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The global AI in precision medicine market is poised for a remarkable ascent. Forecasts indicate a substantial surge from its 2022 valuation of USD 1.74 billion, with projections estimating a staggering leap to approximately USD 16.91 billion by the year 2032. This exponential growth, encapsulated by a compelling CAGR of 25.54% spanning from 2023 to 2032, is intricately woven into the fabric of escalating cancer cases and an ever-growing demand for personalized healthcare solutions.

Artificial Intelligence (AI) in Precision Medicine Market Size 2023 - 2032

The imperative for Early Cancer Detection Drives Surge in Precision Medicine Market Fueled by AI advancement, with 609,820 Deaths in 2023 Reported By National Cancer Society, Spotlighting Urgent Need for advanced Solutions

The intersection of AI in precision medicine market holds the potential to transform healthcare significantly. Precision medicine techniques aim to identify specific patient phenotypes with uncommon responses to treatment or distinct healthcare requirements. AI plays a pivotal role by employing advanced computational processes and interference, allowing the system to derive valuable Insight, enhance reasoning capacity, and facilitate continuous learning.

This, in turn, empowers healthcare practitioners in their decision-making processes through augmented intelligence. Recent literature underscores the importance of translation research in exploring the convergence of AI in Precision medicine market, particularly those involving the interplay of non-genomic and genomic determinants. Integrating diverse data sources, including patient symptoms, clinical history and lifestyle, will streamline personalized diagnosis and prognostication.

Major Principles for Adoption AI in Precision Medicine Market

  • Data and Security: Ensure robust measures for data privacy and security in collecting, storing, and sharing patient information for precise medication adoption.
  • Analytics and Insight: leverage advanced analytics to extract meaningful insights from diverse health data, enabling personalized treatment plans and informed decision-making in precise medication approaches.
  • Shared Expertise: Foster collaboration among healthcare professionals, researchers and technology experts to pool expertise and create a collective understanding for successfully implementing precise medication strategies.

The incorporation of AI in precision medicine market contributes to a notable market increase. AI’s enhanced capability optimizes treatment approaches and paves the way for more targeted and personalized healthcare solutions, positively impacting the overall market dynamics.

Ai’s ability to recognize complex patterns has led to image-based detection and diagnostic systems performing better than clinicians. AI-enabled clinical decision support systems can reduce diagnostic errors, enhance decision-making intelligence, and assist in Electronic Health Record (EHR) data extraction.

Globally, the trend extends beyond the United States, with initiatives like the UK Biobank, BigBank Japan, and the Australian Genomics Health Alliance showcasing the global impact of changing attitudes towards precision medicine.

Advancement in Machine Learning Fosters Growth of AI in Precision Medicine Market

The invention of mathematical models that allow AI systems to analyse data, spot pattern and make prediction more accurately and efficiently is a key component of machine learning algorithm advancements. Developments in deep learning architectures, optimization methods, and algorithmic efficiency are frequently included in these improvements. AI is essential to precision medicine because it allows for the customization of medical interventions based on patient characteristics.

The following are some ways that AI advances the field of precision medicine:

Personalised treatment Plans To generate personalized treatment plans, artificial intelligence (AI) algorithms can examine enormous volumes of patient data, including genetic data, lifestyle variables, and medical history. This makes it possible for medical professionals to provide tailored treatments depending on the particulars of each patient.
Drug Discovery and Development AI makes the process of finding new drugs faster by identifying possible drug candidates more quickly through the analysis of biological data. This may result in the creation of specific drugs that are more matched to the unique characteristics of each patient.
Diagnostic Precision Through the interpretation of intricate medical imaging data and genetic information, machine learning algorithms can improve diagnostic accuracy. This accuracy facilitates earlier disease detection and more potent intervention techniques.
Clinical Decision Support AI helps with clinical decision-making, giving medical professionals insightful information. This entails forecasting the course of the disease, making recommendations for the best course of action, and spotting possible dangers or side effects.
Real-Time Monitoring AI-driven monitoring systems have the ability to continuously evaluate patient data in real time, sending out alerts in a timely manner for possible health problems. Preventive and customized healthcare are aided by this proactive approach.

In addition, Artificial Intelligence (AI) has the potential to transform the precision medicine industry due to its capacity to analyse a wide range of datasets and its constant refinement of machine learning algorithms. Consequently, this fosters the expansion of artificial intelligence applications that offer more efficient, customized, and focused healthcare solutions.

For Instance,

  • In march 2023, Google cloud launched Artificial intelligence (AI)-based life science solutions to speed up drug discovery and precision medicine for biotech, pharmaceutical, and other industry players. The purpose of the target and lead identification suits is to aid the research team in more precisely identifying the function of amino acids. It is anticipated that this approach will strengthen the company’s position in the market and improve the services it offers.

