The pharmaceutical data challenge
Science is the process of generating knowledge from existing data and information; so harnessing the potential of their ‘big data’ is the natural next step for pharmaceutical scientists.
It’s good timing too. The pharmaceutical industry is facing a difficult time, with fewer successful drug launches and expiring patents. According to one report, the average cost of developing a new drug is $4bn over 12 years – with only 1 in every 10,000 experimental compounds making it to market.
Tougher regulatory requirements and increased competition add to the pressure, meaning good decision-making with reliable data analysis is more important than ever.
Pharmaceutical use cases
Bringing a drug to market relies on the identification of connections – between a chemical and an effect, agent and a disease or a drug and a market opportunity. Once these connections have been identified, pharmaceutical companies can find a way to exploit them.
As research volume and data availability grows, these connections have become more abundant, but also more difficult to detect – buried inside meaningless and ‘noisy’ raw data.
Applying network 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.
This is a heavily data-driven process, often with hundreds of research groups working on projects simultaneously. The ability to visualize the connection between research and results can help avoid effort duplication, identify gaps in understanding and generally ensure discovery is more cost efficient.
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.
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.
Pharmaceutical data silos
Successful drug discovery and trialing requires excellent data management.
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.
This leads to:
- Poorer resourcing decisions – decisions taken without 360-degree situational awareness are unlikely to be optimal.
- Duplication of effort – with no central unified knowledge base for disparate teams, effort is bound to overlap.
- Clinical trial wastage – drugs should only be taken to expensive clinical trials if they meet viability criteria based on full knowledge of the data.
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.
Why choose us?
At Cambridge Intelligence, we build graph visualization technologies that make it easy to understand complex networks of information. Using our toolkits, sophisticated graph visualization capability can be easily integrated into existing software tools and platforms.
For more information about how we help solve your healthcare and pharmaceutical data challenges, get in touch or request a free trial.
Graph visualization use case posts from our blog:
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With KeyLines, exploiting geospatial information has never been easier. This blog post describes three compelling use cases to help you get the most out of connected data on maps.
In this blog post, we’ll see how Become Education use graph visualization, powered by KeyLines, to equip children with the skills and knowledge to design their own lives.