In silico/bioinformatics tests

In silico/bioinformatic test

Alidans uses advanced technologies such as bioinformatics, artificial intelligence (AI), mathematical models and computational simulations to optimize the development, safety and efficacy of products in the cosmetic, food, medical devices and chemical sectors.

Techniques Used

Bioinformatics: Analysis of large amounts of biological and chemical data, modeling interactions at the molecular level. It includes computational proteomics and metabolomics to study the protein and metabolic profile of substances, and structural bioinformatics to predict the three-dimensional structure of proteins or molecules.

Artificial Intelligence (AI): Machine learning, deep learning and QSAR models to predict the toxicity, efficacy and behavior of substances. Natural Language Processing (NLP) techniques are used for the analysis of scientific and patent texts.

Molecular Modeling: Molecular docking and molecular dynamics to simulate interactions between substances and target proteins.

Simulations and Mathematical Modeling: ADME, PK/PD models and Monte Carlo methods to simulate the fate of substances and optimize formulations.

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Pratical applications in different sectors

Cosmetics

Botanical extraction optimization: Machine learning algorithms identify optimal parameters (temperature, solvents, duration) to maximize the efficacy of extracts.

Evaluation of ingredient biodegradability: QSAR models and in silico simulations estimate the environmental impact of ingredients.

Simulation of skin penetration: ADME models simulate the absorption of active ingredients to ensure safety and efficacy.

Formulation optimization: Genetic algorithms improve product texture, absorption and efficacy.

Evaluation of toxicological effects: Predict skin and ocular toxicity with QSAR models, avoiding animal testing.

Simulation of formulation stability: Monte Carlo methods and molecular dynamics predict stability over time.

Personalization of treatments: Machine learning to adapt treatments to different skin types.

Simulation of molecule-protein interaction: Molecular docking to improve anti-aging and moisturizing products.

Food Industry

Optimization of food supplement formulations: Evolutionary methods and chemometric techniques improve stability, flavor, and absorption.
Safe dosage assessment: ADME and QSAR models predict safety at specific dosages.
Threshold of Toxicological Concern (TTC) calculation: QSAR Toolbox assesses the safety of substances by reducing in vivo testing.
Prediction of chemical-physical properties: Molecular models estimate solubility, thermal stability, and compatibility between ingredients.
Simulation of shelf life: Monte Carlo methods predict nutrient degradation and shelf life.
Nutrigenomics and nutrition personalization: Machine learning to personalize diets based on genetic profile.

Medical Devices

Prediction of toxicological and immunological effects: QSAR models for the assessment of toxicity and immunological effects.
Simulation of interaction with biological tissues: Molecular dynamics to simulate material-tissue interactions.
Biomechanical Properties Prediction: Mathematical simulations to assess material strength and compatibility.
Design Optimization: 3D simulations and AI to improve the design and compatibility of implantable or wearable devices.
Drug Absorption and Release: PK/PD models simulate controlled drug release and distribution.
Safe Dosage Assessment: ADME and PK/PD models determine the maximum safe dose for substances in devices.

Chemicals

Safety Data Sheets: Computational models compile regulatory-compliant safety data sheets.
Toxicity and Biodegradability: QSAR and EPISuite models to predict acute and chronic toxicity, and biodegradability.
Chemical Synthesis Optimization: AI reduces byproducts and production times.
Environmental Impact Assessment: Predictive models estimate the effect of substances on ecosystems.

Thanks to the integrated use of bioinformatics techniques, computational models and artificial intelligence, Alidans is able to offer innovative solutions that improve the safety and efficacy of products, reducing the need for experimental tests and accelerating the development process in various industrial sectors.

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