Increasing Prevalence of Cancer Leads to a Demand for AI in Precision Medicine Market

In 2023, the American Cancer National Center for Health Statistics collected mortality data and central cancer registries managed incidence data to compile the most recent data on population-based cancer occurrence and outcomes. Society keeps track of new cancer cases and deaths in the United States.

For Instance,

  • In 2023, According to the American Cancer Society, 1,958,310 new cancer cases and 609,820 cancer deaths are projected to occur in the United States. They are corresponding to 1670 deaths per day. Approximately 350 people die each day from lung cancer—nearly 2.5 times more than the number of people who die from Colorectal Cancer, which is the second leading cause of cancer death overall. Approximately 103,000 of the 127,070 lung cancer deaths (81%) in 2023 will be caused by cigarette smoking directly, with an additional 3560 caused by second-hand smoke. The remaining balance of approximately 20,500 nonsmoking-related lung cancer deaths would rank as the eighth leading cause of cancer death.
  • In 2020, According to the National Cancer Institute, there were an estimated 17.35 million new cases of cancer diagnosed in the United States, resulting in 609,640 deaths; globally, there were 18 million new cases, with 9.5 million deaths reported. By 2030, there will be 23.6 million new cases in the U.S.; by 2035, that number is predicted to have increased by 70%.

Estimated Deaths for Selected Cancer in U.S., 2023

The rapid growth of artificial intelligence(AI) in oncology is fueled by enhanced data capture, increased analytical power, and decreasing cost of genome sequencing. This program has significantly impacted biomedical discovery, diagnosis, prognosis, treatment, and prevention. However, challenges persist in developing inclusive and unbiased AI solutions that are generalised effectively across diverse populations. Concerns include inner biases and the potential for the algorithms to reflect the biases of their creator in the context of cancer care.

Adopting a transparent, thoughtful approach to address bias throughout the entire care is crucial. Integrating AI in Cancer research and precision medicine, leveraging projects like the Cancer Genome Atlas (TCGA), has become pivotal. TCGA, a comprehensive omics data source, provides valuable insights from over 11,000 cancer cases. The convergence of omic data, pathology reports, and medical imaging enables a thorough understanding of cancer’s genetic and epigenetic causes, facilitating targeted and preventive measures.

Collaboration and Innovation

In November 2022, Google Collaborate with iCAD they focused on developing innovation and increasing access to mammography technology through cloud-based solutions. The Breast AI Suite from iCAD, a suite of technologies for detecting breast cancer, evaluating density, and determining a person’s short-term risk, will soon include Google Health’s AI technology. The agreement intends to support the journeys of cancer patients by validating and integrating Google’s mammography tools into this portfolio.

iCAD plans to integrate Google’s mammography AI products into ProFound AI Risk, a clinical decision support platform intended to offer a precise, individualised estimate of the risk of developing breast cancer in the near future. iCAD stated that it intends to enhance the functionality of its algorithm to 2D and 3D mammography by utilizing Google’s solutions.

Additionally, the AI driven innovation in cancer detection has contributed to the growth of the AI in precise medicine market, marking a significant advancement in personalised healthcare.

The hurdle of Fairness and Bias in AI for Precision Medicine has Contributed Significantly to Decreased Market Adoption

The inherent biases present in health data, arising from issues such as limited diversity in sampling, missing values, and imputation methods, pose a substantial challenge. When AI models are trained on biased data, they can amplify existing biases, making unfavourable decisions for specific demographic groups based on factors like age, gender, race, geography, or economic status. This bias compromises the clinical applicability of AI models and raises concerns about the overall quality of healthcare outcomes.

Patients from underrepresented groups may experience disparities in diagnosis, treatment recommendations, or risk predictions, exacerbating existing inequalities in healthcare. As a result, potential users, including healthcare providers and institutions, may become hesitant to adopt AI solutions due to ethical concerns and the fear of perpetuating or exacerbating biases in patient care. This hesitancy leads to a decrease in AI in precision medicine market.

Additionally, addressing fairness and bias in AI models requires concerted efforts, including improving data diversity, implementing bias-mitigation techniques proposed by AI communities, and utilizing tools like IBM’s AI Fairness 360 toolkit. Despite these solutions, the nuanced nature of fairness and protected attributes in healthcare necessitates ongoing research and collaboration within the AI and biomedical communities.

Furthermore, weakening stakeholder confidence in these systems and the perceived ethical risks of biased AI models also make stakeholders less willing to invest in and use AI for precision medicine. As a result, it will be difficult for The market for AI in Healthcare to be widely adopted and used.

The Synergy of Technological Advancements and Innovation Propels AI’s Role in Precision Medicine Market Growth

AI in precision medicine market, particularly genome-informed prescribing, marks a groundbreaking innovation with significant market opportunities. The power of precision medicine at scale is exemplified in the developing of machine learning algorithms predicting patients’ medication needs based on genomic information. Real-time recommendations and personalized dosages rely on genotyping patients in advance. Deep learning techniques, such as those highlighted by Zou and colleagues, contribute to efficient genome interpretation, aiding in identifying genomic variations related to disease presentation, therapeutic success and prognosis.

