How in silico technologies could accelerate and amplify AI deployment for pharmaceutical applications?  
There is no doubt that AI will be an essential element of future healthcare to guess the likely evolution of a patient, a treatment, or a manufacturing process. But are the existing data sufficient and reliable enough?  
Computer mode lling and simulation, also known as in silico technology, uses extensively validated models that could predict patient and treatment outcomes, or model manufacturing processes, even in extreme cases.
Is in silico a necessary complement to fill in the AI gaps and provide a complete and reliable solution for the patients? 
Thierry Marchal- Ansys
As the Ansys Program Director for Healthcare Solutions and Chief Technologist Healthcare for EMEA, Thierry Marchal leads the medical devices, pharmaceutical and biotech activities of Ansys through the in silico and personalized medicine evolution. Thierry’s vision of Personal Digital Avatar -- driven by the potential of healthcare digitalization, including Medical Digital Twin and AI -- will be achieved by closely interacting with industrial innovators and SMEs, academic leaders and governmental and regulatory authorities (FDA, EMA, MHRA, etc.) Since January 2018, Thierry has been the Secretary General of the Avicenna Alliance, a global non for profit organization of leading medtech and pharma companies collaborating towards the large scale adoption of in silico medicine. Thierry is also a member of the EMA stakeholder group and the eHealth Stakeholder Group which provides advice and expertise to the European Commission. 
In his 30+ years of professional experience, Thierry has worked as the Global Materials Market Segment Manager with Fluent and Product Manager for Polyflow. Thierry is the author of more than 100 publications and communications; he holds a degree in Mechanical Engineering and a MBA both from Catholic University of Louvain, Belgium.

Pushpinder Singh- GSK

Pushpinder Singh is a Senior Scientist at GSK Technical R&D, where he leads a team of engineers and oversees a variety of modeling activities. His primary objective is to reduce experimental effort by incorporating advanced process engineering knowledge into development activities, thereby accelerating the time to market for new products. Singh's leadership plays a crucial role in streamlining research and development processes, ensuring efficiency and innovation.
Pushpinder, driven by a passion for Computational Fluid Dynamics (CFD) modeling, brings a natural curiosity and dedication to his work. His expertise lies in the field of vaccine development, where he leverages CFD to optimize processes and improve outcomes. Pushpinder commitment to this field reflects his broader interest in using cutting-edge technology to advance healthcare solutions.

Dmitrij Ivanov- Probaligence
I have studied Physical Engineering Science at the TU-Berlin (until 2010) and have since specialized in the application of Machine Learning (ML) to multi-disciplinary optimization problems at research institutions such as DLR (German Aerospace Agency) and Fraunhofer-Gesellschaft as well as in research collaborations between BTU-Cottbus and Rolls Royce Germany. In 2020, I successfully completed my PhD in the field of applying ML methods to engine component analysis. Since 2023, I am working as an ML Engineer at Pi Probaligence GmbH.
Dr. Sadegh Mohammadi- Bayer AG
Dr. Sadegh Mohammadi is the Head of Computer Vision and Sound Analysis at Bayer Pharmaceutical. His research focuses on Generative AI for medical imaging and sound data to address critical gaps in medical diagnostics and treatment. Dr. Mohammadi's group is pioneering synthetic medical image generation with state-of-the-art generative models to tackle medical imaging data scarcity and is the leading force behind bringing Generative AI to Bayer. Before joining Bayer, he earned a PhD in Computer Vision from the Istituto Italiano Di Tecnologia in 2017. Dr. Mohammadi is dedicated to advancing AI-driven medical research, aiming to improve diagnostics and patient outcomes through innovative solutions.
Naghmeh Ghazaleh - Roche
Dr. Naghmeh Ghazaleh works as an Innovation lead for neuroscience in pharma development at Roche Basel. Contributing to various roles in the pharma and diagnostics divisions, she has implemented AI and data-driven analysis for a better understanding of diseases and diagnoses and shaped the strategy for incorporating advanced analytics methods in various stages of drug discovery and developement. Laveraging her educational background in electrical engineering and Ph.D. in neuroscience, she has been awarded multiple innovation rewards as well as patents for innovative projects.

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