In today’s pharmaceutical landscape, the path from target discovery to market-ready drug is long, risky, and expensive, taking on average 10–12 years and costing billions. More than nine out of every ten drugs that begin human testing fail, due to unmanageable toxicity or adverse side effects or lack of clinical efficacy. Add to that growing R&D costs and increasingly complex IP landscapes, and it’s clear that pharma needs a smarter, faster way to navigate development.
One of the most critical bottlenecks? Siloed and disconnected data. Despite the abundance of chemistry data in ELNs, registries, patents, and public repositories, much of it remains trapped in fragmented systems; inaccessible, unstructured, and unlinked. As a result, R&D teams face blind spots that delay discovery, inflate costs, and increase the risk of missed or duplicated IP.
Chemistry Data is scattered everywhere, except where you need it the most
Medicinal chemists must manually sift through diverse systems to find, evaluate, and compare compounds. A typical medicinal chemist spends up to 40% of their time simply looking for information and screening molecules.
Traditional cheminformatics systems struggle to unify the data needed for effective decision-making:
- Chemical structures are stored separately from reactions, SARs, or IP.
- Assay results and properties may live in custom spreadsheets or siloed ELNs.
- Patent claims, when searchable at all, are not linked to compounds or documents.
Researchers must manually navigate these disconnected sources, spending valuable time searching, copying, standardizing, and cross-referencing, often without full context or traceability.
The result? Slower decisions, missed connections, and higher failure rates.
When key relationships between structures, properties, and intellectual property are hidden or manually reconstructed, researchers face blind spots that delay candidate evaluation and increase the risk of redundant work, overlooked liabilities, or lost innovation opportunities. Worse, without full traceability, it becomes difficult to reproduce insights, justify decisions, or collaborate effectively across teams. In a field where timing, novelty, and evidence are everything, fragmented data isn’t just inconvenient – it’s a strategic liability.
BioTech360 Cheminformatics: Where Structure Awareness Meets Connected Science
BioTech360 brings together structures, reactions, documents, properties, and patents into a single intelligent platform powered by an ontology-driven knowledge graph specifically designed for chemistry and life sciences. Some of the top capabilities that BioTech360 Cheminformatics include:
1. A context-driven search: Find what Matters, and faster
Identity, similarity, and substructure searches are all in one place. No more digging through unstructured data sources and wasting time on screening lead compounds. BioTech360 Cheminformatics detects the chemistry you’re referring to, not just the keywords you type. Every hit leads back to connected reactions, properties, patents, documents, and vendor data; therefore, reducing blind spots in exploration.
2. Trust Every Decision
Evidence-linked results show the exact source: the structure, the document, even the original patent claims.
3. Search All Sources in One Query
Internal chemical repositories, public chemistry datasets, and patent databases are unified and integrated into a single, FAIR-aligned knowledge layer.
4. SAR & Property Insight at Scale
Turn structural variations into actionable insights with linked assay/property data and SAR visualization.
A Versatile Knowledge Graph Platform
The BioTech360 Cheminformatics knowledge graph is a unique feature that transforms scattered chemistry data into a powerful, connected intelligence layer designed for discovery. Built on an ontology-driven semantic foundation, the module unifies structures, reactions, properties, documents, and patents into one seamless network, so chemists don’t just search; they see the context and science behind the search. Every result is evidence-linked, traceable, and enriched with context, allowing teams to uncover relationships they didn’t know existed before. By harmonizing identifiers and integrating internal and trusted public datasets, the knowledge graph delivers a powerful, single source of truth that accelerates lead identification and faster R&D decisions. It’s not just scientific data management; it connects chemistry data to innovation.
How BioTech360 Cheminformatics solves the Challenge
A biotech company discovered a promising anti-inflammatory molecule for wound healing. However, understanding its SAR space and patent freedom requires:
- Checking and scanning similar compounds
- Mapping known reactions
- Reviewing patents for overlapping claims
- Exploring repositories alongside public patent content across selected internal and public chemistry datasets
Traditionally, this effort could have taken two to three weeks across multiple systems.
The BioTech360 Cheminformatics Journey: A step-by-step solution for the biotech company
Step 1: From Scaffold to Series
The system instantly retrieved identity, similarity, and substructure matches across both internal files and public chemistry databases.
Step 2: A Context-driven search
Linked property data and known reactions with pre-integrated public ontologies provided immediate visibility into synthetic routes and activity trends.
Step 3: One-click patent scouting
BioTech360 Cheminformatics module surfaced structurally similar compounds buried in global patent collections, automatically extracted reactions, and linked them back to the full patent text. Even structures embedded in PDFs were captured through Optical Structure Recognition (OSR).
Step 4: Build and share a prioritized analog series
The drug discovery team saved the shortlist, tagged key candidates, and shared it with the medicinal chemistry team all within the platform.
The Outcome
Screening of the lead compound was reduced by 70% with increased confidence in patent and document search by structure. The organization was also able to take faster, better decisions driven by contextualized evidence and put an end to fragmented workflow and manual searches.
Cheminformatics an important tool in the AI Era
BioTech360 provides explainable AI with clear knowledge of graph-based evidence to questions users ask. By integrating AI capabilities, LabVantage BioTech360 cheminformatics aims to enhance life sciences research and development processes, enabling scientists to make data-driven decisions and accelerate discovery. It enables explainable AI-powered search by leveraging an ontology-driven knowledge graph and structure-aware search capabilities. With BioTech360 Cheminformatics module, medicinal and computational chemists instantly uncover identity and similarity matches, reactions, patents, and vendor options, all seamlessly integrated across internal and public chemistry datasets. It unites your chemistry, SAR, and patent intelligence in one powerful platform. Connect your chemistry and transform your R&D. Talk to us today for a demo.
