quiid[hub] is fit for
multiple industries
multiple use cases
unlimited fields of applications
Our insilico solutions are flexible enough to extract value from your data across various applications.
multiple industries
Biotech, Pharmaceuticals, Nutrition, Cosmetics, Home and Personal Care, Retail, Agritech, Chemicals...
various departments
Research & Development, Sales, Marketing, Logistics, Human Resources, Business Intelligence...
Diverse Use cases
Biomarker Discovery, Structural Alert Detection, Product Claims, Profiling, Chemical Safety...
quiid[hub] covers multiple use cases
chemical toxicology:
cosmetics & pharma safety
During the development of novel pharmaceuticals drugs or cosmetics, hazard assessment is a critical step. The development of chemicals now requires scientists to fill data-gap. For the formulators to tackle this problematic, they must use a pluridisciplinary approach that respect the regulations and recommendations of authoritative bodies. Besides, animal testing has been strongly reduced and classical investigation (in vitro, in cellulo) are not sufficient by themselves for toxic assessment anymore. Furthermore, because multiplying classical experimentation is time and money consuming, we created a decision-support system named QUIID[CHEM] for toxic hazard assessment.
QUIID[CHEM] aims at optimising your development process by providing a decision-support system, which helps you to shortlist the best chemical candidates during read-across processes. QUIID[CHEM] helps scientists to early predict structural alerts related to toxic properties or any other endpoints (e.g., sensitisation, carcinogenic, mutagenic, or metabolic properties…). The targeted properties of the queried chemicals are predicted using datamining methodologies applied to chemical databases (public and/or private databases). Our predictions allow you to anticipate toxic issues along the drug design phase, leading you to scale up your productivity.
Related publications :
use quiid[hub] for chemical analytics
FormulAtion:
cosmetics and raw materials
Formulation is the art of mixing synthetic or natural raw materials in order to create a final product, characterised by distinct functional properties and that fits the specifications. Therefore, formulation is a key step involved in various material processing industries (cosmetics, agrifood, pharma, adhesives, painting, detergents, concrete,etc…) from upstream (raw material synthesis) to downstream industries in touch with customers (makeup, nutrition).
Formulation is a subject of concern for the Chemical industry because they create active ingredients as well as formulation auxiliaries, which are marketed more for their functional attributes (thickener, UV filter , dye, moisturiser) than their chemical properties (molecular structure, purety, etc…). Downstream industries that formulate for the final customer need to create even more complex formulas. Indeed, diverse raw materials are associated in order to design a ready-to-use product which possesses specific commercial properties and performances. In the end, the formulation revolves around all the application of chemical, natural or synthetic compounds. The goal is to find the best compromise between performance, cost and safety.
QUIID[HUB] helps you create well balanced formulas by giving you the opportunity to reveal new insight, to make smart formulation and also to predict the properties (physical or even hedonic) of your final product. Using QUIID[HUB] for formulation provides you with a strong support to fit your product specifications and to develop innovative formulas in an eco-conception approach.
use quiid[hub] for formulation
biomarker discovery:
metabolomics
Metabolomics, the science of metabolites analysis, is an emerging and promising technology that aims at identifying complex metabolic signatures and pathways. Metabolome profiling contributes towards a better understanding a human physiology by giving us a functional readout of cellular biochemistry. That is why the identification of specific biochemical fingerprints is a key step to tackle common problematics within the (pre)clinical studies and healthcare industry (e.g., biomarkers for diagnostics, treatment’s response, precision medicine…).
Historically, small numbers of metabolites have been used to diagnose complex metabolic diseases as well as monogenic disorders such as inborn errors of metabolism. However in the last decades, emerging technologies (such as proteomic methodologies or high througtput sequencing) have continuously generated complex and considerable amount of data about the metabolome, meanwhile the solutions for analysing those datasets are not efficient as well.
QUIID understands your needs and provides you with solutions to tackle metabolomics problematics. We are able to apply our technology on any subset of metabolic data to unveil hidden correlations between variables (e.g., metabolite interactions, dose effect, pronostical model, pathfinding). QUIID helps you to deeply analyse your existing metabolomics data, and also provides a heavy support and fully understandable outputs.
Related publications :
use quiid[HUB] for life sciences
your activity
No matter your industry, activities and applications, do not hesitate to contact us to find out how we can help you exploit the full potential of your data thanks to our in silico solutions.
We’re looking forward to hearing from you!