In the past decade, data in life sciences has become more complex, more diverse and more abundant. Information and data are playing a critical role within Life Sciences businesses, and they are one of the biggest factors for trends and challenges within science and healthcare. While this presents new challenges for scientists, there are also opportunities to unlock the potential of data in this sector. In this blog, we outline five keys to unlocking this potential as well as the benefits of data.
Data-driven science and discovery:
Data-driven science has the potential to help scientists find new treatments and cures. It can also help them find ways to prevent disease, as well as treat it. Data is a powerful tool that can transform our understanding of biology and help us unlock the mysteries of science.
Data can be used to make new discoveries, test hypotheses, make predictions and models and draw inferences. It can also be used to make conclusions about the data that is collected. In Life Sciences, this is particularly useful for pharmacogenomics researchers who are looking for a way to help patients receive more effective treatment without side effects.
The World Health Organisation reported that an estimated 237 million medication errors are estimated to occur each year in England alone, costing the NHS around £98 million and an estimated 1,700 lives —and many of these mistakes were caused by human error rather than faulty products or machinery. When patients take too much medication or don’t receive the right amount of medication at all, due to incorrect dosage instructions on their prescriptions, it can result in serious health complications.
1. Understanding the health care landscape:
The Life Sciences industry is rapidly changing, and as we know, data is playing a critical role in that change. To understand how your organisation can thrive in this new environment, you need to have a clear vision of what health care looks like today. What are the key challenges? What are the opportunities? How can companies get ahead by providing better solutions than their competitors? And what is driving these changes?
2. Build strong foundations:
It’s crucial to get the basics right and to have a good strategy. You should figure out your objectives and start from there. Understanding the industry and filling gaps in your knowledge is vital.
3. Translating big data into actionable insights:
Once you've identified your key challenges and opportunities, it's time to take advantage of big data analytics, so you can make better decisions about how best to address them. This involves creating models based on historical data sets as well as looking at current situations through new lenses.
Despite the importance and value of data, accessing data can be difficult and expensive. Furthermore, accessing data from other sources can help you unlock a lot of value from your company's assets and help you grow as a business. However, there are some legal agreements and privacy concerns that must be taken into consideration when looking at how much access you can actually get. Making sure that your systems are up-to-date is also important, so that they don't hinder your ability to use them effectively in the future or cause any problems with security breaches or other issues caused by outdated software programs
The benefits of using data in Life Science businesses:
- The complexity and volume of data in Life Sciences is creating new challenges, but there are solutions.
- Data can improve the quality of life for patients and their families.
- Data can improve the efficiency of healthcare delivery, which can reduce costs while improving patient outcomes.
- Data can be used to solve complex problems, like how to deliver cancer treatment more effectively, or how to predict which medications will work best for each patient on an individual level.
The Life Sciences industry is in a state of transformation. The complexity and volume of data is creating new challenges for scientists, but there are solutions. This means learning how to think about data as an integrated part of scientific research where results can be validated through replication and reproducibility tests.
Are you taking full advantage of your Data? What’s developments are most interesting to you? Let us know:)
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