Google and Japan’s Chiral Share the Stage to Co-Envision the Next Decade of Biopharma
TherapiAI, a pioneering biotech AI startup, hosted the “AI-Driven Future of Biopharma: From R&D Innovation to Digital Twin” seminar today (7th) at the Taipei Bioinnovation Park. During the event, the company officially unveiled its two breakthrough technology platforms—Digital Twin and Biologics AI Agent—designed to empower CDMOs by significantly reducing trial-and-error costs and enhancing R&D success rates.
The forum convened a distinguished panel of speakers, including Dr. Yu-Chang Chang from Google, Koji Umeda, COO of the Japanese AI scientific computing startup Chiral, and the executive leadership team of TherapiAI. The speakers took turns presenting the latest trends and practical applications of AI within the biopharmaceutical sector. This event also marked the first joint public appearance in Taiwan for TherapiAI and Chiral since the formalization of their Asia-Pacific strategic partnership in April this year.
International and Local Experts Convene to Present a Comprehensive Blueprint from R&D to Implementation
Following the opening remarks by TherapiAI CEO Michael Han, the seminar’s first keynote was delivered by Dr. Yu-Chang Chang from Google. Dr. Chang shared insights on how Google’s models can be extended to scalable application scenarios within the biopharmaceutical industry. He elucidated the evolution of AI from mere “search technology” to applications that seamlessly integrate into BioPharma workflows, ultimately helping enterprises enhance R&D efficiency and accelerate their digital transformation journey.
Koji Umeda, COO of the Japanese macromolecule design startup Chiral, introduced how Chiral’s no-code scientific computing platform accelerates the drug discovery process. Furthermore, TherapiAI’s CTO Alicia Li and Dr. Jun-Jie Chen showcased the latest advancements of the company’s newly launched Digital Twin platform in next-generation protein process design. They highlighted the transition for CDMOs from descriptive AI to fully automated AI, providing a holistic overview of how AI facilitates the entire journey—from protein R&D and manufacturing to real-world implementation.
TherapiAI Unveils Four Core Prediction Engines to Tackle Industry-Wide 60-80% Failure Rates
Traditional R&D workflows for protein biopharmaceuticals have long been bottlenecked by a failure rate of 60% to 80%. A single late-stage clinical setback translates to a staggering $20 million in sunk costs and a delay of at least 18 months. As market windows narrow and patent lifespans contract, the “trial-and-error” mindset traditional to CDMOs has become the most expensive liability in modern drug development.
TherapiAI’s Digital Twin platform is engineered to solve exactly these challenges. Our newly launched platform provides a comprehensive simulation of the physiological characteristics of protein drugs in a virtual environment. Its core architecture features four key engines: 3D Protein Structure and PTM Analysis for handling protein folding and post-translational modifications; Immunogenicity Screening to filter out potential rejection risks at an early stage; Codon Optimization to maximize production yields; and Manufacturability Prediction to simulate thermal stability and solubility, exposing potential scale-up bottlenecks before they occur. By integrating these four components into a sophisticated “in silico” funnel, we enable CDMOs to eliminate high-risk factors on “Day 0.” This transformative approach saves between $5 million and $20 million in R&D costs per project and compresses experimental timelines from years down to months.
Proven Results for CDMO: Achieving 90% Cell Imaging Accuracy and 20% Reduction in Operating Costs
Furthermore, TherapiAI’s “AI Agent Matrix” has already demonstrated profound impact through real-world implementation. For instance, a Taiwanese CDMO deployed TherapiAI’s AI-powered cell imaging analysis, achieving a 90% accuracy rate in cell growth prediction and an 84% reduction in material waste. Additionally, a Cell and Gene Therapy (CGT) partner successfully lowered operating costs by 20% through AI-assisted process optimization. These cases underscore that Digital Twin technology is far more than a virtual lab for the R&D phase; it is a foundational operational infrastructure that enables CDMO and CGT providers to maximize yield and optimize cost control.
Michael Han, Founder and CEO of TherapiAI: CDMOs Must Make the Right Decisions on Day 0
Michael Han, Founder and CEO of TherapiAI, stated: “The next decade of biopharmaceuticals will be driven by a Digital Twin ecosystem capable of continuous learning and optimization, where AI plays a pivotal role. By bridging Google’s breakthroughs in foundation models, Chiral’s deep expertise in scientific computing, and TherapiAI’s integration of these capabilities into real-world CDMO workflows, we aim to empower CDMOs to make the right decisions on ‘Day 0’—ultimately optimizing costs and maximizing success rates.”
The seminar also featured an on-site showcase of TherapiAI’s Digital Twin applications in real-world BioPharma scenarios. Furthermore, participating enterprises were invited to a complimentary trial of the platform, providing them with a hands-on opportunity to experience firsthand how AI accelerates decision-making and optimizes complex workflows.
