Every few weeks, I'll step outside my usual focus on business models and frameworks to highlight emerging patterns in tech and markets…..so we can adapt to the shifting tides in how we invest, operate and make decisions.
In this issue-
New drugs, new logistics demands, and a delivery technology that could change it
3D printing could flip how batteries are designed; a white space for startups
Edge computing is evolving into something smarter → Edge AI
GLP-1s like Ozempic and Wegovy are changing lives and businesses in dramatic ways. As more people use them to tackle obesity, addiction, and a growing list of health conditions and prices come down, it is indirectly giving a boost to the logistics industry.
GLP-1 need to be stored and shipped in temperature-controlled facilities throughout the supply chain. Other new drugs coming down the pipeline are categorized as biologics. It means that they are derived from living matter and therefore temperature sensitive, requiring refrigeration from manufacture to delivery.
Demand for these drugs is expected to reach a market value of $39 billion by 2033. UPS has responded with a $48 million investment in 27 temperature-controlled facilities across the world.
On the other side is a countervailing force. Microneedle skin patches, currently commonly used for hormones and nicotine, are being developed as a way to deliver more and advanced drugs transdermally (i.e. through skin patches) This market is expected to double from current levels and reach $1.6 billion by 2036.
If the technology matures sufficiently, it will reduce the dependency on complex cold chain logistics. Its benefits include minimally invasive, pain-free self-administration, but there are some regulatory hurdles that companies making these have to overcome. For now, this technology is still in its infancy.
These patterns are not new. Vaccines and insulin both forced the expansion and specialization of cold chain infrastructure in their time. Now it is happening again at a larger scale and with a twist of even more specialization with GLP-1s and biologics. Microneedle patches, when they come due, could potentially require yet another rethink about logistics.
Since these are both emerging trends, here’s what I think will happen.
The cold chain logistics boom that is being driven by GLP-1s and other new generation drugs is likely to sustain for some years.
However, while cold chain infrastructure will likely prevail for complex biologics and drugs that cannot be delivered any other way, drug delivery through micro-needle patches will gradually capture its own segment of the market for simpler self-administered treatments and mass vaccination…..but only after those companies have successfully navigated regulatory approval and scaled up manufacturing.
Today, batteries come in standard fixed forms. Any innovations in battery making in the last thirty years have been in the chemistry of the batteries, i.e., the ‘content’ and not as much the physical aspect. Products, whether drones, phones or or any other devices, have been designed around the battery shape and form.
Until now. Enter 3D printing.
According to a recent Wall Street Journal article, researchers published a whopping 25,000 papers in 2025 on the 3D printing of batteries!!!!!
The idea is that we can flip the way that products have been designed. Instead of building products and organizing components around batteries, 3D printing allows us to print batteries around the components, filling the available space between and around them in a product. 3D printing is ideal for the latter because it entails additive manufacturing, which builds an object by adding material layer by layer until you have the final shape.
The advantage is that 3D printing would enable energy storage to be integrated directly into products, using previously wasted space inside devices, drones, vehicles, and wearables; e.g. “Smartglasses could have sleek battery-packed frames”. So, increasing energy capacity without making products larger or heavier. It is agnostic to battery types which means that it can be used for lithium-ion, sodium-ion, solid-state and possibly other upcoming battery types.
Application of this technology is in its very early stages. There are barely a handful of startups that are innovating in this space. A couple of examples are Material Hybrid Manufacturing and Sakuu. That means there is plenty of room in the market for other start-ups to take this on.
Since it’s commercialization, 3D printing has proven its value in high complexity, low volume, precision applications such as aerospace, medical devices, and hearing aids. It has significantly reduced the time and cost of product development across manufacturing sectors.
If it is able to achieve that again here, it would be another instance of manufacturing innovation unlocking design freedom….similar to how 3D printing has transformed industries before.
We can expect that, based on existing patterns for many new innovations, the first commercial applications will emerge in military and aerospace before eventually reaching consumer devices.
As someone who has worked with data for 20+ years, I can confirm that having more quantity and variety of data is usually a good thing. You can get more reliable results. That’s great when that data is being produced and processed on site. You can get fast results that humans can review and act on immediately, if that is your goal.
But if you are looking to process data received in real time from smartphones, autonomous vehicles, or industrial sensors that are located far away from where the data is processed, there is latency in receiving that data and then transferring results back to the source to take action. Bandwidth is usually limited and expensive.
The solution to this issue has been edge computing in which data is processed locally by following pre-programmed, fixed rules or algorithms. Locally means on the device or location itself. It reduces the bandwidth required to send all of it back and forth. Only relevant information and results are sent for further human review. It’s fast and efficient.
As a simple example, a factory sensor monitors temperature and is programmed to trigger an alert if it exceeds 200 degrees F. It doesn't send every temperature reading to the cloud or server. It just acts when the threshold is crossed. No human in the loop for regular temperature readings.
Now that we have developed advanced AI capabilities, edge computing is starting to morph into Edge AI. Here, the device isn’t just processing, it is also reasoning. It can handle ambiguous unstructured inputs like images or natural language and make judgment calls.
Edge AI is becoming a pattern across industries. See this fascinating use case of edge AI in space, literally the farthest point possible. In April 2026 for the first time ever a satellite in orbit used a vision-language model to identify “areas of interest in response to natural language queries.” It responded dynamically to something it wasn’t explicitly programmed to find.
Well, this one writes itself. As more devices, vehicles, sensors, and yes, satellites generate data in places where transmitting everything back and forth to a central point is impractical or prohibitively expensive, intelligence (AI) will continue to shift to the edge.
The pattern is the same one we saw with edge computing but with AI capabilities added in. We can expect to see it show up in healthcare devices, agricultural sensors, and remote infrastructure monitoring, basically anywhere that data is produced far from where decisions need to be made. At some point as AI Agents become even more commonplace, edge AI could extend to acting on the results autonomously, without human review at all!
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