A Collaboration on Multi-Target, Multi-Modality Research between Amgen and Generate Biomedicines

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On Thursday, Amgen and Generate Biomedicines established a research partnership to find and develop protein therapies for five clinical targets spanning several therapeutic areas and modalities. Amgen will pay $50 million in upfront cash for the first five programs, with a potential transaction value of $1.9 billion-plus future royalties, as part of the research agreement, and will have the option to nominate up to five additional programs at an additional cost. Amgen will pay up to $370 million in future milestones and royalties in the low double digits for each program. Amgen will also take part in Generate’s next round of funding. There were no other terms given.

Both companies will work together to discover and develop protein therapeutics for patients using Generate’s machine learning-enabled technology platform.

Amgen has invested over the last decade in the integration of wet lab high throughput automation and dry lab computational biology, recognizing the particular challenges of multispecific drug development. Amgen’s generative biology strategy has resulted in the formation of a Digital Biologics Discovery group, which will capitalize on the company’s pioneering capabilities in biology, automation, and protein engineering

The goal of Amgen’s generative biology program is to integrate its biologics knowledge with developing sequence-based drug design technology to develop complicated multispecific medications for a variety of difficult-to-treat disorders. By combining Amgen’s biologics drug discovery expertise with Generate Biomedicines’ Artificial Intelligence (AI) platform, multispecific drug design can be facilitated even further, with discovery timelines shortened and potential lead molecules with predictable manufacturability and clinical behavior generated.

“We are now at a scientific hinge point, where computational approaches can advance our knowledge of biology and further drive our ability to design the right molecule for some of the most challenging targets. We believe Generate Biomedicine’s integrated with silico design and wet lab capabilities combined with Amgen’s strength in protein engineering can accelerate our drug discovery efforts, generating novel protein sequences with optimal therapeutic properties,”

said David M. Reese, M.D., executive vice president of Research and Development at Amgen.

“This agreement is a recognition of the transformative power of our generative biology platform. We’re proud to partner strategically with Amgen to combine their world-leading expertise in engineering protein-based therapies with our unique machine learning-enabled drug generation platform. With our technology platform, we are able to expand beyond just proteins that are found in nature – creating de novo, purpose-built proteins capable of performing any desired function under timelines that have not been possible through other approaches,”

said Mike Nally, chief executive officer, Generate Biomedicines and CEO-partner, Flagship Pioneering.

Generate Biomedicines is a leader in generative biology, a ground-breaking approach to drug discovery and development that uses machine learning and artificial intelligence to design novel protein therapies. 

Over the last three years, closed-loop learning on tens of thousands of computationally generated and broadly experimentally characterized novel proteins has improved the company’s technology platform, which analyses hundreds of millions of known proteins looking for statistical patterns linking amino acid sequence, structure, and function. When used in conjunction with the company’s wet lab research, the platform may quickly manufacture antibodies, peptides, enzymes, cell, and gene therapies to address a variety of therapeutic needs. This has allowed the business to discover the generalizable rules by which a linear amino acid sequence encodes protein structure and function, and to create therapies for previously intractable targets at a previously unheard-of speed and scale.

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