A top 5 pharmaceutical company wanted to be at the forefront of the personalized medicine revolution. That's when they reached out to AI Dev to take on this difficult but compelling project.
Our client needed to manufacture small batches of personalized tablets but had trouble meeting the very tight specifications required for size, shape and weight.
Conventionally, tablets are mass-manufactured using an extremely standardized process. While this leads to reliable uniformity and global-scale mass production, it's the exact opposite of what's needed for personalized medicine.
While 3D printing is ideal for personalized manufacturing, it's not a mature technology. Using 3D printers to manufacture medicine is new and unproven.
We turned to a cutting-edge method of 3D printing — bioprinting — in which the tablet begins as a viscous material inside a syringe, then is extruded in the shape of a tablet using precision air-pressure.
Standard bioprinting wouldn't come close to the strict uniformity requirements for size, shape and weight demanded by pharmaceutical standards.
Some materials behave unpredictably under pressure — their viscosity changes during extrusion, making consistent and reliable output a Herculean task.
We customized the 3D printer firmware to allow precise control over movement and extrusion pressure, enabling fine-tuned adjustments impossible with standard equipment.
We built a detailed database of material characteristics and behaviors, including non-Newtonian materials, creating a foundation for intelligent extrusion control.
Deep learning analysis allowed us to conduct tablet manufacturing runs in a simulated environment, which we used to dramatically improve real-world results before physical testing.
We developed a system to adjust material extrusion to pinpoint scientific standards by using an intelligent camera to continuously monitor and measure extrusions in real-time.
Real-time visual data gave us the ability to create automated dynamic air pressure control, thereby obtaining sub-millimeter accuracy in tablet production.
Combining detailed modeling of material behavior with real-time intelligent video monitoring resulted in a robust, reliable and repeatable tablet manufacturing system.
Multiple outside companies made the attempt, but only AI Dev brought tablet production within the required margin of error, demonstrating what was possible and spurring further research into personalized medicine.
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