PharmaTrace

Custom Health and PatchRx Partner to Build a Comprehensive Medication Intelligence Solution

The collaboration merges expertise in medication adherence technologies to create a first-of-its-kind platform designed to improve health outcomes and empower patients. KELOWNA, BC, Nov. 26, 2024 /PRNewswire/ -- Custom Health, a leader in transforming medication outcomes for patients across the U.S. and Canada, today announced a partnership with PatchRx to integrate PatchRx's smart pill bottle caps into Custom Health's innovative medication adherence platform. By combining their technologies, the companies aim to set a new standard in medication intelligence, offering a powerful, data-driven solution for health plans, providers and pharmacies. Custom Health specializes in supporting complex patients with multiple chronic conditions, through personalized medication management and remote clinical oversight. With a tech suite that includes individualized pill-packing, smart medication adherence dispensers, and AI trained to identify prescribing risks, Custom Health operates digital hub pharmacies and supports a network of 100+ pharmacies across the U.S. and Canada. These pharmacies deploy technology into patients' homes, enabling remote monitoring by Custom Health's 200+ U.S. clinicians and achieving a 98% medication adherence rate. Custom Health's nation-leading deprescribing program has moreover reduced opiod utilization by 27%. "At Custom Health, we are passionate about making it easier for people to take their medications and ensuring those medications deliver the intended result," said Shane Biship, CEO of Custom Health. "Integrating PatchRx technology into our AdhereNet® platform enhances our ability to monitor adherence in real time and take swift action to support patients and improve outcomes. Together, we're delivering more than technology -- we're delivering better health." PatchRx's clinically validated smart pill bottle caps, already used successfully in Remote Therapeutic Monitoring programs across the U.S., will complement Custom Health's existing suite of tools, creating an integrated medication intelligence platform. The partnership reflects a shared commitment to addressing the root causes of non-adherence and transforming patient care. "The core of our mission at PatchRx is understanding the causes of medication non-adherence and developing solutions that address the root cause," said Gavin Buchanan, co-founder of PatchRx. "Custom Health shares this mission and has proven its ability to improve outcomes time and again. We expect this partnership to allow us to build a new gold standard in medication management for patients and medication intelligence for pharmacies, providers, and payors." About Custom Health Custom Health helps people achieve the best possible health outcomes through its integrated healthcare delivery model, which includes personalized medication management, always-on clinical oversight, remote patient monitoring, and home-based care. With an obsession for the journey of a pill, Custom Health connects patients with their circle of care, ensuring medications are taken as prescribed and delivering solutions that go beyond adherence to ensure medications work as intended. Learn more at www.customhealth.com About PatchRx PatchRx is revolutionizing patient care through its clinically backed medication adherence technology. The company's patented smart pill-bottle caps for generic prescription bottles, combined with its comprehensive software platform, arm providers with the insight needed to assess a treatment's effectiveness and intervene early to prevent adverse outcomes. PatchRx has improved care outcomes for thousands of patients across the U.S., closing the gap between a patient's prescribed treatment and actual medication-taking behaviors. To learn more, visit PatchRx.io. View original content:https://www.prnewswire.com/news-releases/custom-health-and-patchrx-partner-to-build-a-comprehensive-medication-intelligence-solution-302316597.html SOURCE Custom Health Market News and Data brought to you by Benzinga APIs

