LEADING EDGE BIO

Lessons from Antibodies, Peptides, AI, and Cell Therapy Every biotechnology company believes it has a platform. Far fewer have one that large pharmaceutical companies actually want to partner. Over the past two decades, I've watched our industry transform through successive waves of innovation, from monoclonal antibodies and directed evolution to cell therapy, gene therapy, AI-enabled drug discovery, and programmable biologics. Some platforms generated billions of dollars in

For the past decade, biopharma companies have invested heavily in artificial intelligence to improve target identification, protein engineering, clinical trial design, biomarker discovery, pathology, pharmacovigilance, and commercial operations. Until recently, however, relatively little attention was paid to governing those AI systems. That era is ending. The emergence of healthcare AI governance frameworks—including certification programs and industry playbooks—signals that

One of the more fascinating opportunities I encountered recently involved a highly academic organization developing an AI-driven platform intended to transform how biomedical research and pathology data are interpreted. The science was exceptional. The team consisted of world-class researchers. The technology held genuine promise to accelerate biomarker discovery, improve translational research, and ultimately support more precise drug development. The challenge wasn't the sc

One of the greatest misconceptions in biotechnology is that success comes from having the best molecule. It doesn't. More often, success comes from having the best portfolio strategy. Drug discovery is only one component of building a durable company. The organizations that consistently outperform their peers understand that every asset, indication, biomarker, companion diagnostic, platform technology, and strategic partnership should reinforce the others. They don't simply d

Every external collaboration is an option on the future. The question isn't simply whether today's technology works. It's whether the partnership expands what becomes possible tomorrow. That distinction separates transactional business development from strategic external innovation.

Innovation has become a team sport. Those who understand how biotechnology companies, investors, pharmaceutical companies, and technology providers work together will be best positioned to shape the next generation of medicines.

The future of drug discovery may not lie in finding better needles in the haystack. It may lie in weaving entirely new haystacks.

Artificial intelligence has advanced at an astonishing pace. Large language models (LLMs) can now draft scientific reports, summarize literature, analyze contracts, generate software code, and even assist with regulatory documentation. Yet despite these impressive capabilities, one critical challenge remains: how do organizations trust AI-generated outputs enough to make real business decisions? The answer is increasingly becoming clear. The future of enterprise AI is not sim

The Strategic Art of Knowing When to Spin Out a Biotech Platform Every biotechnology company eventually faces a pivotal strategic question. Should this technology remain part of the portfolio? Should it become its own company? Or should it be partnered with someone better positioned to maximize its value? These decisions are often viewed as financial or organizational exercises. In reality, they are portfolio strategy decisions. The answer can determine whether a promising te