IntelDrug's knowledge spans the area of standard drug development to state-of-the-art AI algorithms.

Check which know-how you need.
See the tool list at the end.

Expertise and Experience
at Your Service.

Golden standard in Computational drug design

At IntelDrug, we know over 20 software programs used in virtual screening, drug-target interactions and toxicology.

IntelDrug will study the tools you need and find cost-effective solutions to generate your next clinical candidates.

In drug design, computational scientists developed artificially intelligent methods well before ChatGPT.

Indeed, IntelDrug can innovate your discovery using AI/ML, NPL, designing colorally data pipelines, data mining, Alphafold, 4D QSAR, and more.

We are very passionate about innovation too.

Integration of cutting-edge technology

Predicting ADMET and PKPD with confidence

IntelDrug's computational toxicology expertise goes beyond simple ADME prediction.

Access to over 500 tox data repositories, analysis of reactive metabolites, 16 adverse effect proteins, tox potential index, PK/PD correlation, dose range finding... to cite few.

Special projects

Let us know if you need a consultancy in special areas:

  • Natural substances and botanical mixtures

  • Flavors and taste properties (organoleptic)

  • Inhalable drug research and medical devices

  • Radioactive drugs and biomarkers (anticancer)

  • Nutraceuticals, vet- or agrochemicals

  • Repurposing

  • IP landscaping

  • Complex matrix analytical characterization

  • Healthtech and personalized healthcare

Agile and flexible approach

Experience in managing complex projects at large corporations leaves a mark. We know where the barriers are and what not to do!

IntelDrug's approach is Scrum Agile and Kanban.
We "Sprint" with you while keeping your experts focused.

CADD

  • Packages: MOE, BioVia, ACD/Labs, Schrodinger, Chemaxon, BioSolveIt, OpenEye

  • Databases: ChEMBL, Toxnet, ACToR, PubChem, Reactome, HMDB, ChemBank, DrugBank

  • Toxicity: Lhasa, VEGA, TEST, Leadscope, ECHA, Cosmos, FooDB, VirtualTox

  • Toolbox: OpenBabel, QSAR Toolbox, PP, Knime

  • Simulations: MOE, Schrodinger, MOPAC, Gromos, CHARMM, Amber

  • Ligand QSAR: ChemOffice, MOEsaic, Chemaxon, DataWarrior

  • Networks, Pathways: Cytoscape, GGobi, Noe4j, KEGG,

  • Flavors: EFSA, The Good Scents Co, Leffingwell, SuperScent, Flavornet, FEMA

  • Patents: Espacenet, Chembl patents, WHO, Patent Lens, Google patents

Molecular Design Approaches

  • Screening: docking, pharmacophore, PLIF, induced fit, water, tautomerism

  • Target: SwissTarget, target hunting, MDS, MOA, homology, hot spots

  • Parameters: 2D and 3D descriptors, phys-chem properties

  • Lead optimization: golden triangle, sweet spot, biosimilars mapping, drug-like

  • AI/ML: QSAR, ML-QSAR

  • Pharmacology: metabolites, ADME, metabolites prediction, toxicity prediction, PKPD

  • Analytical chemistry processes (GC/LC-MS), bioinformatics, radiology

Information Technologies

  • Databases SQL: PostgreSQL, Oracle, SQL Server

  • Databases NoSQL: Neo4J, MongoDB, ArangoDB

  • Websites: Angular, React, VainillaJS, VueJS

  • Desktop programming: C#, Java, Python

  • Infrastructure: On-premises, Cloud, Dockers, microservices, web services

  • Improvements of existing applications: CxP and non-GxP, data ingestion processes (ETL)

Project Management

  • Agile PM: Scrum, Kanban, JIRA, Monday, Trello, Slack, Motion AI

Tools and Methods in detail.