AI is Not a Magic Bullet

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AI cures disease only if the cures already are within a set we have measured, waiting for a better approach. One problem: they do not. Most of human biology has never been observed with detail and understanding sufficient to target a therapy. No amount of inference recovers data that was never collected. The need for AI in life sciences and drug discovery is indisputable. Of roughly ten thousand known human diseases, the large majority have no approved therapy at all; among rare diseases, the figure approaches ninety-five percent. Most approved drugs slow a disease rather than stop it. For the bulk of human illness, medicine offers management or nothing. Humans are systems, and the hardest diseases are within human systems and unsolved. The constraint is not intelligence. It is understanding the system.

The Computable Molecule

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Artificial intelligence is no longer a tool that the life sciences industry is adopting. It is a force that is relocating where value is created and who captures it. Three costs are collapsing at once: drug discovery, company independence, and the ability to reach the patient. Each of these costs was, for forty years, a moat protecting the incumbents who could afford to pay it. In addition, the capacity to discover and manufacture medicine has become a strategic infrastructure in the same category as energy, semiconductors, and compute. The molecule has become computable. The architecture of value creation in life sciences has changed.

The AI Molecule

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Artificial intelligence is reducing the time and cost required to discover new drug candidates. New forms of late-stage capital are allowing better companies to stay independent longer. Direct-to-patient distribution is weakening Pharma’s control of the commercial channel. Together, these changes alter the architecture of biotechnology. The molecule is being separated from the old machine that used to deliver it. This is a structural change in how drugs are discovered, financed, developed, negotiated, and delivered. Biotech companies will build discovery systems, develop clinical evidence, control proprietary data, preserve financing options, and reach patients more directly.

The Broken Road of Innovation

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Discovery, innovation, and practical application are never a straight line and, the best analogy is “the broken road.” Our greatest discoveries and advancements have confusing, uneven, and broken pathways that often lead somewhere astonishing – even though at the outset the initial steps could never envision this as a final destination. Artificial intelligence is the embodiment of this concept. A powerful tool that can lead anywhere given the imagination and unlimited creativity of its users. There may be nowhere more impactful, generating therapies for unmet medical needs in record time, than artificial intelligence’s ability to mimic evolution in minutes. The real outcomes are still unpredictable, but the potential is unfathomable. AI languages that produce pictures seem to be initially relegated toward a combination of Tik-Tok influencers, outraged artists, and those with limited imaginations and creative skills. But now, AI-generated pictures can use text to direct specific protein designs with properties of shape, size, and/or function that make it possible for these new proteins to perform specific tasks on demand. This breakthrough may lead to more efficient and effective drug development and, the discovery in minutes of what evolution would otherwise have taken millions of years to develop.