The Early Challenges of Computational Chemistry - Celebrating the 25th Anniversary of Materials Studio -
Since the birth of computers in 1946, their use in chemistry has progressed, with applications including quantum chemistry calculations and reactor analysis. In the late 1980s, the introduction of computer graphics accelerated development beyond chemistry to a wide range of academic and industrial fields. This lecture will look back on the visualization research that began in 1987 and has led to collaborations with various fields, including automobiles, semiconductors, the environment, and nuclear power, since the 1990s. Specific examples will be used to introduce the results and significance of these efforts.
"The Early Challenges of Computational Chemistry - Celebrating the 25th Anniversary of Materials Studio"Computers, which were invented in 1946, have made advances in the field of chemistry, in areas where numerical calculations are important, such as quantum chemistry and chemical reaction device analysis. However, with the addition of computer graphics (CG) to computer chemistry from the late 1980s, developments in a variety of academic and industrial fields that had previously had little connection with chemistry have also accelerated.The speaker began research using CG in 1987 while he was an assistant professor at Kyoto University, and realized the impact of visualizing knowledge and information using CG. During his time as a professor at Tohoku University from 1992, he developed and utilized various methods of computational chemistry to promote collaboration with various academic and industrial fields, including automobiles, semiconductors, the environment, and nuclear power. He will present the results and significance of these efforts in as much detail as possible.
[Volume to Value, Scaling Compliance and Productivity: Our BIOVIA ONE Lab Journey] As a leading generics organization, Ipca manages a diverse portfolio of high-volume products while adhering to multiple global regulatory standards. To remain competitive and future-ready, digitization has become a strategic imperative. In this transformation journey, Ipca has adopted BIOVIA ONE Lab as its digital QC lab platform to streamline operations, ensure compliance,
and drive efficiency.
Jason BENEDICT is the Vice President of R&D and CEO, BIOVIA brand of Dassault Systèmes. He is a broadly experienced software industry executive with more than 15 years of experience building rigorous internal company processes and high-performance teams supporting the development, quality assurance, and lifecycle management of scientific software products. As vice president of R&D, Mr. BENEDICT is responsible for the full BIOVIA product portfolio—defining and directing scientific software development strategies supporting molecular modeling/simulation, data science, scientific and laboratory informatics, formulation design, quality/compliance, and manufacturing analytics solutions that advance collaborative innovation for science-based industries. In his current role as CEO of BIOVIA, Mr. BENEDICT has assumed overall responsibility for Finance, Marketing, Sales, Services, and Customer Success. Prior to becoming VP R&D, Mr. BENEDICT served as director, solutions consulting, Accelrys (2004-2008); principal architect, R&D, Accelrys (2008-2013); and senior director, software development, BIOVIA (2013-2016). Mr. BENEDICT is a graduate of Carnegie Mellon University with a degree in Chemical Engineering.
【Modeling & Simulation】"Materials design and measurement data analysis using generative AI and machine learning potential"In recent years, materials development utilizing machine learning has progressed rapidly. Machine learning potentials (MLPs), proposed by Behler and Parrinello in 2007, have been developed as a method that enables highly accurate and fast atomic-scale simulations, and in recent years, pre-trained general-purpose potentials (e.g., MACE) that can handle almost all elements in the periodic table have also appeared.On the other hand, generative AI, such as ChatGPT and Stable Diffusion, has also become widespread, and the application of these technologies to reverse design of materials and data analysis is attracting attention. In this presentation, we will introduce the ferroelectric simulation under electric fields using machine learning potentials, which the presenter's research group has been working on in recent years, as well as methods for reverse design of materials and analysis of measurement data using generative AI.
【Computational Insights in CO2 Capture: An Industrial Perspective】「Atomistic and Molecular Mechanistic Insights- Designing Efficient Processes」
Development of sustainable and efficient processes is a desired interest for industries. Understanding key technological bottlenecks in the process is thus essential. Molecular and atomistic scale simulations and computation provide key insights into chemical transformations. These lead towards actions associated with new material discovery, process optimization and eventually to enhanced yields. During the talk, three examples will be shared on how we utilize these approaches to optimize catalysts, screen new materials and evaluate process enhancement. The talk will reference how these approaches are being used to address and build decarbonization solutions.
