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Cross-functional Perspectives Are Crucial For Risk Assessment
Risk assessment must go beyond the concerns of operations or monitoring teams and span the entire organization – because the conversation is no longer just about monitoring. Read More
KRI Trending Graphs and Ending the Groundhog Day Loop
The famous quote “Those who fail to learn from history are doomed to repeat it” seems appropriate when describing the pharmaceutical industry, at least according to our track record over the last few decades. It often feels like Groundhog Day, and we are Bill Murray hitting the alarm clock before realizing “Oh, here we go again!” Read More
Get The Return You Need On Your mHealth Investment
You just decided to invest a significant portion of your innovation budget to power your clinical trial with new mobile health technology. Now what? Read More
Risk-based Monitoring: People, Process & Systems In Motion
Much like driving a car on new roads, you don’t necessarily know what is around the next bend, so you must constantly monitor your surroundings. Read More
Medical Coding Plays Vital Role In Clinical Trial Speed
Imagine that you are the director of clinical systems at a life science company. Your goal is to ensure that the clinical trial succeeds. Read More
Is Machine Learning the Next Big Thing in Healthcare? (Part 1)
What are the latest trends in machine learning and how will it impact healthcare in the near future? Read More
Pharma Is Long Due for a Disruption
Tech has already disrupted a number of industries such as music, books, retail, data storage, etc. Read More
Adaptive Designs Cut Costs and Improve Efficiency
The adoption rate of adaptive clinical trial designs will increase dramatically in the coming years. Read More
Hearables, Wristables and Eyewearables!
In Christian Stammel’s NYAS talk about wearable tech’s impact on the healthcare market, he gave an overview of the wearables market as well as his take on what’s coming next. Read More
Data Mining as a Path to Better Trial Design
The prospects of Big Data are tantalizing for the life sciences industry, but there’s still much left to do with small data. Read More
