Data Analytics

Pharmaceutical and life sciences organizations rely greatly on data to drive decisions on product planning and positioning. Historically, this data has been largely fragmented and distributed across various data sources such as hospital data records, physician notes, clinical trials systems, sales and marketing databases, claims data, research data, and more. With advances in technology, pharmaceutical and life sciences organizations are now able to tap into different types of data – machine data from servers, social data from Facebook and Twitter, clickstream data from websites, voice logs from call centers, communication data from e-mails, data generated from sensors and IoT(e.g. wearable devices), and more.

“Boundaryless” information

Data from all the traditional and new-age sources need to be integrated in a seamless way in a “boundaryless” data platform to build advanced data analytics solutions. Such solutions can be leveraged to generate powerful insights to enable informed and insight-driven decisions. Effectively leveraging data harnessed from multiple structured and unstructured sources through “boundaryless” information platform and building data science driven predictive and prescriptive analytics will enable life sciences organizations to effectively respond to challenges and convert them into opportunities to drive competitive advantage.
Analytics

Analytics enables data exploration, analysis, and data science driven predictive and prescriptive analytics solutions which help in responding to the following key trends in the pharmaceutical industry:
Drug discovery analytics – Enables scientists to source scientific findings and insights from external labs or internal knowledge to jump start discovery which will in turn help reduce cycle time for product development aiding faster go-to-market
Reduce cycle-times for clinical trials – Through better insights driven by improved accuracy of analytics
Supply disruptions predictive analytics – Building predictive models using a combination of internal and external data would help reduce unforeseen shortages in availability of drugs impacting customer service levels and lost sales revenues
Product failure analytics – Via root cause analysis and predictive analysis of product failures (vendor data)
Risk analytics – For evaluation of potential risks posed by elemental impurities in a formulated drug product
Real-time medical device analytics and visualizations – Leveraging Interconnecting data from implanted devices and personal care devices
Digital channel analytics / social analytics – To more fully understand customer perceptions about their products which helps in proactively fixing product issues or managing communication better
Enhance reporting systems – To meet the changing regulatory compliance needs more effectively
Visualization – Renew focus on understanding the underlying business data and generating analytical insights using latest business intelligence (BI) visualization tools

Pharmaceutical organizations can leverage big data and analytics in a big way to drive insightful decisions on all aspects of their business from product planning, design, manufacturing to clinical trials to enhance collaboration in the ecosystem, information sharing, process efficiency, cost optimization and drive competitive advantage. At Hephzibah Technologies, we focus on delivering business value through insights and predictive models as well as driving efficiencies in data investments through consolidation, integration, enhancing, enriching and monetization of data.

 

 

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zahera

Zahera

(HR)

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Alex

Alex

(CEO)

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Alex

Sara

(CCO)

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Mark

Mark

(Manager)

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