Training Seminars - 2026 Archive

2026 ARCHIVES

Cambridge Healthtech Institute Training Seminars offer real-life case studies, problems encountered and solutions applied, along with extensive coverage of the academic theory and background. Each Training Seminar offers a mix of formal lecture and interactive discussions and activities to maximize the learning experience. These Training Seminars are led by experienced instructors who will focus on content applicable to your current research and provide important guidance for those new to their fields.

Training Seminars Will Be Offered In Person Only
To ensure a cohesive and focused learning environment, moving
between conference sessions and the training seminars is not allowed.

Monday, May 11, 2026 8:30 am - 6:00 pm | Tuesday, May 12, 2026 8:30 am - 12:45 pm

TS3A: Introduction to Multispecific Antibodies: History, Engineering, and Applications

Detailed Agenda

Introduction to Multispecific Antibodies is an informative and practical guide to getting up to speed on critical aspects of multispecific antibody therapeutics. Topics will include historical successes, failures, and lessons learned. Specific practical instruction will span mechanisms of action, engineering, developability, regulatory considerations, and translational guidelines. Perspectives on ideal implementation of multispecifics as targeted and immunomodulatory approaches will be discussed.

G. Jonah Rainey, PhD, Associate Vice President, Eli Lilly and Company

Topics to be covered:

A brief history of bispecific antibodies: 60 years of progress with critical advances and key pioneers
Bispecific applications and powerful mechanisms-of-action
Engineering bispecific antibodies:100 formats and counting
Bispecific-specific considerations in preclinical development and regulatory landscape
Developability, manufacturing, and analytical considerations
Clinical experience, translation, and regulatory approval
Current trends and future opportunities in regulating immune checkpoints, cell-based therapies, and personalized approaches

INSTRUCTOR BIOGRAPHY:

G. Jonah Rainey, PhD, Associate Vice President, Eli Lilly and Company

Jonah Rainey holds a PhD in Biochemistry from Tufts University and completed postdoctoral training at the University of Wisconsin and the Salk Institute. He has engaged in discovery, research, and development of bispecific antibodies for more than 15 years. He is an inventor on several patents describing novel bispecific platforms and current clinical candidates that exploit these platforms as well as an author on almost 30 publications. Jonah contributed to research and early development leading to multiple clinical candidates from Phase I and through approved products and led many advanced preclinical programs in oncology, infectious disease, autoimmunity, and other therapeutic areas. Previous industry experience includes MacroGenics, MedImmune/AZ, Oriole Biotech, Gritstone Oncology, and Alivamab Discovery Services. Currently, Jonah is a Senior Director in Protein Science at Eli Lilly & Co.

TS7A: Introduction to Immunogenicity

Detailed Agenda

This 1.5-day training seminar provides a practical, comprehensive overview of immunogenicity—the causes, how to assess, predict, and prevent, and what to do if you observe immunogenicity during preclinical, clinical, and post-market approval. The seminar begins by detailing the science behind immunogenicity, the latest international guidance, followed by assay and bioanalytical assessment strategies for traditional and emerging biologics. Other topics include predictive models, the role of AI/ML, and reporting immunogenicity.

Chloé Ackaert, PhD, Senior Scientist, Immunogenicity, IQVIA Laboratories

Timothy Hickling, PhD, Consultant, Quasor Ltd.

Sofie Pattyn, Founder & CTO, IQVIA Laboratories

TOPICS TO BE COVERED INCLUDE:

Part 1: Introduction to Immunology and Immunogenicity

What is immunogenicity?
Immunology and major mechanisms affecting immunogenicity
Consequences of immunogenicity
Risk-based approach

Part 2: Non-clinical Immunogenicity Potential assessment

Part 3: Clinical Considerations of Immunogenicity and Regulatory Expectations

Part 4: Assay Methodology and Approaches for Describing Immunogenicity in the Clinic

Assay methodologies
Comparison of different methods Screening, confirmation
Characterization of anti-drug-antibodies
Cut-points Immunogenicity of complex biologics (e.g. multi-domain, biosimilars)
PK/PD and safety and efficacy-- as a measure
Immunogenicity in the clinic – how to report?

