2025年的短期课程

Our short courses are designed to be instructional, interactive, and provide in-depth information on a specific topic. They allow for one-on-one interaction between the participants and instructors to facilitate the explanation of the more technical aspects that would otherwise not be covered during our main presentations.

Short Courses Will Be Offered In Person Only

Monday, 10 November 2025 14:00 - 17:00

SC1: Best Practices and Advanced Applications for Label-Free Interaction Analysis in Therapeutic Antibody Discovery

This short course will provide simple guidelines for best practices of interaction analysis using commonly-used commercial label-free biosensors in the characterisation of therapeutic antibodies. We will focus mainly on the use of surface plasmon resonance (SPR) and biolayer interferometry (BLI). First, we will address best practices for generating high-quality binding kinetic and affinity data. Then we will do a deep dive into epitope binning. A basic knowledge of interaction analysis is assumed, but "all-comers" should find this course helpful. We will review several case studies together to reinforce these concepts.

Topics covered will include:

BINDING KINETICS:

Optimising experimental setup including the influence of reagent quality, assay orientation, immobilisation method, and surface capacity
Corroborating surface-based measurements with solution ones

EPITOPE BINNING:

Assay formats
Bin definition
Throughput
Nuanced binning (antigen heterogeneity, asymmetry, and displacement)?

INSTRUCTOR BIOGRAPHIES:

Yasmina Abdiche, PhD, Senior Vice President, Exploratory Research, OmniAb Inc.

Yasmina is an internationally recognized and innovative scientific leader in the field of antibody discovery and biosensor technology with twenty years of experience in protein engineering and biopharma. She has authored over 50 peer-reviewed publications, had 25 patents granted in the therapeutic antibody space including a market-approved drug for migraine (Ajovy) and a Phase 3 investigational drug for bladder cancer (Sasanlimab), presented over 60 times as an invited speaker globally, and has been involved in numerous industry-wide collaborations and scientific advisory groups. After a twelve-year career at Pfizer where she held positions of increasing responsibility from Principal Scientist to Research Fellow, more recently, Yasmina has held senior management roles at biotechnology companies and contract research organizations including Carterra (CSO), ImmunoPrecise Antibodies (CSO), ALX Oncology (VP Protein Science), Revelar (CSO and Co-Founder), and FairJourney Biologics (CTO). During her time as CSO at Carterra, she co-founded its antibody screening biosensor platform (the LSA) which has helped transform label-free interaction analysis in early-stage drug discovery. Yasmina has a master's degree in chemistry and a PhD in biological chemistry from Oxford University and did post-doctoral studies in biophysical interaction analysis at the University of Utah.

SC2: Best Practices for Targeting GCPRs, Ion Channels, and Transporters with Monoclonal Antibodies

Complex membrane proteins are important therapeutic targets and together represent the majority of protein classes addressed by therapeutic drugs. Significant opportunities exist for targeting complex membrane proteins with antibodies, but it has been challenging to discover therapeutic antibodies against them. This course will examine emerging technologies and strategies for enabling the isolation of specific and functional antibodies against GPCRs, ion channels, and transporters, and highlight progress via case studies.

INSTRUCTOR BIOGRAPHIES:

Ross Chambers, PhD, Vice President, Antibody Discovery, Integral Molecular, Inc.

Ross Chambers is the Vice President of Antibody Discovery at Integral Molecular. He pioneered the use of DNA immunization for antibody production and developed Integral Molecular’s MPS system for isolating antibodies. Dr. Chambers earned his PhD from the University of Otago, New Zealand, and did post-doctoral studies at UC Davis and Berkeley. Before joining Integral Molecular, he was the Director of R&D at SDIX and directed the discovery of thousands of commercial antibodies.

SC3: Developability of Bispecific Antibodies

Bispecific antibodies are a rapidly growing and clinically validated class of antibodies with marketed drugs and multiple candidates in clinical trials. Targeting multiple antigens in a synergistic manner can confer enhanced therapeutic benefit and potentially uncover novel biological mechanisms. However, multiple formats and a tedious candidate selection process to select functional and developable bispecific antibodies makes such programs cumbersome. This short course highlights the rapid growth in the field, therapeutic applications, and focuses on challenges with discovery and development of bispecific antibodies. We will use an approved bispecific antibody as a case study to understand the varied aspects of discovery and development of bispecific antibody programs.

Topics to be covered:

Introduction to bispecifics and bispecific formats
Therapeutic applications of bispecific antibodies
Developability of bispecifics
Case study: discovery and development of an FDA-approved bispecific antibody

INSTRUCTOR BIOGRAPHIES:

Nimish Gera, PhD, Vice President, Biologics, Mythic Therapeutics

Nimish Gera is the Vice President of Biologics at Mythic Therapeutics leading multiple projects to engineer and develop novel antibody and antibody-based drugs in oncology and immuno-oncology. Prior to Mythic, Nimish has over fifteen years of experience in antibody and protein engineering with five years leading bispecific antibody programs in several disease areas such as rare diseases, oncology, and immunology at Alexion Pharmaceuticals and Oncobiologics. Nimish received his PhD degree in Chemical and Biomolecular Engineering from North Carolina State University and a B.Tech degree in Chemical Engineering from Indian Institute of Technology, Guwahati.

