Client Challenge
This company focuses on API manufacturing.
Traditional process optimization relies heavily on expert experience and sequential testing, adjusting only a few parameters at a time.
This makes it difficult to evaluate multi-parameter interactions, resulting in long development cycles and inefficient use of resources.
The client needed a systematic approach to parameter selection and process optimization to reduce cycle time and dependence on experiential decision-making.
Solution Implemented
導入BioFusion Analytics AI Agent，透過 AI 進行細胞培養條件建模與產量預測，預測出具高抗體表現潛力的細胞株，協助研究團隊大幅縮減需實際培養與驗證的候選細胞數量，將篩選範圍精準聚焦於最具生產優勢的細胞株，顯著提升篩選效率與抗體產量。
Results Achieved
The AI models accurately identified high-productivity clones, reducing cultivation and validation workload while lowering material and labor costs.
Even with the same development timeline, overall production costs decreased by approximately 75%, greatly improving resource efficiency.
