Molecular Modeling Services
molecular modeling services
Scientific Software Development Services
Scientific Software Development Services
Corporate Alliances & Partnerships
Corporate Alliances & Partnerships

Over the last 10 years, Intelligent Pharma has acquired extensive experience in scientific software and solutions development specific to the needs that arise during research & development. As a life sciences company ourselves, we understand first-hand the data and technologies our clients use and the challenges they face.

We work with technologies that intensively use computational resources. Some examples are virtual screening of molecules, molecular dynamics, and Deep Neural Networks (DNNs). Our team has extensive experience in the use of supercomputing (HPC) by using our own in house supercomputer or the cloud (or a combination of both).

With communication and flexibility as core values, and using Agile methodologies, our team can create solutions specific to the needs of life sciences companies. Furthermore, our IT team is composed out of engineers and doctors in Computer Science, guaranteeing a high quality, professional, maintainable and scalable software. Your project will also benefit from a close collaboration between our IT team and the other departments present at Intelligent Pharma (chemists, biologists…).

The research process involves the generation of a large amount of heterogeneous data. Intelligent Pharma has multiple tools at its disposal in order to delve into this data, organize it, and create specific solutions for its unification, management, analysis, and subsequent knowledge extraction.

Big data is an extremely powerful tool that allows you to perform simulations and predictions in very diverse areas. We can take your data sets and objectives and design and implement a data mining strategy using cutting edge methodologies and tools. Talk to us!

Some examples of our work include an intelligent search solution for managing preclinical oncology model databases, analogous identification in a petrochemical database and a wide range of solutions for managing and analyzing chemical compounds. These are described in more detail below:
Oncology models portfolio management tool

Our client required a very intuitive web application that would allow customers to easily find and compare data (gene expression, mutations, tumor characteristics, histology images and standard of care data) of preclinical murine oncology models and display this information in a simple and interactive way, to facilitate the selection of the most appropriate model for the customer’s research.

The main challenge of this project was that the model information was located in heterogeneous data sources, and the client required a single point of entry into these data sources.

The solution that we created was able to abstract the model information from the different data sources, index them, and implement a complex search engine among the data sources to compare and analyze them using a simple graphical interface. The result was a simple google-like interface that allows customers to execute simple searches in order to locate specific and relevant model information, regardless of the complexity of the parent databases.

Furthermore, the solution included a business intelligence module that tracked user search and usage information (such as search frequency, searches without results) to help drive the business strategy, understand better the customers´ needs and allow sales representatives to offer training and support.

Petrochemical reservoir databases management tool

The goal of this project was to unify a large number of heterogeneous petrochemical reservoir databases into a single database which could detect analogous reservoirs among the different databases, manage upgrades and eventual changes in the data model, perform statistical analyses of the data, and generate reports.

This project also included unit detection and standardization, synonym management, configuration of custom validation functions for the data, and users and roles management.

The solution was a usable and intuitive web application over a relational database.

Chemical compounds management tool

The aim of this project was to create a simple compound management tool which could compile results from experiments over a number of compounds developed by different companies in an international collaboration research project.

The tool was a web application over a relational database that allowed the creation, modification, and deletion of compounds, while also being able to perform physical property calculations and statistical analysis. The tool also provided the functionality of managing users, roles, and permissions over the view of compounds and the operations therein.


One characteristic that distinguishes our computational services from other providers is our foundation consisting of internally developed solutions. Our IT team at Intelligent Pharma uses all its artificial intelligence and statistical skills to collaborate with scientists and develop state-of-the-art scientific software, especially in the field of computational chemistry.

Our internal solutions include virtual screening solutions, QSAR modeling and prediction tools, a hit to lead technology based on genetic algorithms, and a polypharmacology prediction tool.

These are some examples of our flagship software solutions. You can find more details HERE.

PYTHIA is a platform for polypharmacology prediction. PYTHIA is a standalone web-based computational technology that predicts targets and indications for molecules and mixtures.

Our software development team works side by side with our chemists and biologists to incorporate into PYTHIA many interesting state-of-the art features such as:

  • Automatic curation of the ChEMBl database and ability to update to new versions.
  • Design and implementation of a friendly and intuitive interface, to make usage and interpretation of the results easy and generation of attractive reports.
  • Web-based architecture based on tokens to allow multiple concurrent users, database optimization to make searches fast and with low resource consumption.
  • Integration of features such as a molecule searcher tool, a compound drawer, substructural filters, similarity calculation with multiple type of fingerprints and more!
  • Possibility to execute batch processes.
  • Workspaces to save user information and configuration and history of experiments.

