At ISMD, we undertake research and consultancy in new product development, as well as discoveries around finding new materials, new compounds, and new uses at the molecular level. This includes areas such as new active leads for drug development and nutraceuticals, food and drug toxicology, metabolite prediction and fragrance and flavour research among others.
With over 30 years of experience, combining domain expertise and wet lab experience with state-of-the-art cheminformatics tools (such as cluster analysis and pattern recognition), ISMD are enabling breakthrough discoveries and delivering powerful, tailored solutions to meet our clients’ unique needs.
Although primarily operating in the virtual world, our approaches are firmly grounded in practical outcomes — transforming conceptual ideas and hypotheses into wet lab environments for validation and real-world application. Focused and solution-driven, we excel at problem-solving and deliver highly innovative, practical solutions to our clients’ most complex challenges.
Below are just some highlights of what we offer — see Full List of Services
Small dataset analysis
In an era of big data, researchers often face data overload, making it difficult to extract meaningful insights.
We specialise in small dataset analysis, where focused, high-quality data allows for more manageable and interpretable inferences.
By leveraging over 30 years of expertise in organic chemistry, 2D/3D molecular analysis, cheminformatics, and AI-driven approaches, we uncover hidden opportunities even in deeply mined, exhausted, or retired datasets. This enables the discovery of new and valuable leads that others may overlook, enhancing drug and molecular discovery through precision-driven analysis rather than sheer data volume.
Evolution and dataset creations, all sorts
We use a number of evolutionary techniques where molecular structures can “evolve” through virtual mutation and selection based on fitness criteria (e.g., drug-likeness, binding affinity). It’s a way of creating new virtual molecules but with certain restrictions such as limiting the molecular weight and molecular complexity ranges and “growing them” into new virtual chemical structures. Below is a dynamic example:
Starting with an alkaloid (compound A) on top as the “seed compound” we create a selection of virtual molecules based on various evolutionary fitness criteria that progresses (middle image) to a difluorinated derivative (compound B) on bottom.
The evolutionary phase can generate 1000s or billions of potential new virtual compounds which can be probed further to find useful and interesting functionality.
Full List of Services
Activity Cliffs Analysis
Alkaloids
Artificial Natural Products (ANPs)
Bespoke extracts
Evolution and novel datasets
Molecular docking
Natural Products predictive toxicology and safety assessments
Patent Analytics
Pattern recognition studies
Pharmacophore scaffold hopping and Target hopping
Pseudo-Natural Products (PNPs)
Prediction of new natural products
Similarity searches
Small and Retired Datasets
Sourcing of plants
Synergy effects
Virtual library creation
Contact Us