What is a personalized ASO?

A personalized antisense oligonucleotide (ASO) is a short synthetic DNA strand designed specifically for one patient's unique genetic mutation. It binds complementary RNA to modulate gene expression — silencing a toxic gene, modifying splicing (exon-inclusion, exon-skipping, or pseudoexon-blocking), or upregulating an insufficient gene — without editing the genome.

How do I get an ASO designed for my mutation?

Visit pequliar.ai and describe your genetic mutation or upload your genetic report. Pequliar's AI designs ranked, synthesis-ready ASO candidates with full chemistry assignment and vendor-formatted sequences. A complete design costs $399 and takes minutes.

What diseases can be treated with ASOs?

ASOs can target nearly any genetic mutation. FDA-approved ASO drugs exist for spinal muscular atrophy (Spinraza — exon-inclusion), Duchenne muscular dystrophy (Exondys 51 — exon-skipping), ALS (Qalsody — gene-silencing), and hereditary transthyretin amyloidosis (Tegsedi — gene-silencing). Personalized ASOs have been designed for Dravet syndrome, MELAS, Usher syndrome, Angelman syndrome, Huntington's disease, Leber congenital amaurosis, and many other rare genetic diseases.

How much does personalized ASO design cost?

A complete ASO design on Pequliar costs $399. This includes ranked candidates, full chemistry assignment, thermodynamic scoring, quality checks, and vendor-formatted sequences ready for ordering from synthesis vendors.

Has Pequliar been validated?

In blind validation, Pequliar recovered the exact sequences behind FDA-approved ASO drugs — including Nusinersen (Spinraza), Tofersen (Qalsody), and Eteplirsen (Exondys 51) — that took years to develop, in minutes.

July 30, 2026

ASO Design Tools: What Patients and Researchers Should Know

ASO designantisense oligonucleotidesrare diseasecomputational biology

Antisense oligonucleotides (ASOs) are short synthetic DNA strands that bind to messenger RNA and modify gene expression. They are one of the most promising therapeutic approaches for rare genetic diseases, with over a dozen FDA-approved ASO drugs and hundreds more in clinical trials. But designing an effective ASO for a specific patient mutation is a complex computational challenge.

Several tools exist for ASO design, each with different strengths. Here is what patients, families, and researchers should know about the current landscape.

Academic and research tools

OligoWalk (University of Rochester)

OligoWalk is a thermodynamic prediction tool developed by the Mathews Lab. It calculates the free energy of oligonucleotide-target RNA binding, accounting for self-structure in both the ASO and the target. It is widely cited in the ASO literature and considered a gold standard for binding energy prediction.

Strengths: Rigorous thermodynamic modeling based on nearest-neighbor parameters. Accounts for target RNA secondary structure. Well-validated against experimental data.

Limitations: Command-line interface requires bioinformatics expertise. Does not handle the full design workflow (target selection, off-target screening, chemistry optimization). No variant-specific guidance.

MASON (Max Planck Institute)

MASON (Massive Automated Sequence-Optimized Nucleotide design) is a research tool for designing antisense oligonucleotides against any target transcript. It scores candidates based on binding affinity, self-complementarity, and off-target potential.

Strengths: Automated candidate generation across the full transcript. Considers multiple scoring criteria simultaneously.

Limitations: Research-focused interface. Requires users to provide their own transcript sequences and interpret raw scores. No clinical context or variant-specific design.

Oligo-ASST

Oligo-ASST is a web-based tool for antisense oligonucleotide design that provides accessibility predictions and binding site analysis.

Strengths: Web interface lowers the barrier to entry. Visualizes target accessibility.

Limitations: Limited scoring depth compared to OligoWalk. Does not integrate with clinical variant databases.

sfold (Wadsworth Center)

sfold samples RNA secondary structures from the Boltzmann ensemble and identifies accessible target sites. It provides a statistical approach to target selection that accounts for the dynamic nature of RNA folding.

Strengths: Ensemble-based approach captures structural diversity. Strong theoretical foundation.

Limitations: Computationally intensive. Not specifically designed for ASO chemistry optimization.

What these tools have in common

All of the tools above are designed for researchers who already know their target gene, have the relevant transcript sequence, and can interpret thermodynamic scores in context. They answer the question: "Given this RNA target, which binding sites have favorable thermodynamics?"

This is an important question, but it is only one piece of the ASO design puzzle. A complete design workflow also needs to consider:

Variant-specific targeting. Which region of the pre-mRNA should the ASO bind, given the specific mutation? For exon skipping, the ASO must target splice regulatory elements of the exon to be skipped. For splice switching, the ASO must block aberrant splice sites created by the mutation.
Off-target screening. Does the candidate sequence bind elsewhere in the transcriptome? NCBI BLAST screening against the human genome is essential to avoid unintended gene silencing.
Chemistry selection. Different ASO chemistries (2'-MOE, PMO, LNA, cEt) have different binding affinities, nuclease resistance, and tissue distribution profiles. The optimal chemistry depends on the therapeutic goal and delivery route.
Quality heuristics. Empirical rules from decades of ASO research — GC content windows, avoidance of G-quartets, CpG motif minimization, poly-nucleotide run limits — that correlate with in vivo efficacy and safety.

The gap for patients and families

For a family navigating a rare genetic diagnosis, the challenge is not choosing between OligoWalk and MASON. The challenge is that none of these tools provide an end-to-end answer: "Here is a designed ASO candidate for your child's specific mutation, with off-target screening, quality assessment, and enough documentation to bring to a physician or n-of-1 program."

This is the gap that patient-facing ASO design platforms aim to fill. Rather than replacing the research tools — many of which represent excellent science — the goal is to orchestrate them into a complete workflow that starts with a mutation and ends with a ranked set of synthesis-ready candidates.

What to look for in an ASO design platform

Whether you are a researcher evaluating tools or a family exploring options, here are the criteria that matter:

Variant-specific design. The tool should accept a specific genetic variant (gene, mutation, coordinates) and design ASOs targeting the relevant mechanism (exon skipping, splice switching, gene silencing, etc.).
Multi-tool concordance. No single scoring method captures all aspects of ASO quality. Look for platforms that integrate multiple orthogonal scoring approaches and rank candidates by agreement across methods.
Off-target screening. BLAST-based screening against the human transcriptome should be standard, not optional.
Transparent scoring. You should be able to see why a candidate ranks where it does — which heuristics it passes or fails, what its binding energy is, how it compares to alternatives.
Synthesis-ready output. The output should include the full ASO sequence, recommended chemistry, and enough documentation to hand to a synthesis provider or research collaborator.
Accessibility. If the tool requires a bioinformatics degree to operate, it is not accessible to the patients and families who need it most.

Where Pequliar fits

Pequliar is a patient-facing ASO design platform that orchestrates multiple scoring tools — including thermodynamic prediction, off-target BLAST screening, and 36 empirical quality heuristics — into a single workflow. You describe your mutation in plain language, and the platform returns ranked ASO candidates with full documentation.

It does not replace the need for experimental validation, and it does not replace the judgment of physicians and researchers. But it aims to lower the barrier between a genetic diagnosis and a concrete ASO design that can be evaluated, discussed, and potentially pursued through n-of-1 treatment programs.