Newsletter

Are we getting closer to curing Alzheimer’s Disease?

---- Beta-amyloid and beyond

On January 6, 2023, FDA approved a new drug for Alzheimer’s Disease (AD), Leqembi (previously known as lecanemab). This is the second FDA-approved AD drug targeting the biological roots of the disease pathology, instead of temporarily relieving the symptoms. Yet not a cure for AD, Leqembi can buy some time for early-stage AD patients by delaying cognition decline and memory loss. The success of Leqembi provided evidence supporting the Aβ theory, which the field is drifting away from after the repeated failures of Aβ-targeting agents in clinical trials.

Does it mean we are getting closer to curing AD? To shed light on this question, I will dive into AD therapeutic development. In this post, I will focus on the beta-amyloid hypothesis and what makes lecanemab the best Aβ targeting therapy so far.

Machine learning-powered drug discovery: Now and Tomorrow

Part II. Platform, business model, scaling, and emerging trends

The first generation of AI-first biotech companies started to emerge around 2012. So far, there are over 200 companies in this space. I took a closer look into 40+ AI-first companies that developed ML-based platforms directly contributing to discovering new drug candidates or repurposing existing drugs. As these companies matured, patterns started to emerge. They showed some defining characteristics that are fundamentally different from typical asset-centric biotech companies:

Platform-first company structure
Versatile business models
Scaling up like tech companies

Machine learning-powered drug discovery: Now and Tomorrow

Part I: Application, progress, and ecosystem dynamics

Machine learning (ML) are making inroads in drug discovery during the past decade. Vertically, ML has been applied to all steps of the drug discovery funnel and driven new efficiencies and insights across the whole value chain. Horizontally, ML has been adopted by multiple key players including biopharmas, big tech, AI-first biotech companies, and a variety of service providers. With this post, I will give an overview on where we stand now with ML-powered drug discovery.