Monoclonal antibodies (mAbs) represent a rapidly growing therapeutic class, yet their development and manufacturing remain costly - often exceeding $95–$200 per gram. These high costs stem from challenges in manufacturability, stability, and process development. Early sequence optimization offers a powerful solution. By integrating computational prediction with high-throughput empirical workflows, developers can identify and mitigate liabilities - such as aggregation, poor stability, or unfavorable post-translational modifications - before they impact downstream processes.

This proactive approach not only accelerates timelines to first-in-human studies but also reduces cost of goods (CoGs) and improves therapeutic quality. Case studies demonstrate that optimized mAbs exhibit dramatically lower aggregation under stress conditions and enhanced serum stability, translating into higher yields and potentially lower patient doses.

Discover how advanced AI/ML-driven tools and systematic optimization strategies can transform mAb development - making life-changing therapies more accessible and affordable.

The white paper explains how Just – Evotec Biologics uses its J.MD™ suite of AI/ML technologies to analyze and optimize antibody candidates before clinical development, enabling the selection of highly developable and manufacturable leads.