Prozomix and Ginkgo Bioworks Collaborate on Next-Gen Enzyme Development for Sustainable API Manufacturing
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Insights
The partnership between Ginkgo Bioworks and Prozomix presents a significant development in the field of biocatalysis, particularly for the pharmaceutical industry. Biocatalysts are increasingly recognized for their potential to streamline the manufacturing of active pharmaceutical ingredients (APIs) by offering environmentally friendly alternatives to traditional chemical synthesis. The collaboration aims to combine Ginkgo's AI/ML capabilities with Prozomix's extensive enzyme sequence data to enhance the diversity and performance of enzyme plates used in API manufacturing.
From an industry perspective, this partnership is expected to address the growing demand for sustainable and cost-effective manufacturing processes. The integration of AI-driven models to predict and design new enzyme functionalities could lead to more efficient production routes and potentially reduce the cost of goods sold (COGS). The initiative could also influence stock market sentiment as investors often look favorably upon innovations that promise to improve margins and sustainability in the pharma sector.
The emphasis on sustainability within the pharmaceutical industry is a response to both regulatory pressures and consumer demand for greener practices. The use of biocatalysts fits into a broader trend towards sustainable manufacturing, which includes reducing waste, lowering energy consumption and minimizing the use of hazardous chemicals. The partnership's focus on producing enzyme plates that enable more sustainable API manufacturing methods aligns with these goals and could set a precedent for other companies in the sector.
Furthermore, the agreement between Ginkgo and Prozomix could have implications for the overall sustainability of the pharmaceutical supply chain. By enhancing the efficiency and reducing the environmental impact of API production, this partnership could contribute to a more positive public image for the involved companies and the industry at large. This, in turn, could have a favorable impact on the companies' market valuation in the long term, as sustainability becomes an increasingly critical factor in investment decisions.
The technical aspect of the partnership involves leveraging Ginkgo's AI/ML models to sift through vast amounts of enzyme sequence data, aiming to identify and optimize biocatalysts for specific chemical reactions in API production. The ability to rapidly screen and iterate enzyme candidates can significantly shorten the development timeline for new drugs. This acceleration could be a game-changer for pharmaceutical companies, enabling them to bring new therapies to market more quickly and at a potentially lower cost.
Moreover, the promise of next-generation enzyme plates to outperform traditional ones in terms of diversity and capability could resolve some of the limitations that currently hinder biocatalytic applications in pharma. If successful, this could lead to a broader adoption of biocatalysis in the industry, influencing not only the way APIs are manufactured but also the competitive landscape of pharmaceutical manufacturing technologies.
The partnership combines Ginkgo's AI/ML and enzyme engineering expertise with Prozomix's wealth of enzyme sequence data to create best-in-class enzymes for API manufacturing
This agreement also marks Prozomix's entry into the Ginkgo Technology Network, a groundbreaking ecosystem of cutting-edge technology partners dedicated to driving innovation in customer R&D programs. Ginkgo's Technology Network brings together a diverse array of partners, spanning AI, genetic medicines, biologics, and manufacturing, with the aim of integrating their capabilities to provide customers with robust end-to-end solutions for successful R&D outcomes. With Prozomix now in the Technology Network, Ginkgo customers will have access to Prozomix's scalable contract manufacturing services, including enzyme samples from mg to kg scale.
For several decades, demands for both improved supply chain sustainability and reduction of costs of goods sold has driven the pharma industry towards the adoption of biocatalysts in commercial API manufacturing. Existing enzyme plates offer users an opportunity to rapidly screen potential candidates early in development to identify and de-risk the use of biocatalysts capable of supporting specific reactions in API manufacturing routes. As such, biocatalyst adoption largely depends on the diversity and performance of the enzymes available in these plates.
Prozomix and Ginkgo are partnering to usher in a new generation of biocatalysts built off of sequences and activity data from previous enzyme libraries. Ginkgo will build class-specific AI models informed by enzyme sequences and data from its own massive metagenomic database as well as Prozomix's enzyme libraries and associated screening data. These models can then be used to discover novel functional enzyme sequences. Prozomix intends to then use next-gen enzyme libraries, designed by these models, to manufacture novel enzyme plates.