Benzinga

Tue, 26 Nov, 4:19 PM UTC

Atropos Health Deploys AI Models to Identify Undiagnosed Conditions

Generative AI accelerates precision medicine, improving outcomes and patient experiences. Atropos Health announced on Monday the deployment of AI models to identify patients living with undiagnosed conditions. These AI models will be made available to clinicians through members of the Atropos Evidence Network. According to the company, Atropos Health's AI-built models are developed, trained, and tested using real-world data (RWD) from the Atropos Evidence Network, which includes over 300 million patient records. The goal is to reduce the time from initial symptoms to testing, diagnosis, and treatment at the point of care. Also Read: Meta Says Open-Source AI Is Transforming Healthcare Outcomes The models are created by Atropos Health medical doctors, epidemiologists, statisticians, and experts. Their implementation is expected to save clinicians time and improve the patient experience by enabling earlier identification of conditions and faster treatment, the company said. "Increasing the speed, inclusivity and accuracy of precision medicine is the power of Generative AI in practice," said Brigham Hyde, CEO and co-founder at Atropos Health. "By utilizing the portfolio of Atropos Health services such as Geneva OS and the Atropos Evidence Network, precision medicine based on RWE is becoming a reality and reducing the time from symptom to treatment leads to better outcomes for patients and better experiences for providers." Atropos Health noted that members of the Atropos Evidence Network can access more RWD tailored to their specific needs, supported by the Real World Fitness Score (RWFS), which evaluates the relevance and quality of data for individual inquiries. These additional datasets enhance opportunities for partners to identify "fit-for-purpose" data. Also Read: Novo Nordisk and Valo Health Expand AI Partnership for Drug Discovery The partnership between Arcadia and Atropos Health allows healthcare providers to accelerate clinical decision-making with actionable, AI-powered insights at the point of care. By combining real-world evidence with longitudinal patient records, the partnership aims to improve outcomes while driving high-value, cost-effective care. The Evidence Network recently expanded its partnerships to include organizations such as Forian, Syndesis Health, and Norstella. Atropos Health offers automation and standardization of AI model training, testing, and deployment for healthcare AI developers. These developers can now build at scale and meet emerging AI assurance standards, applying their technologies to improve patient outcomes, the company said. Also Read: AMD Invests in Absci to Accelerate AI-Driven Drug Discovery Additionally, Atropos Health highlighted the importance of data quality and transparency in methodology through its Data Quality ScoreCard. This tool provides data holder members of the Atropos Evidence Network with a confidential way to measure, evaluate, compare, and benchmark their data quality based on objective criteria.

TelecomTalk

Tue, 14 Jan, 2:17 PM UTC

Clinical Data Analytics Market to Reach $614.7 Billion by 2034, Fueled by Surge in Chronic Disease and Technological Advancements - TMR Analysis

