The Chain: Protein Engineering Podcast – Détails, épisodes et analyse

November 11, 2025 | What is the next modality to focus on in the next 10 years? For Bahija Jallal, CEO of Immunocore, it would be T-cell engagers. In this episode of The Chain, host Rakesh Dixit speaks with Jallal on the potential advantages of bispecific T-cell engager therapy versus T-cell receptor therapy, biggest anticipated changes in drug discovery and development in the next 10 years, and how AI is going to impact the next generation of scientists. Plus, Jallal shares her experiences as the previous president of MedImmune and at AstraZeneca, what her most rewarding project was, and the transformations and achievements that occurred under her leadership. 

Links from this episode:  
Immunocore 

As drug development pushes into more complex antibody formats, the big question is: how do you really assess developability? In this episode, host Nimish Gera speaks with Shamit Shrivastava, Ph.D., founder and CEO of Apoha, to dive into Liquid Brain, his interdisciplinary innovation that’s changing the way researchers tackle developability of challenging antibody-based drugs. Shamit breaks down what makes Liquid Brain different from traditional developability methods, reveals how it’s unlocking new possibilities for complex format development, and shares a glimpse into Apoha’s future-including an exclusive preview of what’s coming at PEGS Europe this November. 

February 21, 2025 | This episode marks the 50th anniversary of one of the most influential papers in biomedical science—the 1975 Milstein and Köhler paper on hybridoma technology, which paved the way for monoclonal antibodies. Ralph Minter, Biotech CSO/CTO, discusses this important milestone with a true pioneer in the field, Sir Greg Winter, Nobel Laureate and one of the key figures in the development of therapeutic antibodies. 

In this episode of The Chain, host Andrew Bradbury, CSO of Specifica, an IQVIA business, speaks with Randolph Lopez, CTO and co-founder of A-Alpha Bio, about how A-Alpha Bio is changing the game of protein-protein interactions with their platform AlphaSeq. Lopez delves into the origins, the process, the successes, and the possibilities of the company’s platform and how it can help with epitope mapping, affinity predictions, and off-target binding. With the data the platform generates, Lopez also discusses how this affects the potential of AI and ML. 

LINKS:    
Bionavigen
A-Alpha Bio
Specifica 

November 12, 2024 | In this episode of The Chain, host Rakesh Dixit, PhD, DABT, president and founder of Bionavigen Oncology and Regio Biosciences, speaks with Anthony Tolcher, M.D., FRCPC, cofounder of NEXT Oncology, about antibody drug conjugates (ADCs) including the role of the bystander effect, approaching targets in oncology, dual-payload technologies, the potency of new payloads, and bispecific targeting. Tolcher also shares what inspired him to pursue oncology, how he came across ADCs, and where he sees ADCs heading in the future.        

LINKS:    
Bionavigen 
NEXT Oncology 

October 15, 2024 | In this month’s episode of The Chain, host Rakesh Dixit, PhD, DABT, president and founder of Bionavigen Oncology and Regio Biosciences, and John Lambert, PhD, consultant, about antibody drug conjugates (ADCs) then, now, and beyond. Lambert shares his experiences from his decades-long career at ImmunoGen, why ADCs are more successful now compared to in the past, and where he sees ADCs going forward. He also discusses his thoughts on the half-life of diffusible payloads, the toxicity of the bystander effect, and more.  

LINKS:
Bionavigen
ImmunoGen 

September 10, 2024 | In this episode of The Chain, host Nimish Gera speaks with Tariq Ghayur, of Tariq Ghayur Consulting, LLC and Entrepreneur in Residence, FairJourney Biologics (and a fellow host of the podcast), about the current renaissance of bispecifics and ADCs, the impact of AI in pharmaceuticals, and what to watch out for in the biopharma space in the next few years. Ghayur also shares his journey from BASF Pharma to AbbVie, what it was like when the industry shifted its focus from small molecules to biologics, and the major differences between doing a postdoc in academia versus in the industry. 

In this episode of The Chain, host Nimish Gera, Ph.D., vice president of biologics at Mythic Therapeutics, speaks with Peyton Greenside, CSO and co-founder of BigHat Biosciences, about the role of AI and machine learning in antibody engineering and targeting complex modalities, including bispecifics and ADCs. Greenside also discusses the work her organization does, what BigHat is doing to ensure the quality of data to train their AI models with, the methods of approaching harder targets such as GPCRs, and certain properties that AI can optimize better. 

In this episode of The Chain, host Brandon DeKosky, associate professor at MIT, speaks with Andrew Kruse, PhD, professor of biological chemistry and molecular pharmacology at Harvard University, about protein signaling and structural biology. Kruse explains what exactly bias signaling is and discusses the problems he and his team are working to resolve, as well as the tools they use to work out the dynamics of structures. He also shares the findings in signaling receptors and biology that he’s most excited about, recent advancements that have caught his attention, and the new directions for him and his lab. 

his special episode of The Chain features a panel of industry experts who discussed AI and ML in antibody discovery and engineering at this year’s PEGS Boston event. Peter Tessier, professor at the University of Michigan; Andrew Bradbury, CSO at Specifica; Andrew Waight, Senior Director of Machine Learning, Discovery Biologics & Protein Sciences at Merck Research Labs; Peyton Greenside, Co-Founder & CSO of BigHat Biosciences; and Paolo Marcatili, Director of Antibody Design at Novo Nordisk take on where AI/ML has the biggest impact, what the hype is in the use of AI/ML in antibody discovery, how new AI/ML methods are being benchmarked against traditional discovery methods, and what controls should be used in an AI/ML discovery or optimization campaign.