Genetic Medicines: A Blend of Payload & Delivery System

Benefit #1

Genetic Medicine Payloads

Genetic medicine payloads such as mRNA, siRNA, DNA, antisense oligos (ASOs), and gene editing systems, offer potential to revolutionize the treatment of human diseases.

Our primary goal is to expand and enhance therapeutic targets by enabling frequent re-dosing, reducing toxicity, and increasing transfection rates.

Diagram of genetic payloads
Diagram of Payload Delivery
Benefit #2

The Delivery Challenge in Genetic Medicines

However, the hurdle lies in the effective delivery of these payloads into cells. Current methods, including viral vectors, lipid nanoparticles (LNPs), polymers, adeno-associated virus (AAV), exosomes, GalNAc-conjugates and more, have inherent limitations.

Issues ranging from safety concerns, immunogenicity, inability to frequently re-dose, payload constraints, and tissue specificity, pose challenges for their broad therapeutic application.

Benefit #3

Lipid Nanoparticles: The Current Picture

LNPs, while popular for drug delivery, face significant challenges. Their non-degradable nature inhibits frequent re-dosing, lowers transfection rates, and ultimately reduces therapeutic effect.

Additionally, the process to synthesize, screen, and producing new LNP formulations for various targets is costly and time-consuming.

Image of a female scientist looking at a microscope
Our technology

The Future of LNPs.

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    At Opus Biosciences, we are actively redefining the future of LNPs. Two core proprietary technologies take center stage in our work, alongside our persistent pursuit of new innovations in drug delivery.

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    We have developed a new class of rapidly degradable LNPs, an approach designed to enable superior endosomal disruption, more frequent re-dosing, and higher transfection rates across a variety of organs, tissues, and cell types.

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    Concurrently, we have streamlined the lipid synthesis process by establishing a more efficient and GMP friendly methodology.

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    Artificial intelligence is a vital part of our LNP synthesis process.

    By utilizing machine learning algorithms, trained on our comprehensive bio-molecule library, we are effectively optimizing for increased transfection efficiency, reduced toxicity, and enhanced specificity in targeting.

    This approach is propelling us forward in our mission to create more sophisticated and effective drug delivery systems.

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    This technology allows Opus to rapidly expand our library of LNP formulations for a diverse array of targets without compromising quality or effectiveness.

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Image of two hands, one holding a lipid nanoparticle, the other holding a vial