From Injections to Patches: IPA's AI Revolution in GLP-1 Diabetes Therapy

The current GLP-1 drug landscape has a persistent problem—frequent injections. Drugs like semaglutide require repeated dosing due to their short half-life, which impacts patient compliance and quality of life. What if we could redesign these molecules from scratch using artificial intelligence?

ImmunoPrecise Antibodies (IPA) just did exactly that.

Listed on NASDAQ: IPA, the biotech company has leveraged its proprietary LENSai™ platform—an AI-driven system that decodes evolutionary patterns in biological data—to generate an entirely new class of GLP-1-like therapeutics in just two weeks. This isn’t incremental improvement; it’s computational drug design at scale.

The Problem With Today’s GLP-1s

Current GLP-1 therapies dominate diabetes and obesity treatment, but they come with tradeoffs: short duration requiring frequent injections, manufacturing complexity, and limited patient accessibility for non-invasive options. The industry has been tweaking chemical structures, but IPA took a different path.

How LENSai Rewrites the Rules

Instead of traditional medicinal chemistry, IPA’s LENSai platform identifies unique molecular patterns by analyzing how therapeutic sequences evolved across species. The system then generates optimized genetic sequences that:

• Extend half-life through enhanced resistance to enzymatic breakdown—meaning fewer doses
• Improve manufacturability using rational genetic engineering rather than chemical synthesis
• Enable non-invasive delivery by optimizing molecular size and properties for transdermal patches

The AI-generated sequences were further refined using IPA’s proprietary HYFT® technology, which enhances binding strength and therapeutic stability. The result: GLP-1 alternatives designed for compatibility with nucleic acid-based expression systems.

The Transdermal Game-Changer

Perhaps the most striking innovation—IPA is exploring transdermal patch delivery for these AI-designed GLP-1 therapies. Rather than weekly or daily injections, imagine a small patch providing steady, controlled release of the therapeutic peptide. The AI optimization specifically tailored molecular properties to support this delivery method, addressing a major pain point in current diabetes management.

Why This Matters for Biotech Innovation

IPA’s approach represents a fundamental shift in how therapeutics are discovered:

1. Entirely computational: From discovery through optimization, the process happens in silico before any wet lab work
2. Rapid iteration: Two weeks to generate, develop, and optimize novel sequences—versus months for traditional methods
3. Precision engineering: Every molecular detail is optimized for specific therapeutic goals rather than following conventional industry templates

The HYFT patterns underlying LENSai are exclusive to IPA, providing competitive moat and potential licensing opportunities across multiple therapeutic areas.

The Road Ahead

These AI-designed GLP-1 constructs are currently in preclinical evaluation. IPA is investigating transdermal feasibility, collaborating with established nucleic acid delivery specialists like Aldevron (a Danaher company) to ensure compatibility and optimize gene expression while minimizing immune response risks.

The implications extend beyond GLP-1: LENSai’s in silico capabilities position IPA at the frontier of next-generation biologics development, with potential to accelerate drug discovery across diabetes, obesity, and beyond.

For investors tracking biotech innovation and AI-driven therapeutics, IPA’s computational approach offers a glimpse into how drug development may evolve—faster, more precise, and eventually, more accessible to patients through non-invasive delivery methods.