Hybrid Computational Chemistry Platform

Our internal Computational Chemistry Platform is in the center of the computational services of the company. Developed for over 6 years, it is able to perform virtual screening experiments, QSAR models and predictions and generate all types of analysis and reports. Besides, an automatic planning system proposes optimal execution scheduling to allow the user to choose whether the calculations are run in our own supercomputer, in the cloud or in an hybrid solution.

  • Most of the computational chemistry solutions integrated in one single platform, that allows to configure and launch experiments and study the results with a wide range of statistical tools.
  • Web based modular architecture to grant the security of the data and allowing to easily integrate new technologies and tools.
  • QSAR platform with different statistical models to choose: from PLS to SVM, from single response to multiresponse.
  • All the technologies might be run in our internal supercomputer or in the cloud. An intelligent scheduling agent will propose the optimal configuration based on budget and time restrictions.


MOBIUS is a novel approach to lead optimization based on genetic algorithms. MOBIUS fosters interactions between computational and medicinal chemistry to produce a new approach to address the challenges of Lead Optimization and enables faster identification of potential drug candidates.

MOBIUS is a standalone java based software that combines an attractive and intuitive interface with a great flexibility in the evaluation of compounds and the possibility to generate and navigate through combinatorial libraries.

  • Generation of fragment based compound libraries.
  • Simultaneous optimization of different parameters measured by different evaluation tools. These tools can be externally provided, such as pharmacophore, or internally developed, such as 3D virtual screening solutions or QSAR predictions.
  • Intuitive interface that allows the user to navigate through the compounds and rate them, export them and generate reports.
  • Possibility to navigate through all the experiments generations, to stop and resume experiments and create new ones based on the results of previous runs.

Grid Independent Molecular Interaction Fields

Grid Independent Molecular Interaction Fields are three dimensional descriptors which allow a 3D-structure-quantitative analysis of compounds. 3D-QSAR models based on GIMIF are more interpretable and efficient, as no preliminary alignment of compounds is required and direct correlation between functional groups and descriptors is available. Intelligent Pharma validated these 3D descriptors for its own models and performed a hepatoxicity model of CYP450, with a R2= 0.78 and a Q2=0.81.


Prometheus is a tool that combines the creation of de novo compound libraries with artificial learning and evolutionary computation to explore new chemical spaces and create new and revolutionary drug candidates. Prometheus takes into account different parameters when optimizing compounds, such as their synthesizability or drug-likeness, and also has the flexibility to use other more specific evaluation functions, such as molecules activity against a particular target.


Nowadays, researchers have vast amounts of data at their disposal. This data comes from both freely available sources and privately owned databases. Moreover, this data can contain key insight into the drug discovery process that might not be easily assessed by mere observation. Machine learning techniques present themselves as the ideal tools for this kind of task, being able to extract the underlying structure of data. This knowledge can be then applied to prediction tasks.

Our expertise includes support vector machines, PLS, deep learning, and random forests for tasks such as QSAR modelling, prediction of the mechanism of action of molecules, and predictions of drug-drug interactions.


This technology allows us to build QSAR models from a variety of descriptors and mathematical methods. The descriptors supported by the technology are rCDK, ECFP and GRINDs, among others. Support vector machines (both regression and classification) and partial least squares methods are included in this technology.

Mechanism of Action (MoA)

Our technology PYTHIA, can predict the mechanism of action of chemical compounds thanks to a model based on Deep Learning. The model is trained on millions of activities registered between hundreds of thousands compounds and thousands of targets. This model allows us to predict the activity (or lack of) of a compound against around two thousand targets.

Drug-Drug Interactions (DDI)

Currently in the research phase, this new technology will allow the prediction of drug-drug interactions between a drug candidate and already approved drugs. To do so, we are training a machine learning model with drug-protein interaction data (from sources as ChEMBL, PubChem, AEMPS, etc), as well as metabolic pathway data extracted from the Reactome database.


With core values consisting of effective communication and flexibility, and an attitude towards an agile methodology of development, Intelligent Pharma is able to create solutions specific for the needs of the different stages of the research process, offering usable and professional technologies.

By a thorough analysis of your needs, we propose a software solution and interface design that fits best to your needs. Our solutions are reusable and maintainable. We work together with you during the development process to guaranty a solution as you envisioned. Once finalized, the solution is deployed over the internet or installed in your internal infrastructure, ready to use.