INSTRUCTOR BIOGRAPHIES:

Chloé Ackaert, PhD, Senior Scientist, Immunogenicity, IQVIA Laboratories

Chloé Ackaert is a pharmacist by training (Catholic University of Leuven 2009) and obtained her PhD at the University of Salzburg (Austria) for the research on the impact of nitration on the immunogenicity of birch pollen allergens in 2013. She first joined ImmunXperts in the start-up phase and continued academic research at the Free University of Brussels (2015-2018) working on the immunogenicity of Nanobodies. Afterwards, she joined ImmunXperts again where she is a senior scientist in the immunogenicity team, collaborating both on the client-based projects as well as on the continuous basic research projects to elucidate immunogenicity-related questions.

Timothy Hickling, PhD, Consultant, Quasor Ltd.

Tim has 15 years’ experience contributing to immunogenicity risk and mitigation strategies for large molecules and advanced therapies at Roche and Pfizer, from early discovery projects to those in clinical development and post-marketing. During the last ten years he has contributed immunology expertise to the development of an in silico immunogenicity model, with the purpose of improving predictions of clinical immunogenicity for drug candidates. Tim previously worked on vaccine development and holds a PhD in Immunology from the University of Oxford.

Sofie Pattyn, Founder & CTO, IQVIA Laboratories

Sofie Pattyn, CTO and founder of Iqvia Laboratories In Vitro Immunology (Formerly known as ImmunXperts), has over 25 years of experience in the field of immunogenicity assessment (vaccines and biotherapeutics) and in vitro assay development with a focus on functional assays for immunogenicity, immune oncology, and cell and gene therapy products. She has extensive hands-on lab experience and has managed and coached several in vitro teams over the last decade. From 2008 until 2013, she was Head of the in vitro Immunogenicity group at AlgoNomics (Ghent, Belgium) and Lonza Applied Protein Services (Cambridge, UK). Prior to that, she worked at Innogenetics in Belgium for over 15 years.

TS9A: Introduction to Machine Learning for Biologics Design

Detailed Agenda

This course offers an introduction to concepts, strategies, and machine learning methods used for biologics design. It includes presentations and demonstrations of the methods used in the field, covering techniques such as triaging sequences, modulating affinity, and designing antibody libraries, along with increasing manufacturability. The course is directed at scientists new to the field and protein engineers wanting an introduction to how machine learning can aid in guiding biologics design.

Francis Gaudreault, PhD, Associate Research Officer, Human Health Therapeutics, National Research Council Canada

Wanlei Wei, PhD, Research Officer, Computer-Aided Drug Discovery, National Research Council Canada

Topics to be Covered:

Basics of machine learning and where it fits into drug discovery
Modern homology modeling and structure prediction
Predicting antibody affinity and specificity modulation
Generative design in biologics: library design and language models
Machine learning applications of T cell and B cell immunogenicity
Methods and application of ML for chemical, folding, solution stabilities

INSTRUCTOR BIOGRAPHIES:

Francis Gaudreault, PhD, Associate Research Officer, Human Health Therapeutics, National Research Council Canada

Francis obtained his PhD in Biochemistry from University of Sherbrooke in 2015, during which he developed a molecular docking program for docking small molecules to flexible protein or RNA targets. While doing his PhD studies, Francis co-founded a successful IT company for automating the management of scientific conferences. Francis joined the National Research Council (NRC) of Canada in 2016, where he has taken part in and led various efforts in the discovery and engineering of antibodies or other biologics. In such efforts are included the structure prediction of antibodies alone or in complex, the affinity assessment of antibody-antigen complexes, and the detection of antibody developability issues. Francis is leading the technical efforts in using artificial intelligence for antibody discovery.

Wanlei Wei, PhD, Research Officer, Computer-Aided Drug Discovery, National Research Council Canada

Wanlei is currently a postdoctoral research fellow at the Human Health Therapeutics Research Center at the National Research Council Canada, located in Montreal, Canada. In this role, he develops and employs computational tools for antibody engineering. Before working in the antibody space, he worked on computer-aided drug design of small molecule inhibitors against RNA, force field development, and computational enzymology. To date, he has published more than a dozen papers in computational chemistry.

TS10A: Introduction to Protein Engineering

Detailed Agenda

This course presents a comprehensive tutorial in the concepts, strategies, and latest tools of protein engineering applied to biotherapeutic research and development, particularly antibody-related products. The class is for scientists new to industry or working in support roles, academics, and protein scientists wanting a detailed update on the current state of the field.