【Modeling & Simulation】"Evaluation of magnetic degradation of soft magnetic material FeCo-V using a multi-scale, multi-physics approach: GRIT (grit) x first-principles calculations for material design (first-principles analysis)"In this presentation, I will introduce the evaluation of magnetic degradation in an FeCo-V alloy as an example of the application of a multi-scale, multi-physics approach in the field of soft magnetic materials. By combining elastic stiffness analysis and micromagnetic simulation, I analyzed the magnetic flux density-magnetic field (B-H) curve and the magnetic flux density-magnetostriction (B-ε) curve, and found that pre-straining leads to a decrease in magnetic flux density and an increase in magnetostriction. In materials development, it is important to understand the discrepancy between calculations and experiments and use it to move forward. I consider how the perspective of researchers with grit (the ability to see things through) is directly linked to maximizing technological value. Reference: Haruki Eguchi, Natsuki Yoneyama, Masakazu Hara, Shinnosuke Nakai, Hiroyuki Nose, Hiroki Yoshizawa, Evaluating magnetic degradation in FeCo-V alloys for high-output and compact electric motors: A multiscale-multiphysics approach, Materials Letters, 382 (2025) 137937, https://doi.org/10.1016/j.matlet.2024.137937
【Modeling & Simulation】「Advanced in Materials Modeling: Focus on Glasses」This presentation aims to explore the latest advancements in glass technology, emphasizing the development of antimicrobial glass and the enhancement of glass-polymer adhesion. By delving into these two key topics, we will highlight the role of materials modeling in driving these innovations and their potential applications. The research utilizes density functional theory and molecular dynamics techniques to simulate the properties and interactions of glass at the molecular level. In the realm of antimicrobial glass, structural analyses of various glass compositions are conducted to identify effect of glass former that effectively enhance chemical durability. The study of glass-polymer adhesion emphasizes interfacial chemistry and surface roughness, aiming to optimize bonding between these materials for improved durability and performance.
【Modeling & Simulation】"Application of quantum chemical calculations to automobile exhaust gas purification catalysts"I will introduce two research examples that utilize quantum chemical calculations targeting exhaust gas purification catalysts (three-way catalysts) for gasoline engine automobiles. The first introduces a technology for designing new three-way catalyst materials, using coupled analysis that combines quantum chemical calculations with chemical reaction kinetics simulations to predict purification rate curves. The second introduces a basic research example that provides a detailed examination of Temkin-type adsorption, the empirical rule that the adsorption energy of molecules on a material surface can be approximately expressed as a linear equation for the coverage rate.
【Laboratory & Data Management】"Initiatives to introduce and popularize electronic laboratory notebooks"At our Basic Technology Research Institute, we have been introducing electronic lab notebooks with the goal of "preserving as much information as possible." However, when we first introduced them, we experienced some setbacks, as they were not widely adopted due to issues with the introduction process and operation. We are currently rolling them out in stages, carefully listening to feedback from the field, and although we are still in the middle of this process, we are beginning to see signs that they are gradually taking root.In this presentation, I will talk about the trial and error involved in introducing and popularizing the system and the lessons learned from that process.
【Laboratory & Data Management】"BIOVIA Notebook Implementation: Achieving an Uptime Rate of Over 90%"The Research and Development Department of Lonseal Corporation introduced BIOVIA Notebook in 2024 as part of its digitalization and digital transformation efforts. The utilization rate of BIOVIA Notebook licenses has remained at a high level of over 90% since the introduction. In this presentation, I will introduce 1) the implementation process utilizing the "Innovator Theory" that achieved a high utilization rate of over 90% immediately after the introduction, and 2) efforts centered on system construction and tuning."Innovator theory" is a marketing theory that classifies and analyzes the process by which new products and services become popular in the market into five types based on the timing at which consumers accept new products and services.
【Data Science & Informatics】"Accumulating Experimental Data and Accelerating Materials Development Using Electronic Laboratory Notebooks"This presentation will introduce the construction and operation of a data infrastructure at Nitto Denko that is based on electronic experiment notebooks and Pipeline Pilot. Our company has implemented a system that structures experimental data in Excel format, preprocesses and automatically stores the data in Pipeline Pilot, and links it to an analysis platform.This is expected to significantly reduce the man-hours and errors involved in recording, searching, and processing, as well as to accelerate decision-making in materials development by utilizing accumulated data across multiple disciplines. In this presentation, we will share specific efforts and the results achieved.
