Data Connectivity and Collaboration in Life Sciences and Healthcare Supply Chain

I’ve just sent a prescription to your local pharmacy. Let’s follow up in a week, and your app will remind you.” “Thank you, Doctor Williams,” says John, who just used the app to get a virtual medical consultation without having to leave his living room. No waiting time, no co-pay. This is now a common example of healthcare consumerism, one of the industry forces that are profoundly changing the landscape.

Through healthcare consumerism, access to healthcare is becoming more like an eCommerce shopping experience. According to the 2017 McKinsey Consumer Health Insight Survey, more than 70% of the respondents said digital solutions are preferred for maintaining health, selecting a provider, and even receiving care. That’s why companies like Merck KGaA (unaffiliated with Merck & Co.) have been automating its demand planning using Artificial Intelligence (AI) since 2017.

When the demand planning is automated, you must wonder about the supply side as well. Making sure products get to patients via various channels is equally critical. When I recently spoke to a handful of life sciences and healthcare executives in the San Francisco area, the common theme was that the industry still has too many siloes of data.

For example, the primary ways of selecting and qualifying temperature-controlled packaging (TCP) and setting up and running logistics have not made any significant technological advancement over the last two decades.

Yes, maybe some incremental improvements were made here and there, and some credits are due to profound industry efforts on regulatory compliance issues. However, eventuallynot being able to automate things on the supply side will catch up with us to cause even more issues down the road. Imagine when personalized medicines become more like the 23andMe process. How will we ensure the absolute accuracy, flexibility, and compliance at each patient delivery level?

I believe that at least we should start with three essential data types that the industry needs to start breaking down the siloes on: time, temperature, and physical handling. What if these data types freely and securely flow among life sciences and healthcare manufacturers, 3PLs, temperature-controlled packaging, data logger and IoT, and IT platform companies? Here are a couple of actual positive examples of how such broken siloes can benefit the industry. One example is that based on the thermal energy left inside of the TCP depending on ambient conditions, the system knows how many hours left to go in real-time, and with deep integration with a 3PL, it intelligently initiates contingency actions without depending on human reactions. Another exciting example is with a CAPA (Corrective and Preventive Action) management that gets raised automatically based on predetermined criteria with automated process management and control instead of relying solely on individual parties’ subsequent actions.

Although there are some naysayers, the market is big enough for everyone, and the benefits of connectivity far weigh the potential concerns about perceived proprietary knowledge. Indeed, it is about time for the collective will of like-minded leaders to make the movement, which I gladly invite you to.