29/12/2024
Our first paper with Dominika Wilczok is now out in the journal of the American Society of Clinical Pharmacology. This paper looks at the many inefficiencies in the AI-powered drug discovery industry and explains why we have not yet seen the first AI-discovered drug reaching approval even in the scenarios where companies cut corners by in-licensing or repurposing existing drugs for going after old targets. It contains valuable advice for the AI drug discovery and pharma companies as well as to the regulators. In the new year, let's work together to accelerate this industry and make real change.
Referenced the work by the St Gallen Consortium Alexander Schuhmacher and Oliver Gassmann, BCG Madura Jayatunga and Chris Meier, BiopharmaTrend, Andrii Buvailo . and other analysts.
The pharmaceutical industry lacks benchmarks on the preclinical R&D side. Trillions of dollars spent over decades and AIDD companies, investors, and pharma companies don't know what to optimize for and how to evaluate the companies. There are very few studies looking deep into preclinical R&D, time, cost, POS, and, most importantly, novelty, and potential patient and market impact.
Without real benchmarks we will have many naked emperors walking around and since the program timelines often span decades and multiple carriers, no one will be held accountable and responsible.
Since the deep learning revolution of the early 2010s, significant efforts and billions of dollars have been invested in applying artificial intelligence (AI) to drug discovery and development (AIDD)...
