Graph visualization for pharmaceuticals

Making sense of big pharmaceutical datasets with graph visualization

The pharmaceutical data challenge

Science is the process of generating knowledge from data and information; so harnessing data visualization is a natural step for pharmaceutical scientists.

It’s good timing too. With tougher regulation and increased competition, good data analysis is more important than ever.

Applying network visualization, also known as graph visualization, and analysis techniques can help to cut through that noise to reveal the connections and patterns you need to see. Let’s look at some examples in the pharma industry.

visualizing patent data as a network
Visualizing data from the US Patent office as a network

Drug discovery

Bringing a drug to market involves understanding connections – between a chemical and effect, agent and disease, or a drug and a market opportunity. Once connections have been identified, companies can find a way to exploit them.

As research volume grows, so too has the volumes of data. Being able to detect and understand connections buried in ‘noisy’ raw data is essential.

Network visualization makes it faster and easier to identify those connections, revealing patterns, correlations, gaps and anomalies, and making discovery processes generally more cost efficient.

Competitor analysis and market landscaping

The pharmaceutical industry is competitive, with thousands of patents registered each year. Understanding competitors, their intellectual property and product pipeline is essential for making the right product decisions. Network visualization can make this complex data, and how it all connects together, simple to understand.

Confirming there’s a market for your product is equally important. Network visualization can help see how patient data, health records, drugs advisories and other external data may affect your sales forecasts.

A KeyLines visualization of the connections between organizations and patents
A visualization of the connections between organizations and patents.

Clinical Trials

For drugs that make it this far, ensuring a conclusive trial is key. Network visualization techniques can help find potential participants with the correct profile, analyze trial results and ensure overall vigilance.

Enterprise knowledge graphs

Pharmaceuticals is a data heavy industry.

Teams, often dispersed across multiple groups in different sites across several countries, require fast and easy access to the right data at the right time. This requires integrated data management systems, unhindered by data siloing between teams.

The ability to visualize the connection between research and results can help avoid effort duplication, identify gaps in understanding and generally ensure better decisions.

Combining data silos with network visualization

Using network visualization software to combine data silos in this way can help pharmaceutical companies make their data:

  • Informative – displaying data within a wider context
  • Accessible – complex data is made available in an easy to digest format
  • Timely – insight can be delivered without the need of IT support each time
  • Actionable – users can interact with the data and make it more valuable with analytical methods

What is network visualization?

Our white paper introduces the topic of network visualization with one of our toolkits.

Download the White Paper

Why choose us?

At Cambridge Intelligence, we build network visualization technologies used by organizations, like GlaxoSmithKline, Shire, Amgen and Biogen, to make sense of complex connected data.

For more information about how we help, get in touch or request a free trial of our software.

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