How Can Life Sciences Industry Help In The Battle Against COVID-19?
Reflecting on these unprecedented times, the chances as a global community to fight the threat that COVID-19 poses to the way of life. All eyes are on the life sciences industry for helping to get life back to normal. In order to do that, life sciences companies will have to collaborate on a scale not imagined previously.
The industry has responded to the current coronavirus threat by marshaling resources and doing its work, such as discovering drugs, developing them, and getting them ready for the market. Several new products are now in the pipeline and being assessed for the impact.
Recent advancements are helping in the response. Previously it used to take two to five years to develop a vaccine. At present, rapid vaccine development technologies must help a vaccine to be ready in 12 months. And the industry can create a scale manufacturing capacity for one billion doses while assessing those doses for safety.
New and old technologies are being utilized to fight this coronavirus — including live-attenuated or inactivated vaccines, subunit vaccines, genetic vaccines, viral vector vaccines.
As the world recovers from COVID-19, the response to this pandemic has taught the world vital lessons about the intersection of data, science, and technology. Here the world has seen the importance of many things like:
• Collaborating through the ecosystem, with friends and competitors alike, on a scale unimagined until now. Government, industry, and universities are collaborating across national borders to further research.
• Bringing in more “big guns” depends on high-performance computing and artificial intelligence (AI) to augment the chance of discovery. US Department of Energy’s Oak Ridge National Laboratory has deployed the most powerful supercomputer, the IBM-built Summit, to fight against COVID-19. Researchers have been granted emergency computation time on Summit, using it to perform simulations with unprecedented speed. In just two days, Summit identified and studied 77 small-molecule drug potential compounds to combat COVID-19. That task, if using a traditional wet-lab approach, would typically have taken years.
• Capturing data and using it. While a cure is being developed, the immediate challenge is to reduce and eliminate the number of cases in our communities. There is an answer to this challenge, and it is data — or as has been highlighted in the media — data related to testing and monitoring.
Learning these lessons is crucial to tackling this terrible disease and defeating it. Applying them in the future will help prevent new pandemics from emerging and promote a healthier future.
What Role Does User Experience Play In Life Science Software?:
Analytical software for life sciences with poorly designed user interfaces can lead to unproductive research and can be very time-consuming, tedious, and frustrating. UX (user experience) design possesses great potential for scientific software that handles big data.
The best pharmaceutical companies wish for their scientists and data analysts to have the most effective tools possible. As an industry, life science is vast, and the industry collects and leverage vast amounts of data. The technologies behind these complex data are highly robust and getting smarter by the day.
It is sometimes easy to forget that the real users will have to handle this information. Interfaces and user experience act as the conduit between technologies and the user. A user-focused approach to understanding users’ needs leads to informed decision-making about what data must be shown and the best ways to display that information.
Understanding User Experience (UX)
Big data will be complicated as ever, but that doesn’t mean the user experience must be complex.
UX methodology is a collaborative and iterative process that debilitates innovation to solve a problem. UX design helps to maximize the user’s satisfaction when using a product. When creating software, it does not matter how powerful and robust the back-end system and the product data are, if rendered by an inaccessible and unintuitive, unengaging UX.
User Experience (UX) Principles for Life Science
Prioritize information- Crucial information should be at the top of the screen because this is where the user’s eyes are more likely to be drawn. This will give the user a quick overview.
Logical layout- Layout should be easy for the user to understand and follow — consistent formatting and design throughout the application. If the dashboard contains several tabs, each tab should have a similar format, styles, and layout.
Think through users’ mental models- With software applications, users expect a specific sequence of events. When dealing with big data sets, it is essential to align the software’s conceptual model with its mental model.
Oversimplify functionality- It is essential to show functionality clearly and not to hide any vital feature under drop-downs. When creating an interface, less is more.
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