(EMAILWIRE.COM, December 07, 2024 ) The AI in Clinical Trials Market is projected to reach USD 2.74 billion by 2030 from USD 1.35 billion in 2024, at a CAGR of 12.4% from 2024 to 2030. The AI in clinical trials market is experiencing significant growth driven by increasing demand for patient-centred and patient-driven situated trials, where AI improves remote monitoring of patients along with improving retention and recruitment of patients. The increasing trend in personalized treatment is also a contributing factor to the growth of artificial intelligence in healthcare, as it facilitates the scrutinization of DNA information for treatment orientation. Moreover, the need for AI in the management of research-related data, and study data for the design of processes and making decisions with high precision has a positive impact on growth. Further, the growing elaborate nature of clinical data and its processing for trial purposes is dependent on AI advanced analytics to handle massive volumes of data and provide insights for trial progress.
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Global AI in Clinical Trials Market Dynamics
DRIVER: Increasing Demand for Clinical Trials
Clinical studies are the backbone of drug development and help pharmaceutical and biotechnology companies launch new products. Over the past decade, demand for clinical studies globally has followed a sharp rise; according to current medical needs, the need to come up with new therapeutics has also surged. According to ClinicalTrials.gov, as of August 2023, nearly 461,614 clinical studies were recorded worldwide, showing a great increase from 5,475 in the year 2000.
RESTRAINT: Shortage Of Skilled Professionals for Clinical Trials
CROS faces difficulties in attracting and retaining highly skilled professionals since they offer the same services as the pharmaceutical and biotechnology companies and academic & research institutions to qualified and experienced scientists. These aspects will force the firms to provide more compensations and other fringe benefits which tend to influence finances and results, mainly for small-scale analytical testing providers. This shortage of skilled professionals may hinder the adoption of new technologies and methodologies and restrain the growth of the clinical trials market in the years to come.
OPPORTUNITY: Rising Demand for Specialized Testing Services
Traditionally, pharmaceutical, biotechnology, and medical device businesses kept early-phase development projects and problem-solving activities in-house, outsourcing primarily late-phase drug development and routine processes. However, in recent years, an increasing number of companies have partnered earlier in the drug development process to improve efficiency.
CHALLENGES: Concerns Regarding Patient Privacy
Data integration highlights the growing issue of patient privacy; with an increasing number of databases among research institutions, CROS, partners, and software businesses, the dangers of data breaches increase. According to the 2009 Health Information Technology for Economic and Clinical Health Act (HITECH Act), covered entities are required to secure individual health records and other identifiable health information by acquiring sufficient privacy safeguards. As a result, applying electronics tools to patient databases raises worries about the privacy of patient records, posing another significant barrier for pharmaceutical companies in complying with privacy policies while employing AI in clinical trials software.
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North America accounted for the largest share of the AI in clinical trials market in 2023.
North America held the most significant market share in the AI in clinical trials market in 2023. This region has a developed infrastructure concerning healthcare, the region has significant investments in R&D compared to their Asian counterparts, and it is home to leading pharmaceutical and biotechnology companies. Moreover, in North America, the regulatory environment and agencies like FDA support the integration of AI in clinical trials for better clinical trial processes. Well, highly adopted digital technologies and robust availability of data have pushed forward the fast implementation of AI solutions across, which has allowed for even more efficient trial designs, patient recruitments, and real-time analysis of data.
Prominent players in the AI in clinical trials market include are IQVIA Inc. (US), Saama. (US), Dassault Systèmes (Medidata) (France), Phesi (US), PathAI, Inc. (US), Unlearn.ai, Inc. (US), Deep6.ai (US), Microsoft (US), IBM (US), NVIDIA Corporation (US), Insilico Medicine (US), ConcertAI. (US), AiCure. (US), Median Technologies. (France), Lantern Pharma Inc. (US), Citeline, a Norstella Company (US), Tempus AI, Inc. (US), TriNetX, LLC (US), ReviveMed Inc. (US), Euretos. (US), VeriSIM Life. (US), Triomics (US), Ardigen (Poland), QuantHealth Ltd. US), and DEEP GENOMICS. (Canada).
Recent Developments of AI in Clinical Trials Market
-In November 2024, Bioforum (Israel) and Medidata (France) took their collaboration a step further providing Bioforum’s clientele in the field of biotechnology with greater access to Medidata’s Al-based technologies. Apart from Medidata Rave EDC and RTSM, Bioforum shall employ Medidata Clinical Data Studio and Medidata eConsent in order to enhance data transfer, quality and regulation of clinical trials.
-In April 2024, IQVIA (US) partnered with Salesforce (US) to accelerate the life sciences cloud development for customer engagement.
-In February 2024, Saama (US) collaborated with Pfizer Inc. (US) to expand multi-year agreement to scale Smart Data Quality (SDQ), leveraging AI to streamline and accelerate data review processes across Pfizers global clinical research portfolio.
-In October 2023, Saama (US) signed a multiyear agreement with AstraZeneca (UK) to streamline clinical data management and medical review processes using Saama’s Al-enabled technology platform. The agreement was designed to hasten the process of drug development incorporating Smart Data Quality (SDQ), Data Hub and Patient Insights solutions thereby facilitating faster data lock and efficient reviews of the data.
