Harness molecular simulation to accelerate innovation for consumer goods

Consumer Packaged Goods

Overview

Molecular modeling and simulation provide new opportunities to accelerate R&D product development, rationalize  behavior at the nanoscale, optimize manufacturing processes, and reduce costs by offering insights into the atomic-level properties that impact product performance.

With Schrödinger’s digital chemistry platform, you can access extensively validated tools to predict key performance indicators for consumer products. By building and simulating complex molecular systems that directly relate to product formulas, you can make informed decisions and create game-changing ingredients and products in response to the rapidly changing trends in consumer goods markets.

Design, develop, & optimize for a full range of consumer products

Consumer Goods

Meet consumer demands with molecular-level insights

Predict physicochemical, morphological, optical, interfacial, and sensory properties for:

  • Ingredient selection
  • Product formulation development, modeling complex formulations with all the critical ingredients 
  • Optimization of processing conditions at multiple scales, from bench to pilot plant to factory
  • Product stability by studying product-packaging interactions
  • Product performance by modeling products in action
Food & Beverage

Enable rational design of healthier, tastier foods

Your ability to design the next generation of sustainable food starts at the molecular level

  • Understand how ingredient interactions and product stability impacts shelf life by predicting degradation, compatibility, and phase behavior
  • Optimize food and beverage processing conditions by looking at phase behavior, pressure, and temperature
  • Study how proteins interact with ingredients and how unfolding affects food texture
  • Understand the molecular basis of odor and flavor molecular activation
  • Study the behavior of micro- and nano-emulsions
Cosmetics & Personal Care

Transform cosmetic and personal care product development with digital chemistry

Accelerate product formulation design by leveraging virtual testing of product performance at the nanoscale

  • Computationally explore formulation design space of cosmetics, fragrance, and personal care products before running experiments
  • Predict chemical and optical stability of ingredients and explore their degradation
  • Understand complex emulsion behavior and stability at multiple scales including morphology
  • Mimic product testing using biological interface models to gain insight to a range of properties (physical to sensory)
  • Derisk bio-based drop-in replacement ingredients using physics-based simulations to ensure compatibility and product performance
Cleaning Products

Design sustainable, efficient cleaning products at the molecular level

Transform cleaning product development with digital chemistry

  • Gain molecular insight into antimicrobial mode action that mimics experiment (i.e. electroporation of microbial membranes with antimicrobial actives)
  • Design next-generation, sustainable active ingredients
  • Predict performance on different surfaces like fabrics and hard surfaces
  • Develop machine learning models for assessing safety (e.g. toxicity)
Packaging Materials

Accelerate the development of sustainable packaging materials

Leverage powerful digital simulations to accelerate discovery of novel packaging materials

  • Understand chemical compatibility between packaging and product ingredients and formulations
  • Virtually test the key properties of new sustainable packaging materials (mechanical, transport properties, moisture sensitivity)
  • Perform life cycle assessment analysis of packaging materials
  • Gain novel insights into product-packaging interactions and how they affect shelf life

Case studies & webinars

Discover how Schrödinger technology is being used to solve real-world research challenges.

Materials Science Webinar

Accelerating Product Development: The Industrial Shift to AI/ML-Driven Formulation

In this discussion, we explore the rapidly evolving role of modeling and machine learning in formulation design; from a supplementary tool to a driving force of innovation.

Materials Science Webinar

Accelerating materials discovery with physics-informed AI/ML

This webinar series will explore how cutting-edge computational methods are revolutionizing the design and optimization of pharmaceutical drugs, biologics , and advanced materials.

Materials Science Webinar

Advancing machine learning force fields for materials science applications

In this webinar, we will introduce Schrödinger’s state-of-the-art MLFF architecture, called Message Passing Network with Iterative Charge Equilibration (MPNICE), which incorporates explicit electrostatics for accurate charge representations.

Materials Science Case Study

Advancing sustainable food processing through integrated experimental and molecular simulation approaches

Scientists from Schrödinger and UMass carried out comprehensive studies experimentally and computationally to investigate the key properties and extrusion performance of zein-formulated meat alternatives.

Materials Science Webinar

Accelerating chemical innovation with AI/ML: Breakthroughs across materials applications

In this webinar, we will explore how AI/ML is driving impactful advancements in materials innovation, highlighting case studies that illustrate cutting-edge ML techniques in diverse applications.

Materials Science Webinar

AI/ML-Powered Formulation Design: Accelerating Innovation

Schrödinger is excited to be hosting a webinar with C&EN on May 29th.

Materials Science Case Study

The Future of Food: Molecular Simulations and AI/ML Reshaping Product Development

Materials Science Webinar

High-performance materials discovery: A decade of cloud-enabled breakthroughs

This talk will showcase how Schrödinger’s integrated materials science platform enables massive parallel screening and de novo design campaigns across diverse applications.

