Those initial few weeks when starting a new project create a unique opportunity to capture definitions of what it is you are doing before you are too familiar with the acronyms, industry nomenclature or just the general concepts. To that end, here’s my definition of my new field of product management: “Clinical Research Informatics”.
I think that the best way to understand this is to break it down into “Clinical Research” and then “Informatics” before reassembling them.
When a company wants to bring a new drug, or a clinical device, to market they need to go through an approval process in those countries that they’d like to market the end product. At an incredibly high-level this process involves designing the product, testing it in a lab, testing it on healthy humans and then testing it on people who have the disease. This process takes years and can cost in excess of $1B (yes, that’s a B). During all of these stages, you are collecting data about the effectiveness and safety of the product. Towards the end of the process you ask the local regulatory organization for permission to take the product to market. This process of testing the product prior to sale is called “Clinical Research”. It’s a lot more nuanced than this but you get the general idea.
Informatics is a branch of computer science focused on “the interaction between humans and information alongside the construction of interfaces, organizations, technologies and systems”. In other words, how people, organizations and systems use data and more specifically, how they can make better use of that data. To be honest, it was not a term that I was familiar with prior to starting this new role but the concepts are close to the analytics and data collection disciplines that you might be familiar with.
When you bring these two concepts together you get Clinical Research Informatics which focuses on how to use data, technology, analytics, processes, and people to more efficiently and safely bring products to market.
To better understand this, imagine that you were the first company to ever bring a new drug to market. You’d have no way of knowing who has the condition that you are treating, you would not know which facilities or doctors would help with the research, no expectation of the potential bottlenecks in the process, no ability to predict the expected outcome, etc. You’d be flying blind and working from scratch at every stage of the process.
Of course, this is not the case: ClinicalTrials.gov “currently lists 210,485 studies with locations in all 50 States and in 192 countries” In fact, Covance’s own investigator knowledge-base includes data from more than 14 million patient visits. Making use of this data to more effectively, and safely, bring drugs to market can reduce the time it takes to get drugs to patients.
Why is this important?
Frankly, it’s important because it saves lives. Understanding the risks involved in the clinical research stage means that the trials themselves are likely to be safer and to capture more of the potential risks in the use of the treatment but more importantly, it gets drugs and devices to patients more rapidly which saves lives.