In recent years, there has been a growing integration of physics-based models with machine learning approaches to enhance the speed and accuracy of existing computational methods. This presentation will explore the latest improvements in Materials Studio and Discovery, focusing on new methodologies and important updates to existing solvers. We will also discuss a collaborative effort involving quantum computing. As these solvers continue to advance, the way we interact with the tools also evolves. Last year, a key functionality called "Virtual Lab" within the 3DExperience platform was introduced, and this session will present the new enhancements to that system.
Reza has over 30 years of experience in executive management, with roles from R&D and portfolio management to driving mergers and acquisitions. As chief strategy officer, he is responsible for BIOVIA’s entire portfolio as well as BIOVIA’s contract research organization. After beginning his career in Defense, Reza moved on to an executive role at a Palo Alto startup and later with MSC Software. As chief Technology Officer at MSC Software, Reza was responsible for the global R&D and a multi-industry portfolio with teams covering Multi-scale Modeling & Simulation and Simulation Lifecycle Management. He holds a number of advisory board positions, including US National Labs. Reza lives in La Jolla Ca. He retains an adjunct status at UCSD and SDSU graduate schools of engineering.
Expertise: Pipeline Pilot, LLMs, Lab Workflows, Data Analytics, Automotive Battery Materials
Gregory is an Industry Process Scientist at BIOVIA, with a focus on cheminformatics and materials science. Greg is an experienced chemist with extensive knowledge in homogeneous and heterogeneous catalysis, commodity chemicals, and structure-property studies.
Gene Tetreault is providing the vision, strategy and management of the Laboratory Management product portfolio that includes the Electronic Laboratory Notebook, Laboratory Information Management System and the Laboratory Execution system. Gene has over 30 years of experience in the Life Science industry developing and delivering Laboratory informatics solutions for the research, development and quality control labs. Prior to joining BIOVIA, Gene led product development efforts for Zymark Corporation and REMP USA. Gene obtained is BS in Mechanical Engineering from the University of Massachusetts in 1991.
An effective leader with excellent communication skills, committed to delivering high-quality solutions and exceptional customer satisfaction. With over 15 years of experience, I bring deep expertise in strategic account development, project management, customer service, and operations management.
I have a broad understanding of the Innovation Lifecycle Management Process, enabling organizations to deliver better products, faster, and more cost-effectively. My technical background includes extensive software expertise in laboratory informatics, electronic lab notebooks, LIMS, LES, statistical data mining, bioinformatics, CADD, protein modeling, database mining, and materials research.
A data professional with 14 years of experience, Abha RAMCHANDANI has expertise in data engineering, analysis, and operations. At Gilead Sciences since 2017, she is a key member of the Discoverant team. She has developed varied solutions from process verification to automation, combining Discoverant and Pipeline Pilot (PLP) capabilities, to support key metrics, procedures, and stability trending.
I hold a BSc in Chemistry from the University of Kinshasa, DR Congo, and a PhD in Biomedical Sciences from the Icahn School of Medicine at Mount Sinai, majoring in molecular biophysics & biochemistry. After postdoctoral research in molecular dynamics at Wesleyan University, I moved to the biopharmaceutical industry, working in computational chemistry roles at BioNumerik, Targacept, Proteostasis Therapeutics, and RCH Solutions. Since 2020, I’ve been Principal Scientist II at Sanofi, specializing in AI/ML-driven drug design.
Sam Watson is a Sr. Manager of Data Engineering and Architecture at Thermo Fisher Scientific, with 20 years of experience in pharmaceutical data management and process optimization. With a background in Biochemistry and Microbial Biotechnology, Sam Watson has implemented advanced data integration and process analysis solutions to enhance operational efficiency and regulatory compliance in the pharmaceutical industry.
She is a Manager in FOODCHAIN ID, with a role for APAC. Proven international experiences and understanding to leverage cross border solutions. Proficient in all phases of organizing and coordinating multi-cultural projects. Profound experience in international / ASEAN business development. Capable leader and team-player.
Kaneka is accelerating digital transformation across the company, and has been gradually introducing BIOVIA Notebook in its research department since fiscal 2020. As the company has diverse business fields, including life sciences, polymers, and food, it is necessary to propose usage methods that are suited to each. Furthermore, when developing tools using Pipeline Pilot, the key is to incorporate generative AI and machine learning libraries in a way that can be commonly used by many departments.
Today, I will discuss the challenges of introducing a company-wide ELN, efforts to further utilize generative AI, and future prospects.