NATURAL LANGUAGE PROCESSING (NLP) IN HEALTHCARE AND LIFE SCIENCES MARKET ANALYSIS

The global natural language processing (NLP) in healthcare and life sciences market is estimated to be valued at US$ 4.98 Billion in 2023 and is expected to exhibit a CAGR of 30.5% during the forecast period (2023-2030).

Analysts’ Views on Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market:

Increasing adoption of technology by market players, growing inorganic growth strategies such as signing partnerships, by market players, and increasing product launches are expected to drive the growth of the global natural language processing (NLP) in healthcare and life sciences market. For instance, on May 22, 2023, Intelligent Medical Objects (IMO), a leading provider of clinical terminology management and data quality solutions for healthcare, announced that it has acquired Melax Technologies, Inc., a healthcare data analytics and business intelligence company. Melax Tech empowers the healthcare and life sciences industries through the use of artificial intelligence (AI) and natural language processing (NLP) technologies to extract information from biomedical textual data to solve real-world problems. 

Figure 1. Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market Share (%), By Component Type, 2023

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Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market– Drivers

• Emerging data operations and increasing usage of smart devices: The healthcare and life sciences industries generate a large amount of data, which is driven by compliance and regulatory requirements, record keeping, and patient care. The growing trend of digitization and data-driven solutions to improve healthcare delivery systems is driving the growth of this market.Therefore, increasing data-driven operations and improved decision-making abilities in physicians due to NLP are major factors driving growth of the market. For instance, in May 2018, Google AI collaborated with the University of California, San Francisco, Stanford Medicine, and the University of Chicago Medicine to integrate machine learning into electronic health records (EHR) in order to achieve scalable and accurate results and develop a data processing pipeline for transforming Electronic Health Records (EHRs) files into a standardized format.

Increasing awareness about connected health and organizations are focused on big data analytics.

Increasing customer awareness about connected health has had a great impact on the adoption of smart devices. The increasing adoption of smart devices is a key factor driving growth of the global natural language processing (NLP) in healthcare and life sciences market. As technology-enabled medical care involves health, digital health, and e-health services.

Major organizations are focused on implementing big data analytics, which provides insight from large data sets and also reduces costs. The data from medical research and the disease population are used to predict and prevent various diseases. For instance, in 2018, eClinicalWorks, a technology-driven company, announced the launch of new cloud-based services for acute care EHR settings and revenue cycle management in the healthcare industry. The platform is designed to create a structured or unified electronic health record with a wide range of capabilities, such as claiming partner of record (CPOR) data, infection control, and referrals management.

Figure 2. Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market Share (%), By Region, 2023

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Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market- Regional Analysis

Among regions, North America is estimated to hold a dominant position in the global natural language processing (NLP) in healthcare and life sciences market over the forecast period. North America is estimated to hold 33.5% of the market share in 2023. The global natural language processing (NLP) in healthcare and life sciences market is expected to witness significant growth in the near future, driven by inorganic growth strategies by market players in the region. For instance, on April 10, 2023, Cerner Enviza, an Oracle company, along with John Snow Labs, are helping support the U.S. Food and Drug Administration’s drug safety Sentinel Initiative. By developing artificial intelligence (AI) tools aimed at extracting critical information from clinical notes within electronic health records (EHR), Oracle and John Snow will aid the FDA in better understanding the effects of medicines on large populations.

Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market– Impact of Coronavirus (COVID-19) Pandemic

Governments and government agencies globally are taking various initiatives to combat the spread of COVID-19. For instance, in May 2020, the Centers for Disease Control and Prevention started working with the All-of-Government and All-of-America approach to increase testing capacity, improve case detection, and contact tracing across all the U.S. states and reopen the country. Moreover, various key players in the market are focusing on strategic partnerships with the governments of countries to provide the valuable information on the ongoing COVID-19 pandemic. For instance, in 2020, Accenture, a technology solution provider company, and Microsoft, a technological company, announced a partnership with India’s Digital India Corporation (MyGov), sponsored by the Government of India. The companies have developed “MyGov Saathi”, with the help of the Microsoft Azure natural language platform, which can handle upto 300,000 users per day and 20,000 concurrent users per minute. The company’s MyGov Saathi software has novel updated which provides information on all most recent data on COVID-19 such as patients suffering from the COVID-19, treatments used for COVID-19 and etc.

Various leading pharmaceutical and technological companies were collaborating with the U.S. government for the faster clinical development of the vaccines for the prevention of COVID-19 infections in the U.S. For instance, in July 2020, IQVIA, the clinical service company, and Astra Zeneca, the pharmaceutical company, announced the collaboration with the U.S. government for Operation Warp Speed project. The project was focused on boosting clinical studies of the vaccine in the U.S. and includes an expansive subject study, which is expected to begin enrolling participants and will leverage IQVIA’s virtual trial solutions including Study Hub.

Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market Segmentation:

The global natural language processing (NLP) in healthcare and life sciences market is segmented by component type, by application, by deployment mode, and by region.

