The AI in Drug Discovery Market is expected to reach USD 8.10 billion by 2030, growing at a CAGR of 25% during the forecast period 2023-2030. The AI in Drug Discovery Market is rising at a global level with growing investment in healthcare infrastructure. Another aspect leading to the lucrative growth of the industry is the growing awareness related to the benefits offered by artificial intelligence in solving complex situations. The preclinical testing portion of drug discovery has maximum chances of revenue loss, using AI-based models in testing can eradicate high experimental costs and help in the efficient prediction which results in a sharp rise in the market which is expected to grow substantially during the forecast period also.

Artificial Intelligence (AI) is a technological system designed with a set of domains including knowledge representation, reasoning, solution search, and machine learning to mimic human intelligence. AI has the potential to interpret and learn from the input data to make independent decisions by using the system, software, tools, and network. The increasing applications of AI in various sectors particularly the pharmaceutical industry have greatly expanded the market in recent times. In this technical era, AI is used in drug discovery, drug repurposing, productivity improvement, and workload reduction in the pharmaceutical sector. 

According to the McKinsey Global Institute, the work culture of society will get transformed under the influence of AI-guided automation.

Artificial Intelligence (AI) for drug discovery can be used at various steps from drug designing to drug screening. The market is witnessing quick growth with the increasing requirements to reduce the overall cost and duration of drug development. There are ginormous piles of molecular data and literature in the drug discovery space, AI makes it possible to screen the required data in minimum time. This leads to increasing adoption and expansion of the AI industry. On average, it takes nearly ten years to develop a drug successfully with an expenditure of US$ 2.6 billion. This long duration is due to the fact that a plethora of candidate drugs are removed within the preclinical and phase 1 clinical trial. Due to this, the majority of pharmaceutical industry stakeholders are interested in adopting artificial intelligence for a rapid, efficient, and cost-effective drug discovery.

Segmentation of Artificial Intelligence in Drug Discovery Market

The global AI in drug discovery market can be segmented based on the following segments:

By Offering 

• Software
• Service

By Technology

• Machine Learning
  • Deep Learning
  • Supervised Learning
  • Reinforcement Learning
  • Unsupervised Learning
  • Other Machine Learning Technologies
• Others Technologies

By Application 

• Drug optimization and repurposing
• Preclinical testing
• Others

By Therapeutic Area

• Cardiovascular Disease
• Infectious Disease
• Metabolic Diseases
• Neurodegenerative Diseases
• Oncology
• Others

By End-User

• Contract Research Organizations
• Pharmaceutical & Biotechnology Companies
• Research Centres and Academic & Government Institutes

The above-mentioned drivers along with rising cross-industry collaborations and partnerships between the market vendors result in manifold profits in the market. However, the lack of required data sets and the unavailability of a skilled workforce are some of the major challenges faced in the adoption of AI in drug development field.

Artificial Intelligence (AI) tools are available as software and services, among these software holds a comparatively larger portion of the market share as there is plenty of software available and there is an increasing demand for AI software from major tech-savvy biotech and pharma industries. By application, drug repurposing and optimization dominated the market. This dominance can be attributed to the capability of AI to identify the toxic effects of the drug on the body which can reduce the negative side effects of drugs being developed. It also aids pharma companies in achieving a diversified product portfolio by identifying slight alterations in existing drugs. 

Artificial Intelligence (AI) made it the to design the drugs for complex conditions due to which the neurological disorder segment has the maximum market share among all the therapeutic areas covered. Based on end-user, the pharmaceutical and biotechnology companies segment occupied more than 50 percent share of the artificial intelligence for drug discovery and development market in 2019.

North America is an early adopter of Artificial Intelligence (AI) which makes it the leading contributor in the market. This is attributed to the well-recognized pharmaceutical industry and high investment in the research and development sector in the region. Moreover, the headquarters of prominent AI technology providers like Google, Microsoft, IBM, and many others are all located in the US.

Competitive Landscape

The process of discovering and developing a drug can take over a decade and then also, there is the possibility that nine out of ten therapeutic molecules fail to cross the investigational study period. Therefore, it is important to develop a potential product for commercialization to minimize uncertainty and maximize growth. This can be achieved by adopting AI in drug discovery and development. Several key players are involved in the market are IBM Corporation, Microsoft Corporation, Google, NVIDIA Corporation, Cloud Pharmaceuticals, Inc., Indivumed GmbH, Deep Genomics, Atomwise, Inc., Insilico Medicine, Exscientia, Bioage, and Envisagenics, among others.

• IBM, one of the leaders in AI in the drug discovery market. the company's Watson is widely used for cognitive computing and data-driven applications by numerous pharma and biotech companies. IBM recently invested approximately US$ 6 billion in order to achieve 15 acquisitions in cognitive, cloud, and security businesses.
• Indivumed launched an artificial intelligence platform to support multi-omics data for discoveries in the therapeutic area of oncology. The company developed pioneering technology to automate and integrate analytics to solve queries across cancer bioinformatics.
• Existencia entered into a partnership agreement with Diamond Light Source and Scripps Research in March 2020 to aid in the identification of Covid - 19 antiviral therapies.
• Google’s DeepMind is working for the betterment of its AI platform AlphaFold with the aim of helping scientists to develop the best treatment for Covid-19. The platform provides information on several proteins associated with SARS - COV – 2.