SC4: In silico and Machine Learning Tools for Antibody Design and Developability Predictions

Given the exciting pace in the evolution of machine learning tools towards antibody design and developability predictions, we plan to present an overview in this field specificity geared towards antibody design and developability predictions. There will be a live demo as well of few ML tools.

Topics to be covered include:

Overview of sequence, structure-guided, ML (machine learning) tools for developability and designs
Overview and demo of various ML tools from Oxford Protein Informatics Group (OPIG)
Antibody specific language models (Ablang - Olsen et al 2022, Ablang2 - Olsen et al 2024)
Antibody (and nanobody) structure prediction (ABodyBuilder2) Abanades et al 2023)
Therapeutic antibody profiling and developability evaluation (TAP - Raybould et al 2019, TAP2 - Raybould et al 2024)
Antibody sequence optimization with inverse folding (AntiFold - Hummer et al 2023)
In silico developability assessment - case studies

INSTRUCTOR BIOGRAPHIES:

Rahmad Akbar, PhD, Senior Data Scientist, Antibody Design, Novo Nordisk

At Novo Nordisk, Rahmad enables patients to realize their greatest potential by catalysing antibody design. He leverages experimental data, molecular simulation, and artificial intelligence to build computational oracles and to design antibody therapeutics faster, smarter, and cheaper.

Vinodh B. Kurella, PhD, Biotherapeutic Computational Modeler, Takeda Pharmaceuticals, Inc.

Vinodh Kurella is a Senior Scientist (Biologics computational modeler) in Biotherapeutic Engineering Group (BE) within Global Biologics at Takeda (Cambridge, USA). Experienced in structure-based antibody/protein design and optimization. Previously had range experiences at various biotech companies in different modalities such as gene therapy, biologics, and CAR T designs. Post-doctoral training at Harvard Medical School/Dana Farber in Dr. Wayne Marasco laboratory in antibody engineering and graduate training from Louisiana State University (LSU-HSC) in the field of protein X-ray crystallography in David Worthylake laboratory.

Odysseas Vavourakis, Generative Antibody Design, University of Oxford

I'm a DPhil (PhD) student in the Oxford Protein Informatics Group (OPIG) under the supervision of Prof Charlotte Deane and Dr Rebecca Croasdale-Wood (AstraZeneca). My research focusses on advancing de novo antibody design using generative models, and I am broadly interested in machine learning approaches to biomolecular structure and design. I hold a MSc in Computational Biology & Bioinformatics from ETH Zurich and a BSc in Biochemistry from Heidelberg University.

SC5: Novel Payloads and Conjugation Strategies - Building on Lessons Learned to Inform Next-Generation ADC Design

In this short course you will learn from real-life experience what are the main drivers of success or failures during the ADC development. How to improve your in vitro and in vivo screening strategies to avoid repeating the same mistakes made by others before you. And finally, what are the critical nonclinical datasets that you need to generate and how to interpret them to make your drug a success.

In this short course you will learn from real-life experience what are the main drivers of success or failures during the ADC development. How to improve your in vitro and in vivo screening strategies to avoid repeating the same mistakes made by others before you. And finally, what are the critical nonclinical datasets that you need to generate and how to interpret them to make your drug a success. We will cover all the areas of current interest in the field as listed below:

Lessons learnt and persisting liabilities of current generation of ADCs
In vitro and in vivo strategies to generate key data when evaluating improved or novel payloads, bispecific and dual payloads ADCs
What to focus on during the evaluation of previously clinically validated or novel ADC targets
Overview bioconjugate applications and challenges beyond oncology

INSTRUCTOR BIOGRAPHIES:

Lenka Sadilkova, PhD, Head, Preclinical R&D, Mablink

Dr. Lenka Kyrych Sadilkova has joined Mablink Bioscience in early 2022, as the Head of Preclinical Research and Development. Previously, since 2013, she worked at SOTIO Biotech as a scientist involved in several projects during the formation of the company development pipeline. Since 2016, she worked as a lead scientist and later as a director pharmacology responsible for non-clinical development of several antibody-drug conjugates, with the first one currently in Phase I. In the past, she held several positions in the field of Bioconjugation and Recombinant Proteins with academic institutions. She has worked for 6 years at Czech Academy of Sciences and for 4 years as a scientific lead in the Laboratory of Clinical Pharmacology in one of the Czech largest hospitals. Her work was focused on recombinant antibody engineering, animal vaccination strategies, and vaccine development as well as on research projects related to pharmacokinetic and pharmacodynamic modelling of selected standard of care regimens in geriatric patients with translational overlaps. She has received her PhD in biochemistry, molecular biology, and gerontology with several publications in peer-reviewed journals.

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