How Connectivity Is Shaping the Future of Laboratory Medicine

Remember when flip phones were thought to be the height of technology? Then came smartphones; the world would never be the same. Now, the life sciences industry is having its own “smartphone revolution,” and labs and manufacturing facilities are undergoing massive upgrades to their ability to help bring life-altering medicines to market.

What’s the secret sauce? It’s the power of connectivity. The Internet of Things (IoT) and advanced data science (including AI) have synergized from shop floor to C-suite, and pharmaceutical R&D and production will, like telecommunications, never be the same.

Climbing the data mountain

Data in life sciences can be like that junk drawer in your kitchen. You know there’s good stuff in there, but can you find exactly what you need, when you need it? That’s tricky. You need a systematic approach to capturing, leveraging, and expanding the utility of that data before it starts to pay real dividends for your organization. You need a plan.

Enter the data science hierarchy of needs.

Let’s break it down:

1. Collect: This is where we gather all data. We need accurate info from every device, sensor, and system in sight. 
2. Move and store: This is all about secure transfer and storage, setting the stage for all advanced analytics.
3. Explore and exploit: Now we’re digging into data, spotting trends, and extracting insights to inform operational decisions. 
4. Learn and label: At this stage, we’re refining and categorizing data, getting it ready for predictive modeling.
5. Predict and prove: Here, algorithms predict future trends and keep us one step ahead of potential operational hiccups, directly impacting productivity and downtime.
6. AI and continuous learning: Welcome to the peak! Systems at this level are not just smart; they’re evolving through ongoing data collection and analysis cycles. Here, we don’t just respond to challenges, we preempt them.

Houston ... we have a problem

Not everyone is living in this data science utopia. Many labs are still struggling with outdated systems, unable to unlock the massive value of the data their facilities are generating. In these situations, data get trapped in silos, with lost opportunities for organization-wide efficiencies slipping through the cracks and potential disasters growing without the light of proactive analytics and AI. Life sciences operations are not farms: nothing good will ever come out of a silo.

But research shows that labs embracing IoT and predictive analytics are seeing real benefits, including greater visibility, more reliable equipment, and less downtime. These improvements have far-ranging positive impacts, including enhanced drug quality control and optimized supply chain logistics.

Connectivity: life science’s new best friend

The challenges labs face today require more than just basic equipment monitoring. They require leading-edge IoT tools that connect equipment and systems across the board:

• Seamless equipment integration: IoT systems can now link a wide range of devices—even older models—ensuring continuous data flow.
• Improved reproducibility: Real-time monitoring of conditions supports consistent experimental results and reliable production.
• Smarter alerts: Predictive algorithms can provide alerts with insightful context, helping teams quickly distinguish routine events from critical issues. 

The future is bright—and really well connected

The integration of advanced connectivity in life sciences isn’t growing; it’s exploding. By fully embracing the IoT connectivity revolution, labs and manufacturing facilities are reducing human error, resulting in fewer “oops” moments and more “aha!” breakthroughs. This is what humans ought to be doing.

The time is ripe for labs and manufacturing facilities to embrace the modern gift of connectivity. Lab managers’ future selves will certainly appreciate the upgrade to time savings and ROI. And who knows? Maybe with all that extra time, you’ll finally figure out what that weird growth in the back of the lab fridge really is.