Life science analytics

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Life Science Analytics

 

Globally the pharmaceutical industry is being challenged by pressure to be more cost efficient, patient centric and improve the services and products on offer. And in this scenario, the life science analytics act as an enabler for the industry by allowing the healthcare companies to overcome these challenges. The pharmaceutical industry is evolving and with more healthcare analytics startups coming up, the industry is shifting to value-based medicine based upon strong real world evidence for consumers, regulators and healthcare providers to drive better patient outcomes.

The life science analytics helps the life sciences and pharmaceutical organizations to derive decisions on the product positioning and planning. Historically, this data which the companies deal with used to be highly fragmented and divided across the sources such as physician notes, clinical trials systems, hospital data records, research data and other sources.

These imperatives offer immense opportunities towards creating better solutions for the healthcare analytics startups in addressing key areas of focus of the healthcare industry. These key areas include:

  • Enhanced overall patient experience
  • Enhanced risk management capabilities to increase predictability of the product success.
  • Reduced time cycles for product development.

These startups raised more money in H1 2014 than the previous 12 quarter combined together. The new age healthcare analytics startups like DCube provide pharmaceutical solutions which enables data exploration, analysis, and data science driven predictive aided with prescriptive analytics solutions which help in responding to the key trends in the healthcare industry. The key trends in the pharmaceutical industries are:

  • Visualization: The usage of latest business intelligence (BI) visualization tools can help the pharmaceutical companies to renew focus on understanding the importance that underlies with the generation of analytical insights into healthcare big data.
  • Supply disruptions predictive analytics: Following a combination of internal and external data to build a predictive model would help the organizations reduce the unexpected shortage in the availability and supply of important drugs that may negatively influence the customer satisfaction quality and might lead to reduced revenues.
  • Drug discovery analytics: The use of DCube analytical solutions help ease the hectic nature of carrying out operations. The solutions enable the scientists to gain insights from external labs and internal knowledge resources which significantly reduce the time cycle required for product development.
  • Social Analytics: These pharmaceutical analytical solutions help the organizations fully understand the perception of the consumers towards the products so that product issues are proactively fixed and communications are managed better.

This evolution in data management is transforming clinical research and moving the healthcare industry closer towards precision medicine. This evolution can be witnessed in the advanced analytics conference where we can witness the peers from across the healthcare industry, who are successfully implementing advanced analytics to accelerate pharmaceutical research and development.

The life science analytics helps the companies go beyond the customary approaches to the data. It is expected that the organizations which adopt the usage of analytical solutions to cope and build upon the velocity of real-time structured and unstructured data i n different formats will be able to outperform the competition by 20 percent in every financial metric.

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