Enter your email to get Benzinga's ultimate morning update: The PreMarket Activity Newsletter Wilmington, Delaware, Transparency Market Research Inc. -, Feb. 18, 2025 (GLOBE NEWSWIRE) -- The clinical data analytics market is experiencing rapid expansion, with the global industry valued at $15.5 billion in 2023. By 2034, the market is expected to reach a staggering $614.7 billion, growing at an impressive CAGR of 39.7%. This growth can be attributed to the increasing prevalence of chronic diseases and the accelerating adoption of advanced technologies in healthcare. Unlock Exclusive Insights - Request a Sample of The Market Report, visit: https://www.transparencymarketresearch.com/sample/sample.php?flag=S&rep_id=86145 Cloud computing and AI-based analytics are pivotal in this transformation. These technologies have revolutionized healthcare by enabling the secure management and analysis of vast amounts of patient data. With predictive analytics, healthcare providers can identify early signs of chronic diseases and intervene proactively. Additionally, the integration of electronic health records (EHR) and mobile access has transformed patient care and clinical trials, facilitating a more interconnected healthcare ecosystem. However, while the market holds immense growth potential, challenges remain, including high subscription and licensing costs for clinical data solutions. These costs may impact smaller healthcare organizations and slow the adoption rate in certain regions. CompanyHeadquartersMarket PositionKey OfferingsIBM Watson HealthUSALeadingAI-driven analytics, cloud solutionsOptum (UnitedHealth)USALeadingPredictive analytics, population healthCerner CorporationUSASignificantEHR-integrated analyticsEpic SystemsUSASignificantReal-time analytics, EHR solutionsMcKessonUSAModerateData-driven insights, decision supportSAS InstituteUSAModerateAdvanced analytics, AI solutionsOracle HealthUSAModerateCloud-based clinical analyticsAllscriptsUSAModerateData analytics, interoperability Key Players and Latest Developments Leading companies in the clinical data analytics space are consistently innovating to maintain their competitive edge. Some of the major players include IBM Watson Health, Oracle Health Sciences, Cerner Corporation, and Medtronic, all of which are integrating advanced AI, machine learning, and predictive analytics into their offerings. In February 2023, Spotify's founder, Daniel El, launched Neko Health, a company focused on using AI-powered body scans to detect health anomalies. This innovation underscores the growing importance of AI and machine learning in clinical data analytics, especially in early detection and chronic disease management. Other key players are enhancing their platforms to support clinical trials by integrating data from various sources globally. For instance, Oracle and Cerner are investing heavily in expanding their cloud-based analytics solutions to provide better insights for clinical researchers and healthcare providers alike. CompanyRecent DevelopmentsStrengthsWeaknessesIBM Watson HealthExpanded AI capabilities, partnerships in precision medicineStrong AI expertise, global reachHigh implementation costsOptum (UnitedHealth)Acquisitions to enhance analytics capabilitiesIntegrated healthcare solutionsRegulatory scrutinyCerner CorporationAcquisition by Oracle, focus on interoperabilityStrong EHR integrationCompetition from cloud providersEpic SystemsAI-driven enhancements, focus on predictive analyticsEstablished healthcare presenceHigh cost of implementationMcKessonFocus on value-based care analyticsStrong distribution networkLimited AI capabilitiesSAS InstituteExpansion in cloud-based healthcare analyticsStrong in statistical analyticsHigh learning curveOracle HealthAcquisition of Cerner, AI-driven innovationsCloud expertise, scalabilityIntegration challengesAllscriptsPartnerships for AI-driven analyticsStrong interoperability featuresMarket consolidation risks Clinical Data Analytics Industry Overview Clinical data analytics is a field that bridges scientific research with practical healthcare solutions. It involves the collection, verification, and analysis of clinical data to enhance decision-making processes in medical practices. The role of clinical data analysts is crucial in turning raw data into actionable insights that can improve patient outcomes and streamline clinical trials. Recent innovations in the sector, such as the introduction of cloud-based solutions, have enabled healthcare providers to overcome traditional barriers of data storage and access. As organizations seek to manage ever-growing volumes of health data, cloud computing facilitates better collaboration and data-sharing across various locations and institutions. For example, Lokavant's introduction of a study planning solution in August 2023 helps optimize clinical trial performance by identifying ideal sites and site mixes. This development is part of a broader trend where clinical data analytics companies are enhancing their capabilities to handle complex datasets generated by advancements in genomics and personalized medicine. Transform Your Business with Custom Market Intelligence! https://www.transparencymarketresearch.com/sample/sample.php?flag=S&rep_id=86145 Market Drivers 1. Growing Adoption of AI and Machine Learning in Healthcare AI and ML-powered predictive analytics models are transforming the clinical landscape by enabling early disease detection, risk assessment, and personalized treatment plans. AI-driven clinical decision support systems (CDSS) are reducing medical errors and improving diagnostics. 2. Increasing Volume of Healthcare Data The exponential growth of electronic health records (EHRs), genomic data, wearable health devices, and medical imaging is creating a demand for advanced data analytics solutions. These technologies enable real-time patient monitoring and predictive analytics for chronic disease management. 