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Artificial intelligence has been used in the financial and computational fields for many years with great success. The use of such technology in the personal care industry is starting to make its impression. Areas like molecular design, formulations, scale-up and manufacturing are some of the fields impacted by the technology. At this stage we are just scratching the surface as the growth of this field will have greater implications on our industry.
In this seminar, two renowned scientists will introduce us to the world of AI and its applications in the world of cosmetics. They will share with us some great examples of how AI is applied in personal care. They will also highlight the benefits of such technology in speeding up the research and development process for launching new molecules and new products.
Welcome and Registration: 5:00 – 5:15pm
First Speaker: 5:15 – 6:00pm
Cocktail Hour: 6:00 – 6:45pm
Dinner and Keynote Speaker: 6:45 – 8:30pm
Artificial Intelligence and its application in the development of new molecules for the Cosmetic Industry
There has been explosive growth in the use of artificial intelligence (AI) and digital technology for innovation and product development. As an early adopter of machine learning and molecular simulation, We have encouraged the use of digital technology to accelerate innovation. New ideas, methods and best practices that takes advantage of these new tools and enhance innovation have been implemented. Molecular simulation, AI/machine learning, and predictive modeling are used to commercialize new products with superior properties. Physical chemical based molecular models are used to simulate molecular structure, dynamics, and interactions giving us insight into the chemical behavior that drives critical-to-function properties. Statistical models based on AI uncover hidden structure-property relationships and optimize chemical processes and properties enabling informed decision making and product innovation. Development of new antimicrobial ingredients, and new hair fixatives using an AI-based rational design approach will be presented.
Dr. Solomon Jacobson is a subject matter expert for computational chemistry, machine learning, polymer chemistry and materials science, with more than 20 years of experience solving challenging technical problems related to personal care and cosmetics businesses. With extensive experience in molecular simulation, AI/machine learning, and predictive modeling, Dr. Jacobson elucidates physical-chemical mechanisms and uncovers hidden structure property relationships that facilitate informed decision making and significantly shortens the product development cycles. Since joining Ashland in 2016, he has been responsible for implementation, development, and utilization of computational chemistry and AI/machine learning methods. These include high quality quantum mechanics (QM), molecular dynamics (MD), soft matter simulation, polymer models, quantitative structure activity relationships (QSAR), and visualization, AI and data analytics techniques that are becoming increasing more important to optimize product manufacturing process and speedup the innovation pipeline.
The applications of data science in the industrial world are almost endless, and this is no exception in the chemical industry. In this talk, I will provide an overview of how digitalization, and in particular data science, is contributing to materials development. Specifically, I will focus on the challenges of data science in the industry and discuss state-of-the-art tools which are being used to overcome these challenges. We will discuss some success stories in the areas of machine learning and experimental design at the industrial level, particularly in the areas of formulation modeling and reverse engineering formulations. I will conclude with a long-term goal of data science: systems integration and Artificial Intelligence Systems.
Keith Task is a senior digitalization research scientist at BASF Corporation, and is based in Beachwood, OH. Keith obtained his B.S. and Ph.D. in Chemical Engineering from the University of Pittsburgh. Keith has been at BASF since 2015 and supports business and research units across the company through statistics and mathematical modeling. Keith’s primary interests include machine learning, experimental design, and linking data driven and mechanistic modeling.
(Thursday) 5:00 PM - 8:30 PM