A leading AI technology conglomerate has strategically positioned life sciences as a core business focus. On September 16, market sources revealed that Anew Labs, the AI pharmaceutical arm spun off from ByteDance, has successfully completed a $290 million initial funding round, achieving a post-investment valuation of approximately $1.5 billion.
ByteDance maintains a controlling stake of 56% in the newly independent entity. The funding round was spearheaded by HSG (formerly Sequoia China), IDG Capital, and Hillhouse Investment, with 5Y Capital serving as a co-lead investor. Strategic participants include Sino Biopharmaceutical and the Shanghai Future Industry Fund. ByteDance had not issued an official response at the time of reporting.
Anew Labs originated as ByteDance's internal AI for Science drug discovery team, established in 2021 under the leadership of Liu Kai, with a core team of approximately 50 members. ByteDance's AI Lab had begun recruiting AI pharmaceutical talent as early as late 2020. In June 2026, ByteDance executed a complete spin-off of this business, transferring all team members, algorithmic platforms, and pipeline assets into the new entity. Internal team members indicated that the project had been operating "under the surface" for an extended period. The company maintains offices in Shanghai, San Francisco, and Singapore.
Industry analysts attribute ByteDance's decision to divest this business line to fundamental differences in operational logic. AI drug discovery adheres to the "double ten law" of pharmaceutical research—requiring a decade of development and one billion dollars in investment, with validation cycles measured in years. In contrast, internet businesses thrive on rapid iteration. When these two distinct operational rhythms coexist within a single organization, misaligned incentives and evaluation criteria inevitably emerge. Independent operation facilitates connections with industrial capital and attracts specialized pharmaceutical talent.
Post-spin-off, Anew Labs positions itself as an end-to-end AI drug discovery company, with its core pipeline featuring the world's first small molecule inhibitor capable of simultaneously suppressing three classes of IL-17 family dimers.
ByteDance's restructuring reflects a broader trend among major AI companies entering biopharmaceutical development. Anthropic CEO Dario Amodei has identified life sciences as one of the company's "most strategically significant" areas, driving the organization's evolution from providing tools to directly developing proprietary drug pipelines.
Leading companies are diverging into two primary strategic paths: "proprietary pipeline development" and "platform provision." The former involves companies directly undertaking drug development while bearing pipeline failure risks. In April 2026, Anthropic acquired the eight-month-old AI pharma startup Coefficient Bio for approximately $400 million, launching autonomous drug development initiatives. Similarly, Isomorphic Labs, spun off from Google's DeepMind, completed a $2.1 billion Series B round in May, simultaneously collaborating with pharmaceutical partners while advancing its own proprietary drug pipelines.
Companies pursuing the "platform provision" route supply AI tools, computing power, or models to pharmaceutical companies without directly owning drug pipelines. In January, NVIDIA and Eli Lilly established a joint AI innovation laboratory with a $1 billion investment commitment over five years, constructing a closed-loop dry-wet R&D process capable of two-hour operational cycles. OpenAI released GPT-Rosalind, a specialized life sciences model, in April, trained on 50 biological workflows. Pharmaceutical giants including Amgen and Moderna have already integrated it into their R&D processes.
The proprietary pipeline approach asserts that AI has matured sufficiently to lead drug discovery, while the platform approach maintains that AI's greatest value lies in lowering industry-wide R&D barriers. Both paths share a common premise: traditional drug development models have become unsustainable, and AI is transitioning from an optional auxiliary tool to an indispensable core production capability.