3. Rising Demand for Personalized Medicine Precision medicine is gaining traction, leveraging genomics, biomarkers, and patient-specific data to tailor treatments. Clinical analytics tools help identify optimal therapies for individual patients, improving treatment effectiveness and reducing adverse reactions. 4. Government Initiatives for Healthcare Digitization Regulatory bodies like the FDA, European Medicines Agency (EMA), and Health Level Seven (HL7) are promoting healthcare data standardization and interoperability. Governments worldwide are investing in digital health transformation, electronic medical records (EMR) integration, and AI-driven healthcare systems. 5. Expansion of Telehealth and Remote Patient Monitoring With the surge in telemedicine adoption, real-time clinical data analytics is critical in virtual care management, chronic disease tracking, and remote diagnostics. AI-driven platforms assist in automating patient engagement and treatment adherence monitoring. Top Market Trends Rising Prevalence of Chronic Diseases: The increasing incidence of chronic diseases such as heart disease, diabetes, and cancer is one of the major drivers of the clinical data analytics market. Predictive analytics and early detection tools are enabling healthcare providers to intervene sooner, improving patient outcomes and reducing healthcare costs. Adoption of AI and Machine Learning: The integration of AI and machine learning into clinical data analytics platforms is enhancing data processing capabilities. These technologies help in deriving actionable insights from complex health data, supporting personalized medicine and tailored treatment plans. Cloud Computing and EHR Integration: The growing adoption of cloud computing solutions, coupled with the use of electronic health records (EHR), is transforming how healthcare data is stored, accessed, and shared. This trend is enabling more efficient and secure collaboration among healthcare providers, patients, and researchers. Personalized Medicine: With the rise of genomic medicine, personalized treatment options are becoming more prevalent. Clinical data analytics is playing a critical role in aggregating data from various sources to support the development of personalized care strategies. The clinical data analytics market is directly impacting patient care and clinical research. For consumers, the growing use of AI-driven insights in healthcare can result in more precise diagnoses and treatment plans. Predictive analytics, for example, is helping detect chronic conditions at an earlier stage, offering patients a better chance at managing their health proactively. Additionally, the healthcare industry's shift towards data-driven decision-making is improving the efficiency of clinical trials. By enabling real-time data analysis and secure collaboration, clinical data analytics is reducing the time and cost associated with bringing new treatments to market, benefiting both healthcare providers and consumers alike. Segments and Regions By Application: Chronic Disease ManagementClinical Trials OptimizationPredictive Analytics in HealthcareElectronic Health Records (EHR) ManagementOthers (Genomics, Drug Discovery) By Technology: Artificial Intelligence (AI)Machine Learning (ML)Natural Language Processing (NLP)Cloud Computing By Region: North America: U.S.Canada Europe: GermanyU.K.FranceItalySpain Asia Pacific: ChinaIndiaJapanSouth Korea Middle East & Africa: Saudi ArabiaUAEQatar Latin America: BrazilMexico Purchase the Full Market Report Today: https://www.transparencymarketresearch.com/checkout.php?rep_id=86145&ltype=S Future outlook The clinical data analytics market is poised for exponential growth, driven by advancements in healthcare technologies and the increasing burden of chronic diseases. The integration of AI, machine learning, and cloud computing will continue to shape the industry, enabling healthcare providers to make more informed decisions and improve patient outcomes. As the market expands, innovations from leading companies and the rise of personalized medicine will likely drive the next wave of growth, offering promising opportunities for stakeholders across the healthcare ecosystem. Explore Latest Research Reports by Transparency Market Research: Phototherapy Treatment Market (광선치료 시장) is expected to grow at a CAGR of 5.2% from 2024 to 2034 and reach US$ 3.4 Billion by the end of 2034.PEEK Interbody Devices Market (PEEK 체간 장치 시장) expected to grow at a CAGR of 7.7% from 2024 to 2034 and reach US$ 5.0 Billion by the end of 2034. About Transparency Market Research Transparency Market Research, a global market research company registered at Wilmington, Delaware, United States, provides custom research and consulting services. Our exclusive blend of quantitative forecasting and trends analysis provides forward-looking insights for thousands of decision makers. Our experienced team of Analysts, Researchers, and Consultants use proprietary data sources and various tools & techniques to gather and analyses information. Our data repository is continuously updated and revised by a team of research experts, so that it always reflects the latest trends and information. With a broad research and analysis capability, Transparency Market Research employs rigorous primary and secondary research techniques in developing distinctive data sets and research material for business reports. Transparency Market Research Inc. CORPORATE HEADQUARTER DOWNTOWN, 1000 N. West Street, Suite 1200, Wilmington, Delaware 19801 USA Tel: +1-518-618-1030 USA - Canada Toll Free: 866-552-3453 Website: https://www.transparencymarketresearch.com Email: sales@transparencymarketresearch.com Follow Us: LinkedIn| Twitter| Blog | YouTube Market News and Data brought to you by Benzinga APIs