Materials Science Webinar

Virtual testing of personal care and cosmetics formulations using digital chemistry methods

FEB 19, 2025 | ケーススタディを通じて、計算化学が製品開発、容器設計、製品使用時の解析にどのように役立つかを示します。

Materials Science Webinar

AI/ML meets physics-based simulations: A new era in complex materials design

In this webinar, we demonstrate the application of this combined approach in designing materials and formulations across diverse materials science applications, from battery electrolytes and fuel mixtures to thermoplastics and OLED devices. 

Featured courseMolecular modeling for materials science applications

Molecular modeling for materials science applications: Consumer packaged goods course

Online certification course: Level-up your skill set in consumer goods product modeling

Learn how to apply Schrödinger’s industry-leading software to predict key properties of simple and complex material formulations for consumer goods with automated workflows and machine learning models.

  • Self-paced learning content
  • Hands-on access to Schrödinger software
  • Guided and independent case studies
Learn More

Documentation & Tutorials

Get answers to common questions and learn best practices for using Schrödinger’s software.

Materials Science Tutorial

Optimizing Viscosity and Cost in Formulations with Missing Structural Data

Learn to build a machine learning (ML) model to predict cost and viscosity of shampoo formulations with missing structural data.

Materials Science Tutorial

Building and Analyzing a Complex Lipid Bilayer and Embedding a Membrane Protein

Learn to build and analyze a complex lipid bilayer and how to embedd a protein.

Materials Science Documentation

Complex Bilayer Builder Panel

Build single or multi-component lipid membranes with or without an embedded membrane protein.

Materials Science Documentation

Membrane Analysis Panel

Calculate structural properties for a lipid membrane over the selected frames of a trajectory.

Materials Science Documentation

Membrane Analysis Viewer Panel

View plots of the structural properties of a lipid over the course of a molecular dynamics trajectory, generated using the Membrane Analysis panel.

Materials Science Documentation

Machine Learning Force Fields

Machine Learning Force Fields (MLFFs) offer a novel approach for predicting the energies of arbitrary systems.

Materials Science Tutorial

Machine Learning Force Field

Learn how to use machine learning force field optimization methods to prepare and simulate various systems.

Materials Science Documentation

MS Transport

Efficient molecular dynamics (MD) simulation tool for predicting liquid viscosity and diffusions of atoms and molecules.

Materials Science Documentation

MS Penetrant Loading

Molecular dynamics (MD) modeling for predicting water loading and small molecule gas adsorption capacity of a condensed system.

Materials Science Documentation

MS Informatics

Automated machine learning tools for materials science applications

Key Products

Learn more about the key computational technologies available to progress your research projects.

Formulation ML

Automated machine learning solution to generate accurate formulation-property relationships and screen new formulations with desired properties

Virtual Cluster

Secure, scalable environment for running simulations on the cloud

Jaguar

Quantum mechanics solution for rapid and accurate prediction of molecular structures and properties

MS Penetrant Loading

Molecular dynamics (MD) modeling for predicting water loading and small molecule gas adsorption capacity of a condensed system

Desmond

High-performance molecular dynamics (MD) engine providing high scalability, throughput, and scientific accuracy

MS CG

Efficient coarse-grained (CG) molecular dynamics (MD) simulations for large systems over long time scales

OPLS4 & OPLS5 Force Field

A modern, comprehensive force field for accurate molecular simulations

DeepAutoQSAR

Automated, scalable solution for the training and application of predictive machine learning models

MS Transport

Efficient molecular dynamics (MD) simulation tool for predicting liquid viscosity, conductivity and diffusions of atoms and molecules

Publications

Browse the list of peer-reviewed publications using Schrödinger technology in related application areas.

Shearing Friction Behaviour of Synthetic Polymers Compared to a Functionalized Polysaccharide on Biomimetic Surfaces: Models for the Prediction of Performance of Eco-designed Formulations

Coscia B.J. et al. Polym. Degrad. Phys. Chem. Chem. Phys., 2023,25, 1768-1780

Exploring the Effects of Wetting and Free Fatty Acid Deposition on an Atomistic Hair Fiber Surface Model Incorporating Keratin-Associated Protein 5-1

Sanders J.M. et al. ACS Appl. Langmuir 2023, 39, 15, 5263–5274

Brewers’ spent hop revalorization for the production of high added-value cosmetics ingredients with elastase inhibition capacity

Scientific Reports, 2022, volume 12, Article number: 22074

Schedule a demo on Schrödinger CPG solutions

Contact us today to discuss how you can leverage molecular modeling and AI/ML to stay ahead in today’s fast-evolving consumer goods market.

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Software and services to meet your organizational needs

Software Platform

Deploy digital materials discovery workflows with a comprehensive and user-friendly platform grounded in physics-based molecular modeling, machine learning, and team collaboration.

Research Services

Leverage Schrödinger’s expert computational scientists to assist at key stages in your materials discovery and development process.

Support & Training

Access expert support, educational materials, and training resources designed for both novice and experienced users.