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    • Pharma and Life Science
    Editor's Pick (1 - 4 of 8)
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    The 4Ps of Digital Transformation in Pharmaceutical Industry

    Debraj Dasgupta, Operating Officer, Head of Strategy and Go-To-Market Planning Division, Nippon Boehringer Ingelheim

    Cloud Computing: Pharma Takes the Plunge

    Andy Newsom, SVP & CIO, CSL Behring

    Machine Learning & Artificial Intelligence in Healthcare Industry

    James Woo, CIO, The Farrer Park Company

    Connected Patients: Healthcare and the Internet of Things

    Geoff Feakes, Group CIO, Tunstall Healthcare Group

    Building a Quality-Focused IT Foundation for a Biopharmaceutical Enterprise

    Andy Newsom, SVP, CIO, CSL Behring

    Points of Focus for CIOs to Succeed in the Next Decade and Beyond

    Dr. Joseph Frassica, CMIO/CTO, Patient Care and Monitoring Solutions, Philips Healthcare

    Innovating Technology -Based Metadata Solutions for Improved Data Analysis

    Douglas Barta, CIO, PAREXEL International

    Real-Time Actionable Intelligence with a Solid Analytics Platform

    Rajeev Nair,

    right

    Life Sciences: Macro View

    By Rajeev Nair, CTO, J. Knipper & Company

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    Rajeev Nair, CTO, J. Knipper & Company

    In Pharma, as R&D budgets come under heavy pressure, industry continues to be fraught with M&A aimed at product and patent acquisition. So integration continues to be a key concern to gain efficiencies and develop a single, unified compliance and regulatory layer; however, gone are the days where you could afford a multi-year rigid, monolithic ERP rollout; not just because of prohibitive costs, but also time for value recognition.

    Healthcare market is going through rapid changes given new regulations—so pharma companies are extremely hungry for market intelligence—product efficacy, patient compliance, market penetration and reimbursement related-Analytics, not just the ability to integrate internal operational and sales data with market data, both structured and unstructured, but also be able to generate predictive behaviors becomes key. This means that the life sciences industry cannot afford to rely on single platforms or solution (providers) to meet the changing market needs. The need to seamlessly partner with various providers, both established and disruptive, who have USPs in niche areas becomes key.

    Technology Implications: Need a New Model

    The above macro factors point to a key technology theme – agility

    • M&A - Agility to integrate up and down the value chain and with new acquired entities.

    • Analytics - Agility to partner with external data providers and integrate with internal operational data.

    • Changing Market needs - Agility to build flexible integration points that allow the enterprise to quickly partner with upcoming and disruptive service providers for niche needs.

    The traditional landscape that is riddled with monolithic applications like traditional ERP, CRM, BI systems don’t allow the flexibility and agility that today’s needs demand. Configurable services with flexible integration points become important as instantaneous integration becomes critical; in addition, for a service provider who provides end to end solutions like JKC, the ability to provide a platform where clients could pick and choose specific elements of the service portfolio to be integrated with their operations.

    However, at the same time, traditional values don’t go away—predictability, compliance needs, efficiency etc. These needs almost seem like the antithesis of agility and flexibility.

    More flexible and agile architectures that have faster integration platforms and configurable services become vital to survive and excel in this landscape—an example is micro-services architecture. In a micro-services architecture, software applications are developed as a suite of small, independently deployable modular services, in which each service serves a unique purpose and communicates through a clearly defined, light weight mechanism. Such an architecture has several advantages:

    • Agility breeds scalability—a highly popular, in demand service can be deployed in multiple, more powerful servers to meet an increased need. This works really well with both in-house and IaaS and PaaS (cloud) landscapes where metered boosting of performance at a service level will be possible. Hard to achieve that through traditional IT deployment models.

    • Agility enables technology/platform agnosticism: Ability to choose specific technology for each service—this becomes vital while responding to specific providers in the market driving technology platform decisions.

    • Agility enables compliance—since each service serves a unique purpose and can be changed independent of each other, testing becomes easier due to higher predictability, and it drives compliance costs lower.

    • Agility breeds predictability and reduces risk: Contrary to large monolithic applications, since each service exists independent of each other, the potential of failure of one service doesn’t impact any others.

    • Agility enables quick integration, thus faster results: Loosely defined, light weight integration allows faster integration with the in-house organization’s and its providers’ and customers’ applications—this provides the agility an organization needs to have to respond to changing market needs.

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    Life Sciences

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    Top 10 Pharma and Life Science Technology Companies - 2020

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