ASO Therapy

Advancements in RNA-based therapeutics centered on the regulation of gene expression

ASO Therapies: Rapidly Evolving RNA-Based Therapeutics

Antisense oligonucleotide (ASO) technology allows targeted modulation of gene expression via short nucleotide sequences. Advances in ASO chemistry have improved stability, binding affinity, and tissue specificity, expanding their potential applications.

From Nusinersen, the FDA-approved 2016 drug for Spinal Muscular Dystrophy (SMD), to Tofersen, designed for SOD1-ALS and FDA-approved in 2023, multiple ASO approvals highlight their therapeutic potential in addressing specific genetic mutations linked to neurodegenerative disorders, paving the way for personalized treatments.

Antisense Oligonucleotide-based drugs are one of the promising therapeutic agents for the treatment of various human diseases. However, several issues must be overcome in the development of ASO based drugs such as:

Delivery of ASOs

Insufficient biological activity

Short ​​blood circulating half-life

Off-target side effects

Generations of ASO Therapies

Representing a new and highly promising class of RNA-based drugs for personalized medicine
The ASO field is an emerging area of drug development that targets the disease source at the RNA level and offers a promising alternative to therapies targeting downstream processes. Antisense oligonucleotide therapy has evolved through several generations, each marked by advancements in oligonucleotide design, and chemical modifications.

First Generation

First-generation ASOs feature a modified phosphorothioate (PTO) backbone, enhancing nuclease resistance and solubility. They exhibit strong antisense activity and induce mRNA degradation via RNase H.

Second Generation

Second-generation ASOs feature modifications such as 2′-O-alkyl, 2′-OMe, and 2′-MOE, which enhance binding affinity, efficacy, nuclease resistance, improve RNA affinity, and mitigate immunostimulatory effects.

Third Generation

Third-generation ASOs employ furanose ring chemical modifications, enhancing ASO-RNA hybridization, improving nuclease resistance, binding, pharmacokinetics, and biostability, while reducing toxicity.

Revolutionizing ASO therapy with AI and innovative approaches

The rapid progress in ASO therapy is being significantly propelled by advancements in ML, AI, and high-throughput sciences.

In silico tools aid in providing a better understanding of available genomic and transcriptomic data, which includes sequence, structure, expression, and function.

Identify targets, including Canonical and Non-Canonical splice site prediction

Predict target and ASO structures and examine complex

Identify and verify targets across species

Design ASOs, make modifications, and conduct simulations to find the most appropriate drug

Aganitha’s Point of View

ASOs represent a new and highly promising class of drugs for personalized medicine.

We utilize Generative AI and ML in Antisense Oligonucleotide therapy to enhance target design, and optimize treatment.

01
Analyzing large genomic and proteomic datasets to identify potential targets for ASO therapy and to predict genes or RNA sequences associated with specific diseases or conditions.
02

Predicting the most effective sequences for targeting specific RNA molecules, and analyzing the structural and sequence properties of the target RNA to optimize ASO design for enhanced binding affinity and specificity.

03
Modeling the pharmacokinetics and pharmacodynamics of ASOs helps predict their distribution, metabolism, impact on the targeted RNA, and elimination from the body.
04
Identifying patient populations more likely to respond positively to ASO therapy involves analyzing diverse patient data, including genetic information and clinical outcomes, thereby tailoring ASO treatments for specific subgroups.
05
Identifying common molecular targets across different species provides the foundation for establishing more reliable animal models that recapitulate aspects of human diseases.
06

Collating omics data, such as evolutionary scores, biomarkers, and regulatory elements, from varied authentic sources to facilitate target identification.

Examples of solutions we have developed for our clients

Pioneering Applications and State-of-the-Art Techniques of ASO therapy

Featurized data to build the model

Featurized genomic data to construct a model for improved prediction of splice sites by analyzing factors such as tissue specificity, methylation, and regulatory elements, thereby accelerating target identification.

Predicted the structure

Predicted the structures of the target mRNA and ASO to better understand the formation of Watson-Crick pairs between the target RNA and ASO. This process depends on the structural availability and thermodynamic stability of both structures.

Examined the stability of target and ASO complex

The efficacy of ASO depends on the binding energies between the target RNA and ASO, and the stability of the resulting complex. Understanding the stability of the complex is crucial for determining the frequency of drug administration.

Found common targets between species

Our advanced in silico simulations allowed for the identification of viral vectors with higher efficacy in targeting specific tissue types, for example, targeting blood-brain barrier receptors.

Identified Off targets

Screened the transcriptome to identify sequences similar to the target RNA and, thereby, selecting the target RNA to be unique enough for the ASO to bind to it specifically, minimizing off-target effects.

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