Educating for the Future
Methodologies and technologies utilised in the clinical development process have been largely unchanged since 2005. Externally, there have been immense advancements in technology and mindsets related to working with data that have had little impact in our industry. This Working Group sees this as a risk. The risks breakdown into 3 categories:
1) There is a risk of advancement happening outside of our domain that may expose us to threats that we are unable to protect ourselves against.
2) There is a risk that our skill sets and capabilities become outdated and external forces strongly influence the Industry without us having a say
3) There is a risk that we are missing opportunities to become more efficient and to use these advancements to deliver better value for patients
The goal of this Working Group is to develop frameworks by which to educate the PhUSE community at large. The frameworks will be designed to educate the community on the importance of topics where we feel we have gaps, the details of the topics themselves, and how they can be used to drive innovation in the industry.
Research materials produced by this Working Group will be published on Squarespace
We have now established 3 sub teams:
Hue efficiencies have been made in BioPharma companies over the last few decades however, the sector is increasingly competing on the basis of their analytical capabilities which requires a centralised, combined, and, as much as possible, automated data environment to support these deeper insights. This project will explore how established Data Engineering techniques, successfully deployed in other industries, could be utilised in our industry. From traditional data warehousing; to the arrival of the big data lake; with data marketplaces; ePRO and IoT; the challenge is on – to identify analytical value from all of these disparate data sources.
Design Thinking is a process that promises to help tackle big ideas in a manageable and structured way. By definition, it is 'a formal method for practical, creative resolution of problems and creation of solutions'. Design thinking methods foster a way of thinking that reframes the problems and solutions we assume we have the answer to. this project would focus on identifying and collating resources in Design Thinking for consumption by the PhUSE community. Because the actual content is not house by the PhUSE project, this can include resources in many media formats, including, but not limited to: Books, Journal Articles, Podcasts, Webpages, Recordings etc. This will be achieved by curating and organising content into an easy-to-use structure and making it readily available and navigable technology.
According to Google Trends, the word “Data Science” is currently at a peak interest for worldwide searches. Companies like Uber or Amazon have built entire business models using data science methodology. The healthcare sector has also seen new players especially in consumer devices, which increased healthy lifestyles applying advanced analytics methods. Digital medicine out performs already traditional medicine in terms of yearly growth.
The pharmaceutical industry is also adapting to these new technologies. For example, FDA approved or cleared devices (eg. activity trackers, etc.) are used mainly for exploratory purposes in clinical trials and create huge volumes of data. We can create valuable insights when we connect these new data sources to clinical data and apply Data Science methods like Machine Learning, Deep Learning or Artificial Intelligence.
This project will support people to familiarise themselves with Data Science and all its various branches. We will provide a Data Science training repository, where we will consolidate available training materials around topics like Machine Learning, Artificial Intelligence, Deep Learning, Quantitative and Advanced Analytics. We will also provide use cases of Data Science in the healthcare sector and we will also look into other industries. A learning path for members of our industry will be provided to dive deeper into the topic of Data Science to educate the future.