Pharmaceutical Formulations & Delivery

Deliver better medicines through in silico design

Optimize Drug Formulation Process

Optimize your pharmaceutical at the molecular level

A smart, strategic drug formulation can efficiently advance your drug development projects and inform downstream processes. Advances in molecular modeling and machine learning are enabling atomistic-level insights to improve drug formulations and the ability to evaluate large numbers of candidate materials and formulations prior to experiments.

Schrödinger offers a range of computational solutions for advancing pharmaceutical formulation, from crystalline or amorphous form characterization to selection of materials and excipients for processing, formulation, and delivery.

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Intuitive computational workflows designed by experts in formulation chemistry

Easy-to-use system builders for complex formulations of large molecular systems
Powerful workflows for molecular simulation, machine learning, and data analysis
Dedicated customer support and extensive training resources

Key Capabilities

Optimize drug process development and manufacturing with predictive characterization

  • Predict pKa, powder X-ray diffraction and crystal morphology 
  • Calculate Young’s and shear moduli to aid in the optimization of tableting conditions
  • Understand solubility in non-aqueous solvents
  • Simulate spectroscopy including VCD, NMR (solution and solid-state), IR, Raman, and UV-Vis

Understand drug stability and reactivity

  • Predict glass transition temperature and water uptake in amorphous materials, including amorphous solid dispersions
  • Evaluate drug stability with respect to various degradation channels
  • Calculate bond dissociation energy to evaluate chemical stability
  • Design molecular catalysts with automated solutions

Predict solubility of drug candidates

  • Accurately predict solubility of amorphous and crystalline forms to encourage the discovery of a soluble active pharmaceutical ingredient (API) and to delineate the potential solubility boost from non-crystalline forms using FEP+
  • Identify instances where pure drug solubility can exceed the expected solubility due to the formation of small drug aggregates

Characterize and optimize drug formulations and delivery

  • Gain insight into the complex requirements and behaviors of lipid-based and polymer-based formulations, including amorphous solid dispersions
  • Evaluate the impact of different polymers or polymer residues on the release solubilization and aggregation of the API
  • Predict key properties such as hygroscopicity, viscosity and miscibility of ingredients, molecular interactions in solution, and drug release profiles

Crystal Structure Prediction Services

De-risk your solid form selection process by identifying the most stable polymorph at room temperature

Overcome the risks associated with disappearing polymorphs in late stage drug development. For a given active pharmaceutical ingredient (API), we will leverage our proprietary crystal structure prediction (CSP) platform to identify the most stable crystal polymorph at room temperature. Starting from a 2D structure of the API, we deliver to you the thermodynamic stability ranking of crystal polymorphs.

Case studies & webinars

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

Life Science Webinar

医薬品原薬形態開発における計算手法の活用

NOV 26, 2025 | 演者が考える研究段階から開発段階にかけての原薬形態選択の戦略の全体像を概説し、さらにデザインスペースの構築に計算的手法を用いた共結晶スクリーニングと、結晶構造予測による原薬形態のリスク評価の実例を紹介します。

Materials Science Webinar

難溶性薬物の放出メカニズムを解明する – ASD研究の新たなアプローチModelling amorphous solid dispersion (ASD) release mechanisms

AbbVie と Schrödinger のエキスパートが、ASDにおける薬物放出やLoss of Release のメカニズムを、熱力学モデリング・分子シミュレーション・実験研究 を組み合わせた最新の研究成果を基に解説します。

Life Science Webinar

Accelerating pharmaceutical formulations development: A computational approach

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

Life Science Webinar

Innovations in Digital Chemistry: Computational Approaches for Drug & Materials Discovery

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 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.

Life Science Webinar

Modelling amorphous solid dispersion (ASD) release mechanisms

In this webinar, AbbVie and Schrödinger will present the results of a study using a combination of Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) thermodynamic modeling and molecular simulation to investigate the release mechanism and the occurrence LoR of an ASD formulation.

Life Science Webinar

Computational insights into polymer excipient selection for amorphous solid dispersions

In this webinar, we will highlight how molecular models can aid our ability to screen through standard polymer excipients for target lists to push into lab testing.

Life Science Case Study

Advancing lipid nanoparticle development with structure-based modeling platform and services

Life Science Webinar

Accelerating pharmaceutical formulations using machine learning approaches

In this webinar, we will demonstrate how Schrödinger’s integrated ML- and physics-based approaches are transforming pharmaceutical formulation design.

Featured courseMolecular Modeling for Materials Science: Pharmaceutical Formulations

Learn in silico drug formulation methods with our hands-on online certification course

Level-up your skills by enrolling in our online course, Molecular Modeling for Materials Science: Pharmaceutical Formulations.

Learn More

Documentation & Tutorials

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

Materials Science Tutorial

Simulating Complex Protein Solutions

Learn to prepare a complex protein system for a Molecular Dynamics (MD) simulation.

Materials Science Tutorial

Creating a Coarse-Grained Model for Protein Formulations

Learn to use the Coarse-Grained Force Field Builder to automatically fit parameters to the Martini coarse-grained force field for a complex protein solution system.

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 Morph

Efficient modeling tool for organic crystal habit prediction.

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

MS Maestro

Complete modeling environment for your materials discovery

Desmond

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

FEP+

High-performance free energy calculations for drug discovery

MS Morph

Efficient modeling tool for organic crystal habit prediction

MS CG

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

Jaguar

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

Crystal Structure Prediction

De-risk your solid form selection process by identifying the most stable polymorph at room temperature

Publications

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

Software and services to meet your organizational needs

Software Platform

Deploy digital drug discovery workflows using a comprehensive and user-friendly platform for molecular modeling, design, and collaboration.

Modeling Services

Leverage Schrödinger’s computational expertise and technology at scale to advance your projects through key stages in the drug discovery process.

Support & Training

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