Artificial Intelligence In Drug Discovery Market Size, Share & Trends Analysis Report By Therapeutic Area (Oncology, Cardiovascular Disease, Metabolic Diseases), By Application, By Region, And Segment Forecasts, 2020 - 2027

Report Overview               

The global artificial intelligence in drug discovery market size was valued at USD 473.4 million in 2019 and is expected to grow at a compound annual growth rate (CAGR) of 28.8% from 2020 to 2027. The growing impetus for decreasing the cost of novel drug discovery and production in recent years is expected to bolster demand for artificial intelligence (AI) platforms in drug discovery space. According to industry journals, the average novel drug discovery and development cost are USD 2.6 billion. This is mainly due to the narrow development testing funnel which eliminates the majority of the candidate therapies within the preclinical and phase - 1 trial. Due to this, the adoption of artificial intelligence for a faster, efficient, and cost-effective drug discovery is gaining momentum amongst the pharmaceutical industry stakeholders.

Another key factor promoting the adoption of artificial intelligence in the drug discovery space is the monumental data generated by the molecule screening processes and the preclinical studies. The large data makes it a difficult process for the scientist to review all the scientific literature. In such cases, artificial intelligence can help boost up the screening process and reduce the time required for studying and identify drug molecule interactions and histology data.

Another key aspect of the rising adoption of AI in the drug discovery space is the availability of myriad options to carry out the standard processes such as data mining and customization capabilities of the artificial intelligence platforms. The advances in artificial intelligence such as machine learning and deep learning enable pharmaceutical companies to specifically recognize molecule binding properties of the drug with high accuracy.

Preclinical testing is one of the areas that account for high revenue loss and low returns. Optimizing preclinical testing can help reduce the cost. This is where artificial intelligence algorithm-based models can be used for accurate analysis of human physiology response as compared to animal models. AI-based models can help eliminate experimental costs and help in the efficient prediction of cross-species differences.

Therapeutic Area Insights

Based on the therapeutic area, the oncology segment accounted for the highest revenue share of 26.5% in the AI in drug discovery market. AI already plays a vital role in the early detection of cancer. Furthermore, as treatments for cancer may vary for each patient, personalized medicine has proven to be an effective alternative for treating cancer. Artificial intelligence platforms designed to identify genetic mutations help oncologists design effective personalized treatment for patients. For instance, Sophia Genetics, a Swiss company has developed an AI platform that helps in the detection of tumors by identifying gene variations and helps in designing personalized medicine for cancer treatment.

The infectious disease application segment is expected to expand at a CAGR of 31.4% in the market for AI in drug discovery over the forecast period. Even though AI-based drug discovery for infectious diseases has been a questionable area for researchers and scientists, due to the large quantities of sample data required by the AI platforms to begin identifying key patterns and points. The adoption of AI systems in infectious disease diagnostics and treatment design has started growing and is expected to witness robust growth in the coming years. For instance, on March 31, 2020, Existencia, an AI-based drug discovery company, entered into a partnership agreement with Diamond Light Source and Scripps Research for identifying Covid - 19 antiviral therapies. Similarly, Google’s DeepMind is working with its AI platform AlphaFold, is working towards providing information on several proteins associated with Sars - Cov - 2, they may help scientists in creating a treatment for Covid-19.

Application Insights

Based on application, the drug optimization and repurposing segment dominated the market for AI in drug discovery and accounted for the highest revenue share of 54.4% in 2019. AI platforms provide an effective way to identify the toxic effects of the drug on the body and thus reduce the chances of adverse effects. Furthermore, these platforms are also being used in identifying alternative applications for existing drugs. This can help pharma companies diversify their portfolio of offerings and assist in producing alternative therapies through minor alterations in the drugs.

Furthermore, the preclinical testing segment is expected to witness lucrative growth in the market over the forecast period. Due to their effectiveness in reducing overhead and experimental cost in preclinical testing, artificial intelligence-based platforms such as BenchSci’s machine learning platform are aimed to reduce errors and assist scientists in experiments. Similarly, another AI platform Euretos can enable scientists to design experiments in - silico, reducing large experimental costs.

Regional Insights

North America dominated the market and accounted for the highest revenue share of 59.4% in 2019. One of the key factors for the large market share is the adoption of AI systems in the U.S. which is further propelled by the presence of several companies in the country. According to the RELX survey findings, the adoption of AI has increased from 48.0% in 2018 to 72.0% in 2019. This is mainly due to the growing positive perception of AI amongst businesses.

Asia Pacific is expected to emerge as the fastest-growing region in the market. The growing adoption of new technology in India and China for new drug development and a focus towards boosting pharmaceutical capacities within the countries is expected to drive the market for AI platforms for drug discovery in the region. The market in this region is expected to witness a CAGR of 32.1% by the end of the forecast period.

Key Companies & Market Share Insights

Competition is intense among existing players attributing to the rising demand for reduced drug discovery costs. Furthermore, strategic expansions by companies in the form of mergers and acquisitions is expected to boost the competition and propel the growth of the market. As the companies have started expanding their artificial intelligence offerings in the drug discovery space the surge in adoption of AI is expected to witness continuous growth. Some of the prominent players in the artificial intelligence in drug discovery market include:

• IBM Watson

• Exscientia

• GNS Healthcare

• Alphabet (DeepMind)

• Benevolent AI

• BioSymetrics

• Euretos

• Berg Health

• Atomwise

• Insitro

• Cyclica

Artificial Intelligence In Drug Discovery Market Report Scope

Segments Covered in the Report

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2016 to 2027. For the purpose of this study, Grand View Research, Inc. has segmented the global artificial intelligence in drug discovery market report on the basis of application, therapeutic area, and region:

• Application Outlook (Revenue, USD Million, 2016 - 2027)

  • Drug optimization and repurposing

  • Preclinical testing

  • Others

• Therapeutic Area Outlook (Revenue, USD Million, 2016 - 2027)

  • Oncology

  • Neurodegenerative Diseases

  • Cardiovascular Disease

  • Metabolic Diseases

  • Infectious Disease

  • Others

• Regional Outlook (Revenue, USD Million, 2016 - 2027)

  • North America

    • The U.S.

    • Canada

  • Europe

    • The U.K.

    • Germany

    • France

    • Italy

    • Spain

    • Russia

  • Asia Pacific

    • Japan

    • China

    • India

    • South Korea

    • Australia

    • Singapore

  • Latin America

    • Brazil

    • Mexico

    • Argentina

  • MEA

    • South Africa

    • Saudi Arabia

    • UAE