Especially after the epidemic, top pharmaceutical companies including Pfizer, Roche, Merck, AstraZeneca, GlaxoSmithKline, Sanofi, Johnson & Johnson, etc., have accelerated their embrace of artificial intelligence, either by cooperating with AI companies, or by acquisitions or acquisitions. Self-built AI department.
From molecular experiments to manufacturing supply chains and even marketing, AI has shown great potential throughout the Buy email list pharmaceutical value chain.
The integration process of AI and pharmaceuticals is mainly based on two modes:
VIC model, namely "VC (Venture Capital) + IP (Intellectual Property) + CRO (R&D Outsourcing)", in which AI companies, as technology outsourcing, provide pharmaceutical companies with solutions to reduce costs and increase efficiency;
The AI-Driven model is dedicated to using AI technology to drive analysis and prediction to discover new compounds and proteins, and to develop innovative drugs by itself.
Compared with outsourcing service providers that are "intelligent in traditional industries", the AI company "Self-reliance Shantou" Pharmaceutical has more room for business imagination, and it has indeed attracted large-scale financing and giants to enter the market in the past few years. In 2021, the scale of investment and financing in this field in China will exceed 8 billion.
The most representative of them is Isomorphic Labs, an AI drug company established by Google’s parent company Alphabet not long ago. Its founder is the CEO of AI pioneer DeepMind, which developed the AlphaFold2 algorithm. Obviously, Google is also very optimistic about the prospect of "making a big impact" in the field of biology with cutting-edge AI technology.
So here comes the problem. The field of biopharmaceuticals is a field with extremely high barriers to expertise. AI has been involved in pharmaceuticals for 15-20 years. During this period, machine learning methods have been used in drug discovery and clinical trials. In 2000, the use of machines for "high-throughput screening" has been applied to compound testing, but so far, there has been no successful case of verifying that AI can "walk independently" innovative drugs.