Chemists Struggle When Forced to Use a Biology Oriented ELN

If you're a chemist using an ELN built for biology, you know exactly what we're talking about. And yes, biologists in chemistry-oriented ELNs feel the same—we’ll get to that another time. A high performing solution exists for you: our partner’s platform lets you keep your biology-focused ELN while seamlessly integrating into a next-generation chemistry environment that supports your full scientific method and domain expertise. 

Many leading ELNs built for biology lack native support for structure-based registration, reaction tracking, or the nuanced workflows that medicinal and synthetic chemists depend on. That’s not criticism; it’s simply a reflection of their design priorities. To date, we haven’t seen meaningful evolution in these platforms to address core chemistry use cases. 

Still, many organizations pursue a “one ELN for all” strategy, which can lead to inefficiencies or even non-adoption if not carefully managed. This challenge extends beyond bench chemistry. In computational chemistry, it’s common to find researchers working outside the deployed ELN altogether—using Jupyter notebooks or specialized modeling tools that don’t fully integrate with the organization’s data environment. 

Regardless of whether your work is in a wet lab or an in silico environment, the scientific method must be consistently and rigorously captured. This is especially true as the industry shifts toward model-first and in silico-first approaches to drug discovery. A fit-for-purpose digital environment isn’t a luxury—it’s foundational. 

That’s where complementary chemistry solutions come in. We’re helping teams bridge the gap by integrating purpose-built chemistry and cheminformatics tools alongside their Bio-oriented ELN — giving chemistry functions the capabilities they need without disrupting the rest of the organization. And… it can save an organization millions of dollars! 

Think about a Chemistry expert platform that has: 

• A laser focus on IDSMTA (Ideate, Design, Simulate, Make, Test, Analyze) is the newer paradigm for medicinal/synthetic and computational chemistry to lead optimization workflow. 

• In silico-first or Model-First approaches where users can host, manage, and fine-tune their own ML/AI models, linking them directly to experimental data to continually improve performance over time 

• Compound design to synthesis and biological testing—into one cohesive platform, eliminating tool silos, spreadsheets, and email chains 

• Seamlessly manages requests across internal teams and external CROs, with queue-based automation that ensures the right compounds are synthesized and tested at the right time Seamless alignment with bioassay data and experimental workflows 

• Incorporates no-code AI tools (like GenMol and DiffDock from NVIDIA BioNeMo) for virtual screening, docking, and predictive modeling—accelerating the Ideate-Design-Simulate–Make–Test–Analyze (IDSMTA) cycle. 

• Enhancing and supporting a connected environment, controlled collaboration with CROs, researchers, and internal stakeholders—ensuring IP and sensitive data stay protected with granular permission settings 

If you're a chemistry team trying to work around a biology-first platform, reach out as we have an amazing solution for you!