In the case of medulloblastoma, AI-mediated analysis has unveiled discrete molecular subgroups, enabling customized treatments for pediatric patients. Precision genomics, steering away from conventional multimodal treatments, allows for targeted chemotherapy, reducing the necessity for radiation. This precision in treatment improves efficacy and minimizes potential neurocognitive sequelae and secondary cancers, presenting a substantial market opportunity.

The integration of AI into imaging recognition has given rise to radio genomics. This novel field links cancer imaging features with gene expression to predict the risk of toxicity after radiotherapy. AI is covering radiogenomic associations in breast, liver, and colorectal cancer. While limited data availability remains a challenge, the growing opportunities in the market for AI in radiogenomics are evident. These findings empower clinicians to select treatments with higher efficacy, presenting additional market opportunities in the evolving landscape of AI in precision medicine market.

Collaboration and Innovation

  • In December 2023, Absci and AstraZeneca collaborated on significant advancements in integrating biotechnology and AI-driven innovation by fusing AstraZeneca’s vast oncology knowledge with Absci’s cutting-edge AI technology. This partnership aims to open up new possibilities in the search for advanced cancer therapies.
  • In September 2023, ACC collaborated with Srv Medical, a Singapore-based AI healthcare company focusing on cardiovascular care through digital therapeutics and increasing medical experience in the developing market.
    Advanced genomic data, facilitated by next-generation sequencing and direct-to-consumer testing, enables personalized preventive care and disease management strategies.

Cardiovascular medicine’s embrace of predictive modelling, considering factors like gender, genetics, lifestyle, and environment, has led to promising developments. Artificial intelligence, particularly in predictive modelling and combining electronic health records (EHR) with genetic data, offers opportunities to enhance disease prediction and diagnosis. Innovations such as AI-enabled recognition of phenotype features and rapid whole-genome sequencing contribute to faster and more accurate diagnoses, especially in cases of suspected genetic diseases in seriously ill infants.
These innovations drive the global increase  AI in precision medicine market, providing a more nuanced and practical approach to healthcare by integrating diverse data sources and advanced technologies.

AI in Precision Medicine Market Growth Expanded by Components

In AI in precision medicine market, hardware advancements play a crucial role in AI by providing increased computational power for complex data analysis. Specialized hardware accelerators, such as Graphical Processing Units (GPUs) and Tensor Processing Units (TPUs), enable faster processing of vast datasets, facilitating more accurate diagnostics and personalized treatment recommendations.

  • Sophisticated algorithms and machine learning models are continually evolving on the software front. These advancements enhance the capability of AI systems to interpret diverse medical data, including genomics, imaging, and clinical records. Improved software solutions contribute to more precise predictions, aiding healthcare professionals in tailoring treatments based on individual patient characteristics.
  • Services in AI-driven precision medicine encompass a range of offerings, from consulting and implementation to ongoing support. The growth in specialized services fosters the integration of AI technologies into healthcare systems, making it more accessible for medical professionals. This, in turn, contributes to the broader adoption of AI in precision medicine market, leading to improved patient outcomes and more targeted therapeutic approaches.
  • The synergistic growth of advanced hardware, sophisticated software, and specialized services in AI has significantly propelled the precision medicine market. The seamless integration of powerful hardware facilitates faster and more accurate data analysis, while cutting-edge software enhances the interpretative capabilities of AI algorithms. Additionally, the availability of specialized services ensures effective implementation and ongoing support for healthcare professionals, fostering widespread adoption.

This fusion of components has fueled the expansion of AI in precise medicine market, resulting in improved diagnostic accuracy and personalized treatment approaches, ultimately contributing to the market’s overall growth.

Pioneering Progress: Unraveling the Forces Behind the Growth

1. AI’s Pivotal Role in Revolutionizing Precision Medicine

The convergence of AI in precision medicine market signifies a revolutionary paradigm shift in healthcare. AI’s prowess in deciphering complex medical data and discerning nuanced patterns empowers healthcare providers with unprecedented insights. This transformative capability not only expedites diagnostics but also enhances treatment efficacy, fostering a new era of precision and personalized care.

2. Addressing the Cancer Conundrum: AI’s Impact on Oncological Care

The escalating prevalence of cancer emerges as a chief catalyst propelling the AI in precision medicine market forward. AI algorithms, armed with advanced learning capabilities, exhibit an unparalleled ability to analyze vast datasets related to cancer genetics, facilitating early detection and tailored therapeutic approaches. This proactive stance against cancer resonates with the global healthcare landscape, driving the demand for AI in precision medicine market solutions.