Together, the partners expect these next-gen enzyme plates to have a diversity and performance that traditional plates lack, potentially unlocking biocatalytic opportunities where previous plates have failed. These plates will be freely available to all pharma process chemistry groups, provided that screening data is shared back with Ginkgo to drive further refinement of the Ginkgo AI/ML models.
Simon J. Charnock, CEO of Prozomix: "With a global reputation for de-risking early stage biocatalytic processes, we believe the Ginkgo partnership will keep Prozomix at the forefront of best in class biocatalyst provision throughout the AI revolution, enabling our customers to continue saving and improving more lives."
Cindy Chang, Senior Director, Business Development at Ginkgo Bioworks: "API manufacturing is poised to greatly benefit from the latest in enzyme engineering and AI/ML enzyme models. We are so excited to partner with Prozomix to get enzymes into as many API routes as possible and help partners meet both their COGs savings and sustainability goals."
To learn more about Ginkgo's Enzyme Services, please visit https://www.ginkgobioworks.com/offerings/biopharma-enzyme-services/
About Ginkgo Bioworks
Ginkgo Bioworks is the leading horizontal platform for cell programming, providing flexible, end-to-end services that solve challenges for organizations across diverse markets, from food and agriculture to pharmaceuticals to industrial and specialty chemicals. Ginkgo's biosecurity and public health unit, Concentric by Ginkgo, is building global infrastructure for biosecurity to empower governments, communities, and public health leaders to prevent, detect and respond to a wide variety of biological threats. For more information, visit ginkgobioworks.com and concentricbyginkgo.com, read our blog, or follow us on social media channels such as X (@Ginkgo and @ConcentricByGBW), Instagram (@GinkgoBioworks), Threads (@GinkgoBioworks) or LinkedIn.
GINKGO BIOWORKS INVESTOR CONTACT:
investors@ginkgobioworks.com
GINKGO BIOWORKS MEDIA CONTACT:
press@ginkgobioworks.com
About Prozomix
Exploring unchartered metagenomic sequence space in collaboration with big pharma and leading academics for over a decade, Prozomix offers the largest, most diverse and free-to- screen Biocatalysis Enzyme Toolkit for API synthesis on the global market. A combined R&D and manufacturing site, purchased by Prozomix and built-out specifically in response to customer demand, now offers seamless scaled-hit production to kgs dry powder within 1 week of request, and has cemented a global reputation for de-risking early stage bioprocess development. A private, profitable and progressive
PROZOMIX CONTACT:
info@prozomix.com
Forward-Looking Statements of Ginkgo Bioworks
This press release contains certain forward-looking statements within the meaning of the federal securities laws, including statements regarding the capabilities and potential success of the partnership and Ginkgo's cell engineering platform. These forward-looking statements generally are identified by the words "believe," "can," "project," "potential," "expect," "anticipate," "estimate," "intend," "strategy," "future," "opportunity," "plan," "may," "should," "will," "would," "will be," "will continue," "will likely result," and similar expressions. Forward-looking statements are predictions, projections and other statements about future events that are based on current expectations and assumptions and, as a result, are subject to risks and uncertainties. Many factors could cause actual future events to differ materially from the forward-looking statements in this press release, including but not limited to: (i) volatility in the price of Ginkgo's securities due to a variety of factors, including changes in the competitive and highly regulated industries in which Ginkgo operates and plans to operate, variations in performance across competitors, and changes in laws and regulations affecting Ginkgo's business, (ii) the ability to implement business plans, forecasts, and other expectations, and to identify and realize additional business opportunities, (iii) the risk of downturns in demand for products using synthetic biology, (iv) the uncertainty regarding the demand for passive monitoring programs and biosecurity services, (v) changes to the biosecurity industry, including due to advancements in technology, emerging competition and evolution in industry demands, standards and regulations, (vi) the outcome of any pending or potential legal proceedings against Ginkgo, (vii) our ability to realize the expected benefits from and the success of our Foundry platform programs, (viii) our ability to successfully develop engineered cells, bioprocesses, data packages or other deliverables, and (ix) the product development or commercialization success of our customers. The foregoing list of factors is not exhaustive. You should carefully consider the foregoing factors and the other risks and uncertainties described in the "Risk Factors" section of Ginkgo's annual report on Form 10-K filed with the
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