Two sessions of 2 workshops will be held during the afternoon of Tuesday, October 11. Please register during the online registration process. Each workshop is available at a fee of 85€.

Workshop 1 - Continuous Chromatography for Small Molecules : Principle, Process Development and Large Scale Manufacturing

Dr Olivier Dapremont (AMPAC Fine Chemicals)

Abstract

In this workshop, the students will learn the basic principles of continuous chromatography for the separation of small chiral molecules using the Simulated Moving Bed process.  The instructor  will introduce the mathematical modelling using the triangle theory to evaluate the performance of the separation and the influence of various parameters.  Once the basic concepts are in place, the instructor will discuss improvements to the technology and the extension of the process to more complex separations.  Finally, the student will learn how to develop an SMB separation from the initial screening to the implementation at commercial scale. 

Biography

Dr Dapremont received his Ph.D. degree in Chemical Engineering and Applied Chemistry in Simulated Moving Bed technology (SMB) and chiral applications in 1997 from the University of Pierre and Marie Curie in Paris France.

He started his career, in 1992, developing SMB technology for Prochrom R&D, France.  In 1997, He joined Chiral Technologies Europe, France, were he was in charge of the kilo lab for SMB chiral separations service.

He joined Aerojet Fine Chemicals, now AMPAC Fine Chemicals (AFC) in Rancho Cordova, CA, at the beginning of 2001.  At AFC, Dr Dapremont is in charge of the development of continuous processes for APIs and intermediates including chromatographic processes as well as implementing flow chemistry and related techniques at large scale.  To this day, he has developed and implemented over 50 chiral and non-chiral separations using SMB from kilogram to multi ton scale.

Dr Dapremont is author and co-author of several articles on preparative chromatography and SMB applications in various scientific journals and magazines.  He is co-inventor on multiple patents using SMB as a purification step for APIs and he is a recognized expert in the field for the past 25 years.

Dr Dapremont is also a member of the Organizing Committee of the Prep Symposium conference and a member of the Scientific Committee of the SPICA conference.

Workshop 2 - Introduction to Machine-Learning Methods for Process Development. From Multivariate Analysis to Hybrid Models

Dr Alessandro Butte (DataHow)

Abstract

In the last years, the use of machine learning (ML) algorithms has increase exponentially also in the context of process development and manufacturing. These tools, together with the progressive digitalization of all processes, procedures and data, the use of advanced sensors, and the possibility of putting different process units in direct communication with each other, is at the basis of what it has been called Industry 4.0.
This course is intended to introduce the participants to the main statistical and machine learning techniques that are typically used in the context of process development and manufacturing, with a particular view on the application to the so-called downstream processes and to chromatography in particular. The participants will be given an overview on all techniques, how and when to apply them, some theoretical background, and addition to relevant industrial application examples.

First, some basic statistical concepts (likelihood, p-values, etc.) will be given, together on a discussion on how to organize and prepare data. Then, an overview of the main multivariate data analysis (MVDA) methods will be given. This includes principle component analysis (PCA) and partial least square (PLS) regression. Then, an overview on the main ML methods for regression and classification will be given. This includes decision trees (DT) and random forests (RF), support vector machine (SVM), artificial neural networks (ANN), kernel ridge regression (KRR) and gaussian processes (GP). For all these techniques, focus will be put on the training and validation methods.

After introducing ML, the focus will move from purely data driven models to so-called hybrid models, where both mechanistic knowledge and data information are fused together to enhance data utilization and model robustness and predictability. Examples from chromatography will be given.
Finally, a brief overview will be given to experimental design and, in particular, on model based experimental design using the aforementioned methods.

Workshop 3 - Prep Chiral and Achiral SFC : Principles and Applications

Dr Eric Francotte (FrancotteConsulting GmbH, formerly, Executive Director at Novartis Pharma Research)
Dr Gerard Rosse (Vice President at PIC Solution, Inc - formerly, Associate Director at Dart NeuroScience)

Abstract

Packed column supercritical fluid chromatography (SFC) has been around for more than 40 years but the adoption of this technology as a general and routine method for chiral separations and achiral purifications is much more recent. SFC has known a spectacular development over the past decade and the revival of the technique has been mainly driven by its preparative usefulness. The green features, the speed, and the low running costs of SFC have greatly facilitated its adoption for preparative purposes, as these factors are essential at the preparative scale. With the introduction of more reliable instruments, the utilization of preparative SFC for chiral separations has rapidly expanded and it is now the method of choice for this application.

Preparative packed column SFC has been embraced by many research laboratories for preparative separations/purifications, in particular in the drug discovery environment and other life science sectors. Indeed, at this stage of drug development, it perfectly fits the requirements, that is, rapid processing of many samples in relatively small amounts. The recent introduction of preparative SFC instruments possessing mass-triggered fractionation capabilities has markedly contributed to the extraordinary acceleration of the expansion of the technique for achiral purifications in particular. The numerous advantages of packed SFC such as high diffusivity, low pressure drop, short equilibration times, reduced solvent consumption and costs, less safety concerns with respect to flammability and toxicity, fast solvent removal, and reduced impact on the environment have certainly also been decisive for this major conversion from HPLC to SFC in the field of preparative purifications. SFC has now become the first approach in drug discovery for the fast purification of thousands of samples produced by high- and medium-throughput synthesis.

The course intends to show the current status of preparative packed column SFC. It is divided in two sections, chiral and achiral as both applications require different setup and apply different types of stationary phases and screening approaches for method development. The course will cover the applications of SFC for small samples as well as for kg scale. It will also discuss the different modes (low to high-throughput) and it will review the currently available instrumentation. 

