According to Nova one advisor, the global Artificial Intelligence (AI) in Life Sciences market size is expected to hit around USD 6.20 billion by 2030 from valued at USD 1.9 billion in 2021 and growing at a CAGR of 20.4% from 2022 to 2030.
According to Nova one advisor, the global Artificial Intelligence (AI) in Life Sciences market size is expected to hit around USD 6.20 billion by 2030 from valued at USD 1.9 billion in 2021 and growing at a CAGR of 20.4% from 2022 to 2030.
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The COVID-19 outbreak has made profound and lasting impacts on the health and life sciences industry. The outbreak has caused life sciences organizations to adjust to supply chain and clinical development disruptions and financial challenges that would have previously been unthinkable. In the near term, healthcare organizations would accelerate innovation to respond to the crisis. These investments would enable healthcare organizations post-COVID-19 to rethink care delivery and financing, thereby stimulating the growth in the adoption of AI for the life sciences industry.
- Further, the industry is witnessing a transformation, owing to increasing cost pressure, a greater need for productivity, and disruption caused by new and innovative market players. An emerging area of artificial intelligence (AI), specifically the analysis of small systems-of-interest specific datasets, can be utilized to improve drug development and personalized medicine.
- According to a study published in Science Translational Medicine, Quadratic Phenotypic Optimization Platform (QPOP), an AI platform is capable of substantially improving combination therapy in bortezomib-resistant multiple myeloma, which is used to identify the best drug combinations for individual multiple myeloma patients.
- Furthermore, complex diseases, such as cancer, often require effective drug combinations to make any significant therapeutic impact. As the drugs in these combination therapies become increasingly specific to molecular targets, designing effective drug combinations, as well as choosing the right drug combination for the right patient, becomes more difficult. With the high average development costs (around USD 2 billion for a new approved treatment), low clinical trial drug success rate (below 12%), low return-on-investment (ROI) due to reduced healthcare expenditure, and focus on rare diseases, drug discovery is becoming more inefficient.
- Clinical trial research is an extensive progress, which can be reduced with the help of AI in numerous ways. One is by using advanced predictive analytics on a broad range of data to identify candidates for clinical trials for target populations more quickly. Additionally, machine learning applications can make clinical trials more efficient by facilitating tasks, such as calculating ideal sample sizes, facilitating patient recruitment, and using medical records to minimize data errors.
- Artificial Intelligence (AI) presents one of the most promising and potentially transformative opportunities for the life sciences industry. AI will be a key investment target in the coming years, with myriad organizations hoping to capitalize on its potential. The number of applications is expected to continue to increase and the investors are expected to enter the AI industry early.
Report Scope of the Artificial Intelligence (AI) in Life Sciences Market
| Report Coverage | Details |
| Market Size | USD 6.20 Billion by 2030 |
| Growth Rate | CAGR of 20.4% from 2022 to 2030 |
| Largest Market | North America |
| Fastest Growing Market | Asia Pacific |
| Base Year | 2021 |
| Forecast Period | 2022 to 2030 |
| Segments Covered | Offering, Deployment, Application and Region, |
| Companies Mentioned | IBM Corporation, Atomwise, Inc., Nuance Communications, Inc., NuMedii, Inc., AiCure LLC., APIXIO, Inc., Insilico Medicine, Inc., Enlitic, Inc., Sensely, Inc., Zebra Medical Vision |
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Key Market Trends
Clinical Trials is Expected to Hold a Significant Market Share
- Clinical trials are one of the most data-intensive tasks in the life sciences industry. They generate vast sets of data everyday monitoring, several variables of a patient under observation. Subjecting these data sets to intelligent AI algorithms can help the researchers to screen meaningful correlation even between loosely coupled data.
- This is encouraging many pharmaceutical companies and clinical research organizations to invest in technologies, like artificial intelligence. In the current market scenario, the rapid adoption of AI is widely seen in the pharmaceutical sector, who are responsible for almost 50% of the clinical trials conducted globally every year.
- Furthermore, the increasing number of clinical trials all over the world is producing colossal amounts of data that is available in the public domain. Over the forecast period, these numbers are expected to increase by at least 11%, creating new opportunities for AI in clinical trial applications, especially in Europe and North America.
- Such rapid growth in clinical trials and public availability of data is helping and encouraging many research institutes to prefer AI over traditional software solutions so that they can obtain specific results from data available in the public domain without having the entire trial procedure. Additionally, many countries, like China, the United States, and several European countries, are making clinical trial data available in the public domain supporting the growth of AI solutions, globally.
The United States is Expected to Hold a Major Share in the Market
- The United States is the largest market for AI solutions in the life sciences market, owing to the high demand for AI solutions from almost all the life sciences applications in the United States. In addition, the significant presence of pharmaceutical companies and the global demand for US pharmaceutical exports are increasingly motivating companies to invest in R&D activities.
- According to the Pharmaceutical Research and Manufacturers of America (PhRMA), the Pharmaceutical Manufacturers Association, the pharmaceutical companies in the United States spent approximately USD 80 billion worldwide on R&D in 2018, and expenditure in the companies’ domestic market of the United States contributed an overwhelming share.
- PhRMA also revealed that, on average, most pharmaceutical companies in the country spent over 19% of their total revenues in R&D activities. Moreover, PhRMA members spent around 19.5% of their combined global revenues on R&D in 2018. This share increased to approximately 22% when only considering the sales and R&D expenditure from the domestic market of the United States.
- Many pharmaceuticals companies, such as Pfizer and Johnson & Johnson, and several clinical research organizations in the country, are increasingly spending on AI solutions, and according to ClinicalTrials.gov, it is projected that by 2024 Johnson & Johnson will have the largest research and development spending among pharmaceutical companies. Also, companies, like Pfizer, despite collaborating with several AI vendors, are investing in updating their in-house AI operations to support their ongoing several drug discovery and patient monitoring processes.
Some of the prominent players in the Artificial Intelligence (AI) in Life Sciences Market include:
- IBM Corporation
- Atomwise, Inc.
- Nuance Communications, Inc.
- NuMedii, Inc.
- AiCure LLC.
- APIXIO, Inc.
- Insilico Medicine, Inc.
- Enlitic, Inc.
- Sensely, Inc.
- Zebra Medical Vision
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 2017 to 2030. For this study, Nova one advisor, Inc. has segmented the global Artificial Intelligence (AI) in Life Sciences market
By Offering
- Software
- Hardware
- Services
By Deployment
- On Premise
- Cloud
By Application
- Medical Diagnosis
- Drug Discovery
- Precision and Personalized Medicine
- Biotechnology
- Clinical Trials
- Patient Monitoring
By Region
- North America
- Europe
- Asia Pacific
- Latin America
- Middle East & Africa
Key Benefits for Stakeholders
- This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the global Artificial Intelligence (AI) In Life Sciences industry analysis from 2022 to 2030 to identify the prevailing Artificial Intelligence (AI) In Life Sciences industry opportunity.
- The market research is offered along with information related to key drivers, restraints, and opportunities.
- Porter’s five forces analysis highlights the potency of buyers and suppliers to enable stakeholders make profit-oriented business decisions and strengthen their supplier-buyer network.
- In-depth analysis of the global Artificial Intelligence (AI) In Life Sciences industry segmentation assists to determine the prevailing market opportunities.
- Major countries in each region are mapped according to their revenue contribution to the global market.
- Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.
- The report includes the analysis of the regional as well as global Artificial Intelligence (AI) In Life Sciences industry trends, key players, market segments, application areas, and market growth strategies.
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