David Bramhill, PhD, Founder, Bramhill Biological Consulting LLC

Topics to be Covered:

What is protein engineering?
Tools and techniques
Engineering-by-design
Designed libraries, display technologies
Production and manufacturing
Improving manufacturing by protein engineering methods
Other protein modifications
Expression of antibodies and fragments for discovery and testing
Emerging molecule and product formats
Antibody-drug conjugates (ADCs)
ML/AI applications and limitations
Other emerging approaches

INSTRUCTOR BIOGRAPHY:

David Bramhill, PhD, Founder, Bramhill Biological Consulting LLC

Dr. Bramhill has over 20 years’ experience in biologics, both in large biopharma and startup biotech companies, and currently consults as a scientific-technical expert. He has expertise in isolating and improving antibodies using phage display and other display systems and is an inventor on library design for small scaffolds and bi-specific formats. He also has experience in diverse expression systems for producing antibodies, antibody fragments and scaffolds. Additionally, Dr. Bramhill has extensive experience in ADC development including diverse chemical and biochemical conjugation methods. He has taught numerous technical courses for over 20 years at international conferences and served as a Key Opinion Leader for major BioPharma companies.

TS11A: Antibody Drug Discovery: From Target to Lead

Detailed Agenda

Over 200 antibody-based therapies have been approved for treating almost all major human diseases. Drug modalities include, but are not limited to, mAbs, bispecifics, ADCs, CAR-Ts, antibody-protein fusions, and fragments. Half of the top 20 bestselling prescription medicines in 2024 are antibodies. More than 50% of the new drugs in clinical development are antibody-based. This course will comprehensively review state-of-the-art concepts, methodologies, and trends in therapeutic antibody discovery and development.

Zhiqiang An, PhD, Professor, Robert A. Welch Distinguished University Chair in Chemistry; Director, Texas Therapeutics Institute; Director, CPRIT Core for Antibody Drug Discovery; Vice President, Drug Discovery, University of Texas Health Science Center at Houston

Topics to be covered include:

1. Different sources of antibodies: animals—mice, rat, rabbit, chicken, llamas, etc; libraries—immune, synthetic, native, fully human, etc.; B-cells—memory B-cells, plasma B-cells of humans and animals; de novo designed antibodies by AI (artificial intelligence)

2. Various antibody-based drug modalities: IgGs, IgA, IgM, bites, nanobody, antibody fragments, etc.; naked antibody; ADC; bispecific/multispecific; CAR-T; antibody-based protein degraders

3. Antibody engineering: affinity maturation; humanization; Fc-engineering: half-life, immune effector function, etc.

4. Target selection and validation

5. Antibodies targeting complex membrane proteins: GPCRs, ion channels; transporters, and membrane-bound enzymes

6. Delivery of antibodies crossing the blood-brain barrier (BBB)

7. AI in antibody engineering

8. Case studies

INSTRUCTOR BIOGRAPHY:

Dr. Zhiqiang An is Professor of Molecular Medicine, the Robert A. Welch Distinguished University Chair in Chemistry, Director of the Texas Therapeutics Institute, and Vice President of Drug Discovery at the University of Texas Health Science Center at Houston. His laboratory focuses on antibody drug resistance mechanisms, biomarkers for therapeutic antibodies, and antibody drug discovery targeting human diseases. During the last five years, more than 12 novel antibody drug leads discovered in his laboratory were licensed to eight biotechnology companies, and six (6) have advanced to clinical trials for diseases ranging from acute myeloid leukemia (IO-202), breast cancer bone metastasis (ALMB-0168), solid tumor (IO-108), spinal cord injury (ALMB-0166), COVID-19 (IGM6268), and solid tumor (PRTH-101). Previously, he served as Chief Scientific Officer at Epitomics, Inc. and was Director of Biologics Research at Merck Research Laboratories. He has authored over 200 journal articles including more than 30 papers in Nature, Science, and Cell journal series; and two books including the award-winning “Therapeutic Monoclonal Antibodies: from Bench to Clinic.” He is an elected fellow of Society for Industrial Microbiology and Biotechnology (SIMB), the American Academy of Microbiology (ASM), American Association for the Advancement of Science (AAAS), and the National Academy of Inventors (NAI). Dr. An received his PhD from the University of Kentucky and his postdoctoral training at the University of Wisconsin-Madison.