Biographies

Eric Francotte received his PhD in organic chemistry at the University of Louvain in Belgium and spent two years as a postdoctoral fellow at the University of Geneva. During 10 years in the Central Research Laboratories of Ciba (Basel, Switzerland), he focused his research interest on the development of new chiral stationary phases for enantioselective separations of chiral compound.

In 2005 he was appointed as an executive director in the pharmaceutical Research of Novartis. He is now independent scientific advisor in the field of Separation Sciences. During his industrial research career he developed and applied innovative chiral materials for the separation of enantiomers of numerous biologically active substances on an analytical and preparative scale. The invention has been commercially exploited through a collaboration with Daicel and the resulting materials have become the new gold standard in the field of chromatographic separation of stereoisomers in all laboratories dealing with chiral separations in the industry and academia. He was a pioneer in applying the chiral chromatography technology in life sciences and for the implementation of new preparative chromatographic technologies such as simulated-moving-bed and supercritical fluid chromatography in the pharmaceutical industry. He was also the chairman of a number of International Symposia in the field of Preparative Chromatography, Pharmaceutical Analysis, Chirality (ISCD), and Supercritical Fluid chromatography. He received several awards for his contribution in the field of enantioselective chromatography, notably the Ciba Fellow Award, the Jaubert Prize of the Geneva University, the Senior Industrial Investigator Award from the Swiss Chemical Society and the highest Novartis scientific recognition ‘The Novartis Distinguished Scientist award. He holds 125 publications and patents, and he published or contributed several books.

Gerard Rosse is Vice President at PIC Solution, Inc. and also serves as President at Arrival Discovery LLC. He is a distinguished consultant in medicinal chemistry, laboratory automation and computational sciences for the Pharma industry. Prior, he functioned in scientific and management positions in medicinal chemistry with Dart NeuroScience, Cephalon, Sanofi and Hoffman-La Roche. During his >20 years industrial tenure, he led multidisciplinary teams and invented pre-clinical candidates for CNS, Inflammation, Metabolism, Oncology and Antibacterial Agents indications. Dr. Rosse’s career is also characterized by the implementation of intelligent laboratory automation platforms using Supercritical Fluid Chromatography (SFC) for the manufacturing of small molecules. His current focus is on the development of novel instrumentation and methodologies for using CO₂ in extraction and purification at research, pilot and industrial scale. He recently edited a 2-volume book on the applications of SFC in life sciences. Dr. Rosse received the Ph.D. degree in chemistry from the University of Basel in Switzerland and postdoctoral training at Stanford University.

Workshop 4 - Application of Machine-Learning Methods to the Production of Therapeutic Proteins

Prof. Massimo Morbidelli (Politecnico Milano)

Abstract

In the last years, there has been an increased interest in continuous and integrated manufacturing of biopharmaceuticals, due to increasing cost and time pressure in industry, as well as new drug formats asking for more flexible production concepts. The next step towards intensification and modernization of current manufacturing technologies will be based on the use of online process control and optimization techniques. This requires the appropriate use of statistical approaches and machine learning techniques - not only in a continuous manufacturing scenario, but also within the more traditional batch integrated processes.

In this workshop, we discuss results obtained through hybrid approaches, where such machine learning techniques are used online in combination with traditional mechanistic models. Applications include : development of soft sensors for up and down stream monitoring (Raman based), online maintenance (prediction of protein A substitution in a monoclonal antibody capture process), hierarchical online process control and optimization of a chiral SMB process and a capture twin column unit.

The illustrated results mainly, but not only, refer to a end-to-end integrated continuos unit for the production of an industrial monovalent antibody of industrial relevance. They provide a very important basis to intensify the main advantages of continuous integrated manufacturing in agreement with the trends of industry 4.0.

Biography

Massimo Morbidelli received his Laurea in Chemical Engineering at the Politecnico di Milano and PhD at the University of Notre Dame. He is currently Professor at the Politecnico di Milano (Italy) and Professor Emeritus at the ETH Zurich (Switzerland).

His main research interest is in the area of biopharmaceutics and specifically on the integrated continuous manufacturing of therapeutic proteins, and its automation and digitalization.

Massimo Morbidelli is co-author of more than 750 papers, 23 international patents and six books, including the very recent ones on Continuous Biopharmaceutical Processes (2018), Cambridge University Press, coauthored with D Pfister and L Nicoud and Perfusion Cell Culture Processes for Biopharmaceuticals (2020), Cambridge University Press, coauthored with M Wolf and J-M Bielser. He is the first chemical engineer elected to the Italian Academy of Science (Accademia dei Lincei), serves as the Executive Editor of the ACS journal of Industrial & Engineering Chemistry Research, and is the recipient of:

• R.H. Wilhelm Award in Chemical Reaction Engineering by the American Institute of Chemical Engineers, 2005
• Gerhard Damköhler-Medaille of DECHEMA.and VDI-GVC, 2014
• Excellence in Process Development Research Award by the American Institute of Chemical Engineers, 2017
• Separations Science and Technology Award by the American Chemical Society, 2018
• ICB Award, Contributions to Integrated Continuous Biomanufacturing, 2019 
• Laurea Honoris Causa, Slovak University of Technology, Bratislava, 2019 

In his career he advised more than 100 PhD students. He is a cofounder of ChromaCon Ltd., a spin-off company from his research group, which brings new chromatographic processes (MCSGP-technology) for the purification of proteins and peptides to the market (now acquired by YMC, Japan) and of DataHow Ltd. for the application of data science and machine learning in Biotechnology and specifically in the Biopharma Industry.