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Case Study: How a Therapeutics Biotech Unified 5 Oligo Notations Enabling Cross-Functional Collaboration

Writer: Karchem Consulting
Karchem Consulting
9 hours ago
4 min read

Client

Clinical-stage Therapeutics Biotech

Service

Benchling Customization

Key Results
  • Notation languages unified: 5 (HELM plus 4 custom notations) managed in one system instead of separate Excel spreadsheets

  • Monomer library built: ~300 monomers defined, covering sugar, base and phosphate modifications

  • Mappings configured: 1,400+ custom notation mappings, validated by the client's scientists

  • Cross-functional communication: chemists, biologists and synthesis scientists work from one shared monomer definition, using whichever notation they use

  • Time to deploy: less than 1 month to configure custom notation mappings

A clinical-stage oligonucleotide therapeutics biotech worked with Karchem to unify five oligo notation languages in Benchling, giving chemists, biologists and vendors one shared way to define and register the heavily modified PMO and siRNA sequences at the core of its pipeline. Teams and oligo synthesizers worked in HELM plus four custom notations, and converting sequences between them relied on Excel spreadsheets that often broke and slowed oligo registration in Benchling. Karchem paired their oligonucleotide chemistry expertise with Benchling configuration, working directly with the client's scientists to capture mapping knowledge only they held, and built a centralized monomer library of nearly 300 base, sugar, and phosphate monomers, plus more than 1,400 custom notation mappings, in Benchling. Scientists now enter a sequence in their preferred notation and register it directly in Benchling, with consistent monomer definitions that support IP documentation and communication across research groups and vendors. The project took less than one month. 


Introduction

Our client is a clinical-stage biotech whose platform pairs a targeting antibody with an oligonucleotide payload, typically a phosphorodiamidate morpholino oligomer (PMO) or small interfering RNA (siRNA), joined through a chemical linker.


Its chemists synthesize these oligos daily, modifying the base, sugar, or phosphate group of individual nucleotides. Because HELM notation treats each of those three components as its own monomer, the team tracks hundreds of monomers and adds new ones as programs evolve. The same molecules were also described in four custom notations, each favored by different internal teams, oligo synthesizers, or external vendors.


Challenge

Every oligo had to be registered in Benchling, but with no single standard for describing the type and position of each chemical modification, sequences existed in five notation languages and different teams preferred different ones. HELM (Hierarchical Editing Language for Macromolecules), the open standard maintained by the Pistoia Alliance, was the canonical format. Four custom shorthand notations sat alongside it.

Converting meant running each sequence through an Excel spreadsheet for each notation, then into HELM. As the company scaled and prepared for IP review, that process caused four problems:

  • Spreadsheets broke constantly. Each new modified monomer risked a formula failure.

  • Registration required several manual steps, and each manual translation created a chance to introduce an error and order the wrong molecule.

  • Monomer definitions were inconsistent, weakening the record needed for IP documentation.

  • Teams and vendors talked past each other, each using its own shorthand with nothing connecting them.




Solution / Approach

Karchem replaced the spreadsheet chain with a native Benchling configuration: one HELM monomer library and four custom notations, all resolving to the same monomer definitions.

  1. Mapped the notation landscape. Karchem audited the four custom notations and existing spreadsheets to see how each expressed sugar, base, and phosphate modifications, and where they disagreed.

  2. Built the HELM monomer library. Using Benchling's monomer library, Karchem gave each of nearly 300 base, sugar, and phosphate monomers one authoritative definition, so every scientist designing sequences selects from the same centralized list.

  3. Defined mappings with scientists, by pattern. The hardest part of any notation project is getting bench scientists to confirm hundreds of mappings. Karchem explained how Benchling resolves notation into monomers, then walked scientists through the naming process

  4. Delivered review spreadsheets. Agreed patterns became structured mapping sheets for scientists to check before anything entered the system.

  5. Configured and tested. Karchem loaded 1,400+ mappings and tested conversions against representative modified sequences until every notation produced consistent output

The key design decision was making HELM monomers the single source of definition. Each custom notation maps to those monomers, not to each other, so a new monomer is defined once instead of across four conversion paths.




Outcome

In less than a month, the client replaced four breaking spreadsheets with one Benchling system. A scientist enters an oligo in any of the five notations, and Benchling automatically generates the other four.

  • One-step registration: oligos register directly in Benchling, with no spreadsheet conversion. Registration is sensitive to chemical modifications, so oligos with the same sequence but different modifications are recorded as distinct entities.

  • IP-ready monomer library: nearly 300 monomers, each with one authoritative definition that preserves the team's institutional knowledge.

  • Clear cross-functional communication: chemists, biologists, and synthesis vendors use their own notation while referring to the same molecule.

  • Built to scale: new monomers are added once and available in every notation.


"We were looking for a truly integrated ELN that could serve as a single source of truth across multiple scientific disciplines. Specifically, we needed a platform that could track reagent and product inventory, visualize and manage complex entity hierarchies for macromolecules including antibodies, peptides, oligonucleotides, and their conjugates, and support material planning and calculations for both in vitro and in vivo studies. Just as important, we wanted all of this, including the data, entities, and experimental context, to be tightly linked, enabling seamless collaboration between chemists, biologists, formulation scientists, and bioinformatics teams."
— Associate Scientist, Chemistry, Clinical-stage biotech



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