• By component type, the market is segmented technology (interactive voice response, optical character recognition, pattern and image recognition, auto coding, text analytics, speech analytics), and services. Out of which, the technology is expected to hold a dominant position in the global natural language processing (NLP) in healthcare and life sciences market during the forecast period, and is attributed to technological advancement.
• By application, the market is segmented into drug discovery, EHRs, clinical trial analytics, adverse event reporting, and others. Out of which, EHRs is expected to dominate the market over the forecast period, and this is attributed to increasing product launches. For instance, on July 26, 2023, Amazon Web Services, Inc., an Amazon.com company, announced AWS HealthScribe, a new HIPAA-eligible service that empowers healthcare software providers to build clinical applications that uses speech recognition and generative Artificial Intelligence, to save clinicians time by generating clinical documentation. With AWS HealthScribe, healthcare software providers can use a single API to automatically create robust transcripts, extract key details (e.g., medical terms and medications), and create summaries from doctor-patient discussions that can then be entered into an electronic health record (EHR) system.
• By deployment mode, the market is segmented into on-premise and cloud. Out of which,  on-premise is expected to dominate the market over the forecast period, and this is attributed to increasing campaigns to boost on-premises deployment in NLP healthcare and life sciences market. For instance, in September 2020, Lexalytics, a machine learning and artificial intelligence company, announced the 'Get Out of the Cloud' campaign, encouraging existing and prospective customers to seamlessly transfer their existing public-cloud Semantria implementation to its Salience on-premise offering.

Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market- Cross Sectional Analysis:

Europe accounted for the second-largest market share in 2022, owing to the rising adoption of artificial intelligence tools by healthcare providers in the region. For instance, according to Healthcare Information and Management Systems Society (HIMSS) Europe, a report of May 2018, around 16% of the healthcare facilities in Europe are currently using AI tools, and it is expected to reach 21% by 2023. Moreover, as per HIMSS Europe, in countries such as Switzerland and Spain, around 37-42% healthcare professionals claim to have obtained purchase plans for AI solutions by the end of 2021.

Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market: Key Developments

In December 2022, KAID Health, an AI-powered health care data analysis and provider engagement platform, partnered with OPN Healthcare, a U.S. network of community oncology providers, to improve oncology care delivery. The company will implement KAID Health’s Whole Chart Analysis, which draws healthcare data from multiple sources, and NLITE (Natural Language Insight and Term Extraction) solutions to enhance OPN’s technology platform. The Note Analyzer feature of KAID Health’s platform automatically extracts the clinical data required by pharmacists, nurses, and other caregivers to make an accurate determination of guideline compliance.

In July 2022, FRONTEO Inc., an Information Technology service management company, and Nippon Telegraph and Telephone East Corporation, a Japanese telecommunications holding company, signed a memorandum of understanding on the development of digital health using language and started collaboration.

In June 2021, Belgian-American e-health company and Afrisda, Inc., African Sustainable Development Advisors, announced a partnership agreement to support digital health implementation in Africa. The companies will focus on the implementation of digital health technologies such as machine learning and natural language processing in healthcare facilities in Africa.

In February 2019, YITU Healthcare, a China-based artificial intelligence (AI) startup, claimed to have a system that uses natural language processing (NLP) to achieve an accuracy of up to 97% when diagnosing pediatric diseases.

In 2019, Synyi, a technology-driven start-up company, announced that the company had raised US$ 36.6 Mn from Series C funding led by Chinese tech giant Tencent, a technology company in China. Synyi stated that the raised funds would be utilized by the company for developing smart healthcare technologies such as natural language processing in healthcare facilities and artificial intelligence technologies in China.

Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market: Key Trends

• Increasing adoption of inorganic strategies to strengthen product offerings: NLP is used in finding suitable clinical trial participants. Amazon offers a software named Amazon Comprehend Medical that helps healthcare companies to obtain business insights and medical records accurately and search suitable patients for clinical trials. This software uses NLP to examine through written documents to find the needed information. Similarly, Nuance Communications offers Dragon Medical One, which uses NLP to help doctors and healthcare providers to translate speech into medical document such as Electronic Healthcare Records (EHR)      

Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market: Restraint

• High training cost for NLP models: The high training cost for natural language processing models is unaffordable for start-up companies, which is expected to restraint the use of natural language processing models in start-up companies mainly present in lower and middle-income countries. For instance, Synced, a company focusing on reviewing the novel technologies, in April 2020, stated that the Stanford University professor of computer science (emeritus) conducted a survey on the cost for training NLP models. The survey was conducted on Google’s BERT language models, which stated that the approximate cost for training the companies on BERT models is approximately US$ 2.5k–US$ 50k (110 million parameter model). The BERT model is developed by Google and is used by all industries such as automobiles, pharma, and others, for data mining and other purposes.Counterbalance: In order to counterbalance the high costs associated with the NLP models, various methods are available to optimize the training model, which needs to be followed by the companies, so that it will help them in affording  the models.

Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market - Key Players

Major players operating in the global natural language processing (NLP) in healthcare and life sciences market include 3M, Cerner Corporation, IBM Corporation, Microsoft Corporation, Health Fidelity, Inc., IQVIA Holdings Inc., Dolbey Systems, Inc., Centene Corporation, Alphabet Inc., Nexocode, Averbis GmbH, Clinithink, Wave Health Technologies, Inovalon, Lexalytics, Conversica Inc., SparkCognition, and Hewlett Packard Enterprise Development LP.

*Definition: Natural Language Processing (NLP) is a branch of machine learning (ML) that primarily aims to reduce the distance between human and machine capabilities. NLP has been used in several areas within artificial intelligence (AI) and data processing application such as social media, translation, summarization, and medical applications. The analysis of medical data such as patient reports, doctor notes, patient demography details, lab test results, and previous medical history can be effectively examined through NLP.