2026年ショートコース

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Monday, 16 November 2026 14:00 - 17:00

SC1: Reinventing Conjugate Therapeutics: Payload Revolution, Target Expansion and Clinical Translation

Antibody-drug conjugates have matured from a promising concept into a proven therapeutic modality - but the field is now undergoing a far deeper transformation than simple iteration. A new generation of conjugate therapeutics is challenging nearly every foundational assumption: payloads are expanding beyond cytotoxins into degraders, cytokines, and nucleic acids; targeting logic is growing more sophisticated with bispecific architectures and novel stromal and vascular antigens; and the disease scope is stretching well beyond oncology into autoimmune and inflammatory conditions. At the same time, the clinic is delivering hard-won lessons about what separates breakthrough molecules from costly failures. This short course charts that evolution - from the payload revolution redefining what a conjugate can carry, to the translational realities shaping what actually reaches patients.

The payload revolution: beyond MMAE and DXd - degraders, cytokines, and nucleic acids
AOCs and siRNA conjugates: silencing disease at the source
Bispecific and multispecific conjugates: engineering synergy into a single molecule
Escaping oncology: ADC strategies in autoimmune and inflammatory disease
Target expansion: CAFs, vasculature, immune checkpoints, and beyond
Lessons from the clinic: what next-gen conjugate failures and successes are teaching us

INSTRUCTOR BIOGRAPHY:

Lenka Sadilkova, PhD, Director, R&D Program, Eli Lilly ČR, s.r.o.

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.

SC2: 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.

Developability of Bispecific Antibodies

Nimish Gera, PhD, Founder and Principal Consultant, MABS R US Consulting

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 BIOGRAPHY:

Nimish Gera, PhD, Founder and Principal Consultant, MABS R US Consulting

Nimish Gera is an independent consultant and biotech executive with broad experience across antibody-based modalities including mono- and bispecific antibodies, protein fusions, and antibody-drug conjugates (ADCs) across several therapeutic areas such as oncology, immunology, autoimmune, and rare diseases. He has held scientific and/or leadership roles at companies ranging from early-stage startups like Mythic Therapeutics and Oncobiologics to large organizations such as Alexion Pharmaceuticals and Genentech. With more than fifteen years in drug development, Nimish has successfully advanced complex bispecific and ADC programs from concept through preclinical and early clinical stages. He serves as Associate Editor of the journal mAbs, hosts the Chain Protein Engineering podcast, and teaches the Developability of Bispecific Antibodies short course at the PEGS Boston and Europe conferences. Nimish has a proven track record of bringing multiple drug candidates to clinical trials, publishing peer-reviewed articles, building IP portfolios, and chairing national and international meetings on antibody therapeutics. He holds a PhD in Chemical and Biomolecular Engineering from North Carolina State University and a B.Tech in Chemical Engineering from the Indian Institute of Technology, Guwahati.

SC3: 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 specifically geared towards antibody design and developability predictions. There will be a live demo as well as a few ML tools.

Federico Devalle, PhD, Senior Data Scientist, AstraZeneca

Ben Williams, PhD, Research Software Engineer, Department of Statistics, University of Oxford

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:

Federico Devalle, PhD, Senior Data Scientist, AstraZeneca

Ben Williams, PhD, Research Software Engineer, Department of Statistics, University of Oxford

I joined the Oxford Protein Informatics Group (https://opig.stats.ox.ac.uk/) in January 2025 as a research software engineer, supporting the development and deployment of the group's tools, including SAbDab, the Structural Antibodies Database. You can use and learn about many of OPIG's freely available tools and resources here: https://opig.stats.ox.ac.uk/webapps I have a doctorate in condensed matter physics from the University of Oxford and spent several years developing software and methods for data analysis at Diamond Light Source, the UK's national synchrotron X-ray source and electron microscopy facility.

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