Ottawa, Jan. 10, 2024 (GLOBE NEWSWIRE) -- The global Artificial Intelligence (AI) in precision medicine market size is anticipated to reach around USD 8,550 million by 2029, increasing from USD 2,740 million in 2024, a study published by Towards Healthcare a sister firm of Precedence Research.
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 artificial intelligence (AI) and precision medicine 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, 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.
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Major Principles for Adoption AI in Precision Medication
The incorporation of AI in precise medicine 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 has seen significant growth and acceptance in various domains in the past ten decades, notably within healthcare. AI offers opportunities for intelligent product design, novel services and new business models, yet it also poses social and ethical security, privacy, and human rights challenges. In precise medication, AI technologies range from virtual applications like deep-learning-based health information management systems to cyber-physical implementation, such as robotic assistants in surgeries and targeted nanorobots for drug delivery. 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.
Precision medicine, notably genotype-guided treatment, has revolutionized healthcare by using genetic information to determine optimal drug dosages, such as warfarin. The Clinical Pharmacogenetics Implementation Consortium provides guidelines for clinicians, enhancing drug therapy through genetic test results. Genomic profiling of tumours aids in tailoring targeted therapies for breast and lung cancer patients. Integrated into healthcare, precision medicine offers precise diagnoses, predicts disease risk preemptively, and designs personalized treatment plans for optimal safety and efficiency. 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.
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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:
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,
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Increasing Prevalence of Cancer Leads to a Demand for AI in Precision Medication
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,
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.
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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 the market for AI in precision medicine.
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 AIs Role in Precision Medicine Market Growth
Artificial intelligence (AI) in precision medicine, 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-driven precision medicine.
Collaboration and Innovation
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 in the AI market for precise medicine, providing a more nuanced and practical approach to healthcare by integrating diverse data sources and advanced technologies.
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Artificial Intelligence in Precision Medicine Market Growth Expanded by Components
In precision medicine, 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.
This fusion of components has fueled the expansion of AI in precise medicine, resulting in improved diagnostic accuracy and personalized treatment approaches, ultimately contributing to the market's overall growth.
Geographical Landscape
North America dominated the AI in the 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.
Europe is anticipated to have the fastest growth in AI in the 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 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 the precise medicine market. Notably, AI examined data from thousands of patients in cancer research in partnership with the Cancer Genome Atlas. Genetic anomaliessuch as mutation or overexpressed proteinswere 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
Market Players
Market Segments
By Technology
By Component
By Therapeutic Application
By Geography
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Towards Healthcare is a leading global provider of technological solutions, clinical research services, and advanced analytics to the healthcare sector, committed to forming creative connections that result in actionable insights and creative innovations. We are a global strategy consulting firm that assists business leaders in gaining a competitive edge and accelerating growth. We are a provider of technological solutions, clinical research services, and advanced analytics to the healthcare sector, committed to forming creative connections that result in actionable insights and creative innovations.
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