Tuesday, May 12, 2026 2:20 - 6:10 pm | Wednesday, May 13, 2026 10:00 am - 6:20 pm

TS9B: AI-Driven Design of Biologics: A Hands-On Guide to Using State-of-the-Art ML Protein Models

Detailed Agenda

Since 2021, artificial intelligence models have revolutionized AI-driven biologics development, enabling breakthroughs in structure prediction, sequence design, and protein engineering. This course equips researchers and professionals with the expertise to leverage cutting-edge tools for structure prediction (AlphaFold, ImmuneBuilder), protein engineering with protein language models (ESM, AntiBERTy) and structure-based design (ProteinMPNN and RFDiffusion). Through a blend of lectures and hands-on exercises, participants will learn best practices for tool selection, method optimization, and design selection. By exploring real-world applications and emerging techniques, such as BindCraft and RFAntibody, attendees will gain a practical understanding of performance capabilities, limitations, and effective workflows.

Bharat Adkar, PhD, Protein Engineer, GRO Biosciences

David P. Nannemann, PhD, Vice President, Rosetta Commons Foundation

Participants are expected to have some prior exposure to computational modeling tools (e.g. Python, R, COOT, Rosetta, AutoDock Vina, etc.) but limited experience applying them to their projects. They should be comfortable using Jupyter notebooks and prepared to explore topics such as evaluating metrics, determining appropriate sampling sizes, and selecting key adjustable parameters. While this seminar does not cover ligand docking or protein-protein docking, it is well-suited for those interested in antibody modeling and, potentially, enzyme design language models.

Hands-on instructional content will be presented as Google Colab notebooks written in python. A basic understanding of general coding principles, such as typing, loops, functions, and classes, will be sufficient. It will not be required to write your own code from scratch, but a sufficient familiarity with python to understand and edit the provided notebooks will be essential to a meaningful experience.

Topics to be covered:

Building practical experience with AI-based modelling of proteins
A breakdown of input formats, command lines, and analysis of output
Hands-on exercises using real-world scenarios in antibody structure prediction, developability pre-screening, immunogen solubilization, and de novo binder design
Discussion of, and guidance on, questions like: how many models, in silico selection metrics and ranking, and how many to test in the lab
Pipelining of protein design software and the critical use of an “oracle”

INSTRUCTOR BIOGRAPHIES:

Bharat Adkar, PhD, Protein Engineer, GRO Biosciences

Bharat Adkar is a protein engineer with over a decade of experience bridging computational design and experimental validation of protein molecules. As an independent consultant and previously at GRO Biosciences, he developed AI-driven design workflows using RFdiffusion, ProteinMPNN, and AlphaFold to engineer therapeutic proteins. His background is unusual in spanning the full design-build-test cycle, from in silico modeling through wet-lab execution and biophysical characterization. Before industry, Bharat was a Postdoctoral Fellow at Harvard University where he demonstrated biophysical basis for bacterial fitness. He earned his PhD from the Indian Institute of Science, Bangalore, where his work was among the earliest to use deep sequencing of saturation mutagenesis libraries for protein structure modeling.

David P. Nannemann, PhD, Vice President, Rosetta Commons Foundation

David is an expert in protein engineering and computational design, with extensive experience applying AI-driven modeling tools in an industry setting. He serves as Vice President of the Rosetta Commons Foundation and Industry Chair on the Rosetta Commons board, helping bridge academic advancements with industry applications. As Managing Member of Rosetta Design Group, he collaborates with companies of all sizes to tackle complex challenges in biologics design. David's deep expertise in leveraging cutting-edge tools like Rosetta, AlphaFold, and diffusion-based models for protein design make him an invaluable guide for participants looking to apply AI-driven biologics design in real-world settings.

TS10B: Introduction to Antibody-Drug Conjugate Design: Targets, Payloads, and Linkers

Detailed Agenda

In this training seminar, your instructors will take you on a journey through the history of ADC technology, the current status of the ADC field, and the most promising up-and-coming technologies that will shape the ADCs of tomorrow. We will place particular emphasis on design principles that can be applied to next generation ADC programs, whether in oncology applications or in a myriad of other therapeutic applications. We will introduce various assay strategies, experimental approaches, and technical insights that will enable participants to have both a practical and a theoretical understanding of the inner-workings of a successful ADC program. Your instructors are seasoned ADC experts that have been involved in numerous ADC programs in academia, in big pharma, and in biotechnology companies.

