March 26, 2024 | Author: Dr. Nicole Mather and Seema Raman
Classification: Healthcare
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Life science research and development is complex. Complex tasks are performed in an environment of big data, specialized technologies, and regulated processes. These complex risk challenges make processes and interactions repetitive, time-consuming, and costly. To accelerate innovation in developing safe and effective treatments, life sciences organizations must overcome these challenges and move faster. The field of design thinking can help bring about a major change in approach, accelerate the process behind innovation of new treatments, and significantly reduce time to market.
When access to complex analytical tools is provided in a user-friendly manner and the data access experience is improved (see ChatGPT), the speed of ingestion increases dramatically. ChatGPT reached 100 million users in just two months, redefining the benchmark for digital adoption. It’s difficult to provide an analytics service that is as easy to use as this, but we believe that a focus on accessibility is critical to extracting value from all types of data and processes.
Design thinking is a problem-solving method that puts human needs and experiences at the center of the design process. It is an approach used to tackle complex problems and generate user-centered and empathetic solutions faster. A growing number of life science organizations are turning to design thinking as a way to create end-to-end digital experiences that better meet the professional needs of scientists and researchers working with data.Collaborate with users to design and give them the last word, This is a powerful tactic to ensure that your solution fits your business processes and exceeds your expectations.
Design thinking enables digital transformation and improves the experience of users’ daily activities. This allows co-creation to unleash creativity and bridge the gap between the worlds of art and science. By taking a user-driven approach, we can uncover scientists’ goals and understand current processes and challenges. This helps identify the data needed to support goals and design solutions and intelligent workflows that harmoniously enhance scientists’ analysis-based activities and decision-making.
design thinking approach
We work at the intersection of strategy, creativity and technology to help clients digitally reinvent their businesses. We have a proven track record of successfully addressing complex challenges by delivering innovative, research-driven solutions that reimagine how design is done in most industries, including life sciences.
To integrate user-centered design and technology development, we created an approach called IBM Garage. Our team has been at the forefront of connecting IBM design thinking with science and research. This enables a user-centric data and technology transformation that puts scientists at the center of every solution.
While design thinking can be a new experience for some clients, our expertise in the life sciences industry allows us to apply this approach to scientific stakeholders in a way that delivers value faster than many clients expect. It is now possible to Our extensive industry experience enables you to effectively transform and prioritize clinical requirements and workflows, reimagine experiences, and improve scientific outcomes. Designing and deploying new approaches at such a pace is an empowering and energizing experience.
Some stories of design thinking in life sciences:
genomics organization
IBM was engaged as a delivery partner to help design and build an innovative new portal to support cancer diagnosis.
We mobilized a collaborative team with experience in science and genomics, design thinking, user-centered design, software development, and agile delivery methodologies, including the AWS Cloud. The client team brought deep expertise and insight into genomic data analysis and interpretation, bioinformatics, day-to-day processes, and even complex program delivery.
Over 16 months, the team co-designed and built an innovative system capable of whole-genome sequencing. The system provides a superior clinical user experience, accelerates cancer diagnosis, and is based on a modern, secure and flexible model for the future.
Our overall approach and architecture aligns with three fundamental principles:
- Value-based: All recommended solutions are tied to user benefits
- User experience: Technology that helps clinical scientists make faster diagnoses
- Secure: An open cloud platform that prioritizes data security, governance as code, and resiliency.
This resulted in a solution with a user-friendly front-end design, consolidating five clinical screens into one, reducing cognitive load and allowing users to focus on clinical decision-making. Together with APIs that support data filtering and aggregation, we now have a high-performance approach to displaying data based on the AWS cloud platform.
‘This is an excellent example of how a mixed team can work together to elegantly and quickly solve user needs and deliver them to colleagues in the clinical setting, continuously improving patient care and laboratory efficiency. It will have a positive impact. ”. Deputy Chief Medical Officer
The above is an example of work on Clinical Variant interpretation for cancer diagnosis.
Trusted by a major foundation
This major teaching hospital is at the forefront of genomic medicine delivery in the UK. Following the success of his PoC, developed through a user-centered design methodology and close collaboration with clinicians and researchers, the MVP release of this new digital genomics management service will accelerate treatments for more than 5 million people.
The platform enables clinicians to manage genomic patient records and build a foundation for data science and machine learning to accelerate multidisciplinary reviews of patients and diagnose patients faster. . The team made an innovative development that reduces clinical risk by allowing clinicians to learn from patients with similar medical histories, accelerating searches for similar records from weeks to seconds. A clear roadmap has also been developed to move from a paper-based system to a fully digital platform that leverages machine learning to deliver actionable clinical insights and results.
clinical team
We have worked on two projects with major clinical departments. Both projects incorporate design thinking practices to improve business and user outcomes. We employ service design to fundamentally reimagine Future State’s employee and clinical trial volunteer experience to improve recruitment efforts to efficiently attract, recruit, and retain the right volunteers for Phase 1 clinical trials. more effectively. The result is a future-state blueprint, supported by a value-driven roadmap, for the department’s digital transformation to deliver a newly designed end-to-end clinical trial volunteer and employee experience: provided the model.
We then moved on to our first milestone: a modern clinical trial volunteer website. To achieve an engaging first volunteer touchpoint, IBM provided:
- Design directed volunteer journeys built on design patterns with complementary business capabilities
- Building trust and engaging content with a new website
- Website functionality has been enhanced to allow volunteers to more actively apply for clinical trials
Through effective user research and design, the team was able to make the difficult clinical trial experience more accessible to volunteer candidates and accelerate recruitment efforts.
Examples of user personas for clinical trial recruitment
sample management
We helped deliver an enterprise sample management solution for a major biopharmaceutical company. We introduce user-centered design to understand our clients’ problems and challenges, and provide a comprehensive, end-to-end biological sample lifespan that enables seamless movement of both clinical and non-clinical samples. We were able to design and support the implementation of a cycle tracking system. – Clinical samples between research units and logistics hubs. Overcoming complex issues in sample and data consent, we worked with researchers to map current sample transfer processes and create a vision for the future.
We are an important partner for implementing new sample biobank facilities. A fully operational sample repository for storage, management, and histological processing of all samples will be required in 2024. By leveraging IBM Garage tools, we identified scientific business requirements and translated them into technical requirements. Supporting innovation and growth for technology and data-driven organizations.
Example future service blueprint and end-to-end journey map for sample transfer and tracking
summary
A user-centric approach is essential for life sciences organizations to become more agile and globally competitive. Design and create solutions that meet the specific high-value, high-priority needs of scientists and researchers, including visualizing complex data, automating and implementing intelligent workflows, and applying strategic approaches to data insights. By doing so, organizations can realize significant benefits. Applying this approach can accelerate research and clinical trials, optimize and accelerate pharmaceutical processes, personalize patient engagement, and provide clinicians with a fundamentally improved data portal. Life sciences organizations have a significant opportunity to unleash their scientists and creativity and accelerate their operations by combining design and digital transformation.
Acknowledgment
The authors would like to thank the team for their significant contributions to this paper. his Karishma Govind, Director of Service Design; Ravi Benitez, Senior Services Designer. Catherine Heylings, Life Sciences Experience Consultant. Emily Ginn, Agile Delivery Business Analyst, Life Science. Chaya Shah, HLS Intern.
