Solutions

Cheminformatics

Chemical data is unstructured by nature and high in value. UVJ builds the systems that give research teams a reliable, searchable and computationally useful view of it.

Chemical structure and compound data representation

Overview

What it is

Cheminformatics is the computational treatment of chemical information: representing and standardising structures, managing compound and reaction data, searching chemical space, and applying statistics and machine learning to properties and activity. It supports discovery, formulation, safety assessment and regulatory work, and it depends on clean, well-modelled data underneath.

The problem

Problems we solve

  • Compound and reaction data scattered across spreadsheets, files and isolated databases
  • Structures represented inconsistently, preventing reliable search and comparison
  • No efficient way to query large compound libraries or screen virtual candidates
  • Predictive models that are not connected back to the data that produced them
  • Regulatory submissions assembled manually from fragmented records

Capabilities

What we build

Compound, reaction and assay data management platforms

Structure representation, standardisation and validation services

Chemical search, similarity and substructure query engines

Data mining, analysis and property prediction workflows

Integration between ELN, LIMS and discovery systems

Regulatory-ready data aggregation and reporting

Toolkit

Technologies & capabilities

  • Chemical toolkits and structure standards
  • Python and R for cheminformatics and statistics
  • Machine learning for property and activity prediction
  • Graph and relational databases for compound networks
  • Cloud data platforms for large libraries

Who it is for

Designed for

  • Pharmaceutical and biotechnology research teams
  • Specialty chemicals and materials companies
  • Agrochemical and flavour/fragrance R&D
  • Contract research organisations

Why UVJ

Why teams choose UVJ for this

01

Chemistry-aware data modelling

We design schemas that understand structures, not just strings, so search, comparison and computation work the way scientists expect.

02

AI where it earns its place

We apply machine learning to property prediction and prioritisation while keeping the underlying data and provenance inspectable.

03

Proven in a rare niche

Cheminformatics demands chemistry domain knowledge, data engineering, AI and regulated architecture together. Few teams hold all four; we have delivered in this niche for years.

FAQ

Frequently asked questions

Why not build cheminformatics software in-house?

It requires a combination that is expensive and slow to assemble: chemistry domain knowledge, data engineering, machine learning and regulatory-compliant architecture. UVJ brings those capabilities together with 23 years of life-science IT experience and a CMMI Level 3 development process.

How does AI and machine learning enhance cheminformatics workflows?

Machine learning supports property and activity prediction, virtual screening, structure-activity analysis and data cleaning. We use it to prioritise and accelerate, while keeping deterministic methods and human review where the decision must be defensible.

Can you integrate with our existing ELN and LIMS?

Yes. Integration with existing electronic lab notebooks, LIMS and discovery platforms is normally part of the engagement, so chemical data stays consistent across systems rather than being duplicated.

Let's engineer what's next.

Tell us about the problem. You will speak with an engineer who understands the domain, not a call centre.