Do you face any of these challenges?
- Looking to apply simulation technologies to drug discovery or pharmaceutical formulation research but unsure how to proceed
- Wanting to adopt data-driven approaches in pharmaceutical R&D but hindered by a lack of skills or data
- Seeking to accelerate collaborative development with peers or cross-industry partners by leveraging DX-based technologies
Advanced Software and Expert Support for Achieving DX in Drug Discovery and Formulation
JSOL offers a comprehensive portfolio of simulation and AI technologies essential for driving digital transformation (DX) in pharmaceutical R&D, covering the wide range of functions and techniques required in both drug discovery and formulation. Applications include modeling protein–ligand interactions, simulating molecular binding kinetics, predicting solubility and stability, optimizing crystallization processes, and using AI for virtual screening and formulation optimization.
Software package is designed for ease of use, and our expert support services—built on extensive experience—help even first-time users quickly integrate these tools into their work and research.
JSOL’s solutions are trusted by pharmaceutical companies, contract research organizations, and research institutions worldwide. By leveraging our network and platform, we provide opportunities for user-to-user communication and collaboration directly through JSOL’s software. When required, JSOL can also coordinate and support the creation of research frameworks that bring together companies, universities, and other partners—empowering joint innovation in drug discovery and pharmaceutical development.
Integrated Solution for Multiscale Simulation and Data Science
- 01. Proven Track Record in Industry and Academia
- 02. Software for Multiscale Simulation
- 03. Software for Materials Informatics
In the pharmaceutical industry, spanning both drug discovery and formulation, there is a growing demand for digital transformation (DX) across diverse areas of research and development. In drug discovery, evaluating various modalities, and in formulation, assessing material properties or designing drug delivery systems, requires considering multiscale phenomena and employing a wide range of specialized methods and technologies. Other relevant applications include modeling protein–ligand interactions, simulating molecular binding kinetics, predicting solubility and stability, optimizing crystallization processes, and leveraging AI for virtual screening and formulation optimization.
JSOL offers a broad portfolio of simulation and AI technologies essential for pharmaceutical R&D, covering many functions and techniques needed in both drug discovery and formulation. Each software package is designed for ease of use, and our expert support services—built on extensive experience—help even first-time users quickly integrate these tools into their work and research.
Our software is used by pharmaceutical companies, contract research organizations, and research institutions around the world. By leveraging this network, we provide opportunities for user-to-user communication and collaboration directly through our software. When required, JSOL can also coordinate and support the creation of research frameworks that bring together companies, universities, and other partners—empowering joint innovation in drug discovery and pharmaceutical development.
01Proven Track Record in Industry and Academia
02Software for Multiscale Simulation
In pharmaceutical R&D—covering both drug discovery and formulation—it is essential to consider which scale of phenomena most strongly influences the final outcome, ranging from molecular structures at the nanometer scale (e.g., protein–ligand binding affinity, drug solubility) to molecular assemblies and phase-separated structures at the hundreds-of-nanometers scale (e.g., lipid membranes, lipid nanoparticles [LNPs]).
Because no single simulation technology can cover such a wide range of scales and phenomena, JSOL offers solutions designed to address multiscale challenges. These software tools encompass the simulation technologies required for analyzing the broad multiscale characteristics found in drug discovery and formulation.
Furthermore, since the volume of experiments needed during the design phase can become enormous, simulation technologies can also be leveraged to facilitate data accumulation and reduce experimental burden. For more information, please refer to the software product websites.
03Software for Materials Informatics
J-OCTA MI-Suite includes machine learning capabilities for predicting material properties using molecular/crystal structures and various conditions as explanatory variables, along with related features such as molecular descriptor calculations, access to public databases, and analysis of each variable’s contribution.
When experimental data are insufficient, the software can supplement them with simulation results. It also provides API functionality to support database construction using physical simulations.
Data selection and learning condition settings for machine learning can be performed via dialogs, without the need for programming. Multiple pre-trained models are included, allowing users to start Materials Informatics projects even without their own data.
Use Cases
