Registrations are open !

Format: Hybrid (BioPark – Online) – 6 modules of 4 hours 

Dates: June 17th, June 20th and June 24th

Registration Fee : 2.400€

EU Biotech Campus is thrilled to introduce our latest training program focusing on AI in bioproduction, in collaboration with DNAlytics, Rombio (Genko) and UCLouvain. This unique opportunity will equip you with the tools to leverage AI technologies, enhancing bioproduction processes from upstream development to downstream processing for efficiency and scalability.

Why AI Integration in Biopharma Matters ?
The biopharma industry is rapidly evolving globally, driven by AI integration. Staying ahead of this curve is crucial to avoid obsolescence and foster innovation.

Tackling Operational Challenges :
Our comprehensive training program addresses bottleneck processes prevalent in biopharma operations. Participants will explore how AI streamlines operations, optimizes processes, and effectively mitigates challenges.

Harnessing Machine Learning  and Combinatorial Optimization:
With a focus on machine learning and combinatorial optimization, our program delves into the intricacies of AI-driven bioproduction. Gain insights into schedule optimization, operations management, predictive maintenance, and data-driven decision-making to revolutionize your operations. The program will also strongly relate to very practical business concerns, such as the need for relevant data models for manufacturing activities or contextualization of the data allowing for regulatory compliance (GMP, GMLP,…).

Join the Innovation Wave :
Seize the opportunity to harness AI’s power in bioproduction. Our hybrid training offers flexibility, blending onsite sessions at BioPark with online modules. Equip yourself with the knowledge and skills to thrive in the evolving biopharma landscape.

Key Benefits :

  • Gain insights into AI applications, combinatorial optimization and machine learning in bioproduction.
  • Learn effective strategies and methods to overcome operational challenges.
  • Network with industry professionals and experts.
  • Receive hands-on training from experienced instructors.
  • Access resources and case studies for practical learning.

You Get the best trainers  

  •  Michael Saint-Guillain 

Michael is an entrepreneur and researcher specializing in computer science applied to biotechnology and healthcare. As the founder and CEO of GENKO, he commercializes the Rombio software, assisting biotech and pharma companies in managing and optimizing their bio-manufacturing operations. He also has extensive experience as a university lecturer and research assistant at Université Catholique de Louvain, where he earned a PhD in Engineering Sciences and another in Computer Science. His research focuses on artificial intelligence applied to bio-manufacturing, space exploration, and treatment process optimization. Michael also possesses skills in management, communication, and leadership, demonstrated through his management of research projects and leadership of a university team.

  • Thibault Helleputte  

Thibault is an expert in data science and artificial intelligence, specialising in healthcare and biotechnology. As CEO and co-founder of DNAlytics, he brings extensive data science expertise to the healthcare and biotechnology sector. He has also held a number of academic and advisory positions, as well as jury roles in health research funding initiatives. His research and publications focus on genomic data analysis, computational biology and the use of artificial intelligence to improve healthcare. He holds a PhD in engineering sciences, with expertise in feature selection and machine learning in complex statistical contexts.

  • Yves Deville 

Yves Deville is a professor at the Université Catholique de Louvain, specializing in artificial intelligence, constraint programming, and optimization. He plays a key role in the university’s digital transformation efforts, particularly in advancing open education and open science initiatives. Deville emphasizes the importance of sharing educational resources and developing online courses accessible to everyone. Additionally, he promotes open publication practices and advocates for the use of open-source software within the academic community.

 Registration

Please complete the form below if you would like to take part in the programme.

You will receive confirmation with full details and payment information.

Please note that places are limited.

See full program below. 

                                                          Full Program 


Module 1: Introduction to Data Sciences in the biopharma industry.

Module 1a : Introduction to data sciences and AI and their impact over the biopharma product lifecycle.

  • Date : 17/06 AM
  • Duration: 4h (Presential)
  • Key elements: Brief historical perspective of AI, high-level big “families” of AI approaches (adversarial theory, supervized and non-supervized Machine Learning, Deep Learning, Generative AI). Biopharma lifecycle and AI (based on European Medicine Agency perspective). Regulation (Good Machine Learning Practice, based on FDA perspective).

Module 1b : Introduction to AI in operations management

  • Date :  17/06 PM
  • Duration: 4h (Presential)
  • Key elements: The curse of dimensionality and the need for AI in operations management, model-driven AI versus data-driven AI, applications in suppply chain, S&OP, and at the shop floor. Introduction to optimization.
 

Module 2 : AI in biomanufacturing.

Module 2a : Data-Driven Biomanufacturing

  • Date : 20/06 AM
  • Duration: 4h (presential – online possible)
  • Key elements: Data types and data sources,  IT versus manufacturing standpoint regarding manufacturing data, data and metadata, overview of applications of data sciences in biomanufacturing such as continuous process verification, process improvement, process development. 

Module 2b : Variations on the theme of modeling of cell culture.

  • Date : 20/06 PM
  • Duration: 4h (Presential – online possible)
  • Key elements: three complementary approaches of cell culture modeling (i) pure data-driven / ML approach; (ii) hybrid data+mechanistic approach; (iii) spectrometry-based approach. Illustration of GMP-compliant model building, validation and deployment.
 

Module 3: AI in operations management

Module 3a : Theory of scheduling by Yves Deville (UCLouvain)

  • Date : 24/06 AM 
  • Duration: 4h
  • Key elements: Temporal networks, Complexity: equivalence classes, P≠NP, uncertainty, Solution methods: approximate versus exact methods, Mathematical modeling: a simple job shop scheduling problem
 

Module 3b : Applied project in operations management.

  • Date : 24/06 AM 
  • Duration: 4h 
  • Key elements: demonstration and application of real case studies. Short term (operational), middle term (tactical, e.g. Supply Chain) and long term (strategic, e.g. business plan, S&OP) planning and scheduling: optimization, simulations, bottleneck, communication, execution tracking. Multi-level (inter-department) planning and decision making.
 

Optional Module 4: Practical case – digitalization of a biomanufacturing process.

  • Duration: 8 hours.
  • Key elements: In this session, participants receive material describing a concrete biomanufacturing process, such as (simplified) SOPs, record forms for different manufacturing steps, specifications of IT systems, etc. as well as a training regarding a practical methodology for describing a given biomanufacturing process. Their goal is to work in groups and provide a reworked version of the process description, ready for full digitalization, and data exploitation. The resulting process representation will be imported in the Hercule software for data-driven biomanufacturing excellence, which would allow for participant to actually “play” with their newly digitalized process. First 2 hours are for project introduction, 4 next hours are for group work, last 2 hours are for results presentation and sharing.
 

Optional Module 5 : Practical case – Operational process modeling.

  • Duration: 8 hours 
  • Key elements: Participants will model an operational process within their company, based on their own experience.
 

                                                                                                                        Training illustrations