Does the integration of AI technology herald the arrival of the industrialization of biomedical science?

liu, tempo Date: 2021-07-19 11:34:28
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The biopharmaceutical industry has always had the pain points of “high investment, high risk, and long cycle”, and it is accompanied by the entire pharmaceutical R&D, testing and production links. In recent years, the combination of artificial intelligence and biomedicine has emerged. Using the cognitive capabilities of AI technology (strong learning ability, intelligent prediction, and reproducible and traceable characteristics), artificial intelligence technology has solved the main problems faced by biology. The pain points have promoted the transformation of biopharmaceuticals from labor-intensive to smart technology in many aspects.

biopharmaceutical industry


1. Artificial Intelligence + Disease Diagnosis



Human brain storage is very limited and will gradually be forgotten, but learning a large amount of clinical image data through AI technology and training diagnostic models can intelligently diagnose and assist clinicians with high accuracy. At present, successful cases of using AI technology such as diabetic retinopathy, macular degeneration and diabetic macular edema, such as blindness, skin cancer, breast cancer, and cervical cancer, have been reported.



According to reports, SK Biopharmaceuticals uses AI technology to develop advanced treatment methods for non-small cell lung cancer, and an AI technology platform to identify the relationship between chronic kidney disease and diabetic patients.



2. Artificial Intelligence + New Drug Research and Development



The pain points of the “two highs and one long” in the pharmaceutical industry are particularly obvious in the new drug research and development stage. Traditional medical research and development requires a large amount of labor to do intensive tasks repeatedly, and it often takes several years to more than ten years, which leads to huge new drug research and development costs, and there are more uncertain factors that affect the risk of new drugs being launched. With its high learning ability and high accuracy rate, artificial intelligence technology has opened a green channel for the research and development of new drugs.



According to reports, AbbVie’s AI-based patient monitoring system is used to better understand its current Phase 2 research on patients with schizophrenia, thereby increasing its data insights and reducing clinical trials, and using AI technology to optimize its manufacturing process. ; AstraZeneca uses AI and machine learning to develop new therapies for chronic kidney disease and idiopathic pulmonary fibrosis, and to accelerate drug innovation, thereby tracking the nature of diseases such as Parkinson’s disease.


3. Artificial Intelligence + Genetic Data Analysis



AI technology can study disease-causing gene mutations more comprehensively based on functional units, eliminating the single detection of the relationship between a single point mutation and the disease being studied in the traditional genetic data analysis process, greatly shortening time and saving costs.

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