Informatics
Experience for Life Sciences (UXLS) initiative aims to communicate the value of UX in life science R&D. Using shared knowledge and best practice, the project partners are also developing a UX toolkit with R&D-specific case studies, methods and business metrics.
Nurturing the UX network in the life sciences A workshop (Figure 8) helped forge this new com- munity by exploring and articulating the shared challenges of UX practice in life science R&D. “It’s exciting to get to know so many UX profes- sionals and practitioners from many different phar- ma companies and vendors,” says Pat Keller, Global Head of User Experience at Novartis, NIBR Informatics. “Face-to-face meetings mean we can work together to create a better place for UX in life science. Everybody is passionate, everybody wants to improve the industry, and that’s what gives this group momentum, inspiration and motivation to achieve its goals.”
Through this new professional peer network, there is an opportunity to establish thought leader- ship in the area of UX in life science R&D and to influence senior decision makers. A follow-up workshop at EMBL-EBI in June 2017 will include R&D IT senior vice-presidents and directors from leading pharmaceutical R&D companies.
Providing a UX toolkit for life science R&D Each project team member, co-ordinated by a PA project manager, is working on a pro bono basis to deliver the free online UX toolkit, positioned to help improve the quality and usability of scientific software. By sharing their deep knowledge of UX, gained in the field of life science R&D, they will help others foster UX best practices in their own companies.
The new toolkit will benefit organisations with a UX team of one, and those with much larger UX departments. In the project’s next phase, partners will develop UX metrics to help users measure and communicate the impact of their work. There are two main benefits of this toolkit:
1. It supports cultural change in research organisa- tions where UX design is undervalued. 2. It provides practical support, helping UX (non- science domain expert) professionals understand how research scientists work, so they can help cre- ate better digital experiences.
The toolkit is targeted at UX practitioners, busi- ness analysts, software developers and managers of technical delivery teams. The first full release is scheduled for Q4 2017. To register your interest see:
http://www.pistoiaalliance.org/projects/uxls/.
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Dr Jennifer A. Cham is Lead Experience Analyst at EMBL-EBI. She has an engineering doctorate in bioinformatics from Cranfield University UK, and has previously worked in product development in pharmaceutical R&D at Merck KGaA and GSK. Jenny is interested in UX strategy and design lead- ership, especially in complex data domains.
Katrina Costa is Senior Scientific Engagement Officer at EMBL-EBI. She has an MA (Oxon) in Biology and an MSc in Science Communication from Imperial College, and has previously worked at the BBSRC. Katrina is interested in translating science to a wide audience and has helped facilitate UX research.
Drug Discovery World Summer 2017
The Pistoia Alliance: new UX opportunities in R&D There are clear opportunities for pre-competitive UX projects in life science R&D, for example improving the UX of clinical trials, where many companies suffer the effects of poor patient engagement. UX mapping from both the patient and caregiver perspectives could help to reduce attrition rates and improve patient compliance. UX research and design could also greatly improve product development in a range of R&D settings, including patient consent solutions and ‘laborato- ries of the future’.36
Further Reading
Free online UX training module provided by EMBL-EBI
https://www.ebi.ac.uk/training/online/ course/user-experience-design.
Open Targets37 (
http://www.targetvalidation.org/) is a good illustration of a software solution designed for life science R&D using a user-centric approach38. It allows bench biologists and disease experts to execute complex queries on target and disease information in an intuitive way, without the need of expert computational biologists, thus saving costs and increasing efficiency.
DDW
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