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How Can AI Be Integrated into Pharmaceutical Company’s Overall Strategy?


Artificial Intelligence (AI) has the ability to transform the entire pharmaceutical industry. At present, almost every large pharmaceutical company plan to invest in AI technology to varying degrees.
  • Author Name: Lisa George
Editor: Lisa George Last Updated: 21-Jul-2020

Artificial Intelligence (AI) has the ability to transform the entire pharmaceutical industry. At present, almost every large pharmaceutical company plan to invest in AI technology to varying degrees. AI is being increasingly used in drug target discovery, pre-clinical and clinical research, and post-market activities.

Four modes of AI

Although AI itself does not have a consistent definition, it broadly refers to a system that can operate independently to a certain extent and can continuously optimize the process through iteration. In the field of life sciences, we divide AI into the following four modes:

  1. Machine learning

Process data input and continuously repeat the optimized calculation process through the results of each output.

  1. Deep learning

Based on machine learning, it is possible to use logical structures similar to biological neural networks to build algorithms.

  1. Natural Language Processing Institute

Sophisticated automated language recognition system can communicate with humans, not just provide simple feedback on stylized requirement.

  1. Robots and Internet of Things

Collect, integrate, and share different types of information through connections between devices.

The four application modes of AI will accelerate or even replace some steps in the traditional drug development process, and ultimately achieve the purpose of significantly improving the success rate of R&D and greatly reducing the cost of R&D. Currently, 90% of the clinical development of drug candidates cannot be approved for marketing, resulting in an average drug development cost of approximately US$1.4 billion. The application of AI will hopefully and significantly reduce the R&D costs of the entire pharmaceutical industry.

Some large pharmaceutical companies have begun to use AI to accelerate drug research and development. For example, Novartis uses AI to capture clinical data from multiple internal data sources to predict and monitor patient recruitment, cost, and quality in clinical trials. Novartis claims that the application of this technology allows patients recruiting time to be shortened by 10% to 15%. Faster drug development and higher chances of approval can also help pharmaceutical companies enjoy a longer post-market patent protection period and earn more profits. In addition, AI also has the ability to help optimize patient support after the drug is approved.

What should pharmaceutical companies do in the future?

The broad prospects of AI have led many pharmaceutical companies to include it in their business strategies. At the same time, with the continuous evolution of technology itself, AI companies are also continuously improving their products to meet the different needs of pharmaceutical companies. Driven by the above factors, it is foreseeable that in the next decade, AI technology will flourish in the field of biological sciences (especially drug discovery). The development of AI technology will significantly change the operation of pharmaceutical companies and replace some traditional time-consuming technologies (such as high-throughput screening), and these traditional technologies will only be used in some specific scenarios or fields. As the artificial intelligence market is currently highly fragmented and strictly regulated, it will be a complicated process for pharmaceutical companies to formulate effective artificial intelligence strategies. In this process, pharmaceutical companies should consider four key issues:

  1. Cooperation with AI companies

Talents with both AI and biological knowledge are extremely limited, so it is more efficient to establish partnerships with leading AI companies than to build internal AI teams. Based on such a win-win partnership, pharmaceutical companies can obtain customized AI solutions for their internal data, while AI companies can further improve the accuracy of the algorithm through extensive data analysis.

  1. Data sharing

The fierce competition in the pharmaceutical industry has made it extremely rare for companies to share information, and increasingly stringent regulations and compliance standards have further exacerbated this phenomenon. Therefore, some AI projects have been criticized for lack of sufficient data. From this perspective, data sharing with other pharmaceutical companies can maximize the potential of AI.

  1. Transparency of the algorithm of the regulator

Regulators need to clearly understand the algorithms used in drug development to understand the logic behind AI-led decisions. If the algorithm is not transparent for supervision, AI will be a "black box" that cannot be rigorously and scientifically evaluated and verified. This may lead to unforeseen problems in the drug approval process. In order to avoid the above-mentioned problems, pharmaceutical companies should actively discuss with the regulators the regulatory approaches that both sides can accept and benefit from.

  1. Data privacy

Because the patient data is not involved in the drug discovery phase, AI is more widely used in the drug discovery phase than in the clinical phase. However, it should be noted that the use of patient data is very sensitive. With the development of AI technology, enterprises must take reasonable legal and compliance measures to protect increasing patient data. In Europe, General Data Protection Regulation (GDPR) will become particularly important. If not strictly followed, it will destroy the reputation of the company and cause huge financial losses.


The rapid development of AI has brought a more efficient, faster, and cheaper chemical drug development model to the pharmaceutical industry. However, opportunities and challenges coexist. Under the tide of AI, pharmaceutical companies need to break the tradition and seek new opportunities with unprecedented close cooperation. A survey of executives in the pharmaceutical industry shows that in the next five to ten years, AI will become a must for pharmaceutical companies.


About AI & Medicine

Missioned to helping fulfill the specific drug R&D requirements in the industry, AI & Medicine successfully develops an AI-powered drug discovery platform for medical institutions and pharmaceutical enterprises across the globe, offering a broad and integrated portfolio of medical and scientific solutions in areas like drug R&D, medical translation, medical imaging, medical therapy and research system, and more. It recently broadens its service offerings to chemical drug development, molecular docking, de novo drug design, retrosynthetic analysis, docking and scoring, SAR analysis, etc.