide alliance partner network to provide our customers with a lean, agile delivery model that minimizes project timelines and cost, via more efficient processes. The MaxisIT’s Collaborative Partner Network is comprised of and also welcomes contract research organizations (CROs) of all sizes, consulting companies, technology providers and clinical operations groups that share MaxisIT’s vision of collaborative growth.

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