3. Rising Demand for Personalized Care: A Paradigm Shift in Patient Expectations

In an era where one-size-fits-all solutions are giving way to personalized experiences, the healthcare sector is no exception. Patients are increasingly seeking tailored interventions that align with their unique genetic makeup and lifestyle. The surge in demand for personalized care dovetails seamlessly with the capabilities of AI in precision medicine market, positioning it as a linchpin in meeting the evolving expectations of the modern healthcare consumer.

The Road Ahead: Navigating Challenges and Opportunities

While the trajectory of the AI in precision medicine market is undeniably upward, it is not devoid of challenges. Ethical considerations, data security, and regulatory frameworks necessitate meticulous navigation. However, as innovation continues to surmount hurdles, the opportunities presented by AI in precision medicine market promise to redefine the healthcare landscape, ushering in an era of unparalleled advancements and patient-centric care.

Charting the Course for a Transformed Healthcare Landscape

The astronomical growth forecasted for the global AI in precision medicine market between 2023 and 2032 is emblematic of a healthcare revolution in the making. The symbiotic relationship between AI in precision medicine market holds the promise of not only addressing the challenges posed by conditions like cancer but also steering healthcare towards an era of personalized, efficient, and data-driven interventions. As we embark on this transformative journey, the marriage of artificial intelligence and precision medicine emerges as a beacon illuminating the path to a future where healthcare is not just curative but profoundly individualized.

Geographical Landscape

North America dominated the AI in precision medicine market. This region boasts a robust ecosystem of research institutes and healthcare providers collaborating to leverage AI for more accurate Diagnostics, personalized treatment strategies, and improved patient outcomes. Johnson and Johnson, Google, IBM Watson, and NVIDIA.

  • In July 2022, Certara, Inc. collaborated with Memorial Slon Kettering Cancer Center to build new biosimulation software. They developed a Bisimulation platform for CAR T cell treatment. The main driver of market expansion in the United States is the growing demand for individualized care.

Europe is anticipated to have the fastest growth in AI in precision medicine market. Improving early infection diagnosis is becoming increasingly important as the number of older adults rises, and chronic diseases become more common. Many businesses are implementing strategies to give them a competitive edge over rivals. For example, Nuclear and Merck KGaA Darmstadt declared their collaboration to leverage image analysis to find a biomarker platform.

In Asia-Pacific, the multi-country GenomeAsia100K initiative aims to “sequence and analyze the genomes of 100,000 Asian individuals to help accelerate Asian Population-specific medical advances and precision medicine.” All discoveries and outcomes will be disseminated to the larger scientific community to distribute the accountability for advancing the sector through R&D among other like-minded establishments and associations.

Competitive Landscape

AI in precise medicine market improves diagnosis by analyzing vast datasets, customizing treatment plans based on individual patient characteristics, and speeding up drug discovery through data-driven insight. Leading Companies like IBM, Microsoft, Google, and NVIDIA actively engaged in innovation, contributing to the expansion of AI in precise medicine market. Notably, AI examined data from thousands of patients in cancer research in partnership with the Cancer Genome Atlas. Genetic anomalies—such as mutation or overexpressed proteins—were discovered through this collaboration, providing novel therapeutic targets for precision medications. These discoveries make creating highly specialized medicines catered to specific patients possible.

Recent Developments

  • In November 2022, MedStar Health partnered with Zephry AI, Inc., and They developed Artificial intelligence – enabled precision medicine tools to improve chronic conditions and outcomes.
  • In September 2021, SOPHiA GENETICS collaborated with Hitachi Ltd. The collaboration aims to advance data-driven precision medicine for patients worldwide by connecting pharmaceutical companies, healthcare providers, and real-world, demonic, and clinical insight.

Market Players

  • IBM
  • Microsoft
  • Google
  • NVIDIA
  • Illumina
  • Roche
  • Johnson & Johnson
  • GE Healthcare
  • Intel Corporation
  • AstraZeneca
  • Sanofi
  • Tempus

Market Segments

By Technology

  • Machine Learning
  • Querying Method
  • Deep Learning
  • Context-Aware Processing
  • Natural Language Processing

By Component

  • Hardware
  • Software
  • Service

By Therapeutic Application

  • Oncology
  • Neurology
  • Cardiology
  • Respiratory
  • Others

By Geography

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • The Middle East and Africa

READ MORE RELATED REPORT: Precision Oncology Market

By Sanskruti

Sanskruti Sathe is a passionate healthcare professional author dedicated to improve advancing healthcare knowledge. With over a decade of experience in the field, Sanskruti has worked in various healthcare research institutions. She holds a Master's degree in Public Health and has authored several articles and books on topics ranging from chronic disease management to healthcare policy. As an advocate for evidence-based practice, Sanskruti continues to contribute to the healthcare community through her writing and consulting work.