Robert J. Lutz, PhD, CDO, Synthis Therapeutics

L. Nathan Tumey, PhD, Associate Professor, Pharmaceutical Sciences, SUNY Binghamton

Topic areas to be covered:

An overview of the history of ADCs, emphasizing key developments and discoveries that shape the current therapeutic landscape
Principles and lessons in target selection
Antibody engineering: considerations and current trends
Conjugation and linker chemistry, past and present payload design and selection
Designing effective lead identification and screening strategies
Next-generation ADC technology: what does the future hold?
ADCs beyond oncology

Who should attend?

Seasoned scientists who are moving into the ADC field
Early career scientists in the ADC field who want a solid grasp of the “big picture” of ADC
Executives and project managers who want a solid grasp of the challenges and opportunities of ADC technology

INSTRUCTOR BIOGRAPHIES:

Robert J. Lutz, PhD, CDO, Synthis Therapeutics

Bob has been an independent consultant in the biotech/pharma industry since 2015 and has worked with multiple clients providing strategic, tactical and operational input for their research and development efforts. Prior to initiating his consulting practice, Bob held various R&D roles over a 23 year span at ImmunoGen, Inc. In his most recent position at ImmunoGen, Bob was Vice President of Translational Research and Development with responsibility for all early stage antibody drug conjugate (ADC) development programs from lead identification through phase 2. He also served as ImmunoGen’s research lead on Genentech’s FDA-approved trastuzumab emtansine (T-DM1) program. Before the ADC research position, Bob was part of ImmunoGen’s Apoptosis Technology Inc subsidiary where he led the research collaboration leading to the discovery of the BH3 domain of the BCl-2 family of death regulatory proteins. Before ImmunoGen, Bob was a research and postdoctoral fellow at the Eleanor Roosevelt Institute in Colorado. He earned his doctoral degree in Biochemistry at Brandeis University.

L. Nathan Tumey, PhD, Associate Professor, Pharmaceutical Sciences, SUNY Binghamton

L. Nathan Tumey is joined Binghamton University in 2017, following 15 years of medicinal chemistry experience in the pharmaceutical and biotechnology industry. His research focuses on the design of antibody-drug-conjugates (ADCs) for the treatment of cancer, auto-immune disorders, and rare diseases. Specific research projects include immune-stimulating antibody conjugates, glucocorticoid-antibody conjugates, legumain-cleavable linkers, and site-specific conjugation technology. He is a frequent consultant at various biotechnology and pharmaceutical companies, and serves on the scientific advisory board of multiple ADC-related organizations. Dr. Tumey received his PhD in chemistry from Duke University in 2001, under the supervision of Michael Pirrung. During his years in the pharmaceutical industry, Tumey was a key leader in multiple drug-discovery programs including the development of 5HT2c agonists for obesity, PKC-theta inhibitors for asthma, IRAK4 inhibitors for rheumatoid arthritis and antibody-drug-conjugates (ADCs) for the treatment of cancer.

Thursday, May 14, 2026 8:30 am - 5:40 pm | Friday, May 15, 2026 8:30 am - 12:15 pm

TS7C: Bioassay Development and Analysis

Detailed Agenda

This course will focus on factors to be considered in the design, development, and validation of bioassays. The course introduces terminology and important statistical tools and best practices. Examples and case studies will be provided to help solidify understanding on the topics of design and development, robustness, validation, and post-validation. Relevant pharmacopeial and EUA regulations will be highlighted.

Steven Walfish, Principal CMC Statistician, Iovance Biotherapeutics

Key Topics:

Introduction to Bioassays
Guidance Documents on Bioassays
Design & Development
Robustness Validation & Post Validation
Statistical Analysis Models
Examples/Case Studies

INSTRUCTOR BIOGRAPHY:

Steven Walfish, Principal CMC Statistician, Iovance Biotherapeutics

Mr. Walfish is Principal Science & Standards Liaison at United States Pharmacopeia (USP) responsible for the Statistics Expert Committee. Prior to this role Mr. Walfish was Principal Statistician at Becton Dickinson in Franklin Lakes, NJ responsible for supporting continuous improvement efforts and process development for worldwide operations. Mr. Walfish has held roles at GE Healthcare, Human Genome Sciences and Chiron. Steven was President of Statistical Outsourcing Services, a consulting company that provides statistical analysis and training to the FDA regulated industries. Mr. Walfish brings over 30 years of industrial expertise in the development and application of statistical methods for solving complex business issues. Steven has experience applying statistical methods to analytical method verification and validation and stability analysis. Mr. Walfish holds a Bachelors of Arts in Statistics from the University of Buffalo, Masters of Science in Statistics from Rutgers University and an Executive MBA from Boston University.