Benzinga

Tue, 18 Feb, 4:13 PM UTC

How Generative AI Can Accelerate Pharma GCCs in India

By combining AI tools and fast talent scaling, Agilisium is helping pharma companies overcome data barriers. Drug development is an expensive and high-risk process. The median cost per approved drug can reach up to $2.8 billion, largely due to failures at each stage, from discovery and preclinical research to late-stage clinical trials. Pharmaceutical companies deal with various data sources, including clinical trials, real-world evidence, and patient data, which are often siloed and difficult to integrate. Moreover, incorrect data can result in regulatory issues, such as FDA application denials, leading to major delays in bringing drugs to market and potential damage to the company's reputation. To navigate these challenges and mitigate risks, pharmaceutical Global Capability Centers (GCCs) are turning to artificial intelligence (AI). For instance, Los Angeles-based Agilisium Consulting complements this journey with its agentic AI solutions like NextGen DLS agent, Content generation, Insight Generation, and Data Observability to accelerate transformation in Pharma GCCs. Agilisium's Content Generation, built for the life sciences industry, addresses the challenges of creating compliant, precise, and scalable content. It uses AI to automate the development of clinical trial protocols, regulatory submission dossiers, patient narratives, HCP engagement materials, infographics, educational training modules, case report forms (CRFs), drug safety reports, patient recruitment campaigns, post-marketing surveillance reports, grant proposals, and product labeling and packaging content. The platform ensures alignment with regulatory standards like FDA and EMA, reducing time-to-market while maintaining accuracy and compliance. On the other hand, NexGen DataOps Platform is an AI-powered that improves data management in the Life Sciences industry. It uses smart agents to help companies monitor their data, detect issues in real time, and analyse trends. The multi-agent model enables data teams to accelerate time-to-insight, making decision-making more efficient. Additionally, the well-trained LS Co-Pilot provides recommendations for improvements, quickly resolves errors, and automates updates for business teams. It enhances the data-sharing model seamlessly without compromising security. Agilisium's Insights Generation solution takes data analysis and decision-making in the Life Sciences sector to the next level. It connects to a variety of data sources - from Scientific Journals and Databases, Unstructured Data, Electronic Health Records (EHRs), Genomic and Proteomic Data, Laboratory Information Management Systems (LIMS), Data Warehouses and Knowledge Graphs.This allows organisations to tap into both structured and unstructured data with ease, unlocking deeper insights. With powerful search capabilities, including keyword and full-text search, the platform drastically cuts down the time spent retrieving documents. This means researchers can spend less time searching for data and more time on critical analysis, making their work more efficient and impactful. Agilisium's Data Observability solution ensures accurate, compliant, and AI-ready data with end-to-end observability. Gain full visibility, detect anomalies in real-time, and enhance data integrity for better decision-making. With no-code onboarding, security-first architecture, and seamless scalability, the solution integrates effortlessly with your existing data stack, providing a single view of data health across lakes, warehouses, ETL, and BI tools. Pharma GCCs can accelerate innovation and reduce significant operation costs by collaborating with GenAI-as-service based solution providers who are exclusively Life Sciences domain lead experts. Agilisium is the preferred AWS partner that emerged as one of the Top 11 AWS Partners with both Life Sciences Consulting Competency and Generative AI Services Competency across the globe. One standout success is Agilisium successfully rearchitected a fortune 500 Biopharma company with AI-powered commercial data lake and data warehouse with end-to-end process automation, resulting in a 75% increase in data processing efficiency and enabling data availability and accessibility for stakeholders but also led to multimillion-dollar annual cost avoidance. With generative AI now in the picture, data analytics companies are witnessing a change, with companies like ZS Associates, Indegene, Axtria, Zifo and Saama Analytics leading the charge in India. However, Agilisium has been growing steadily in India since its inception in 2014, now employing over 700 professionals. The company plans to expand to 2,000 employees by the end of 2027. A significant part of Agilisium's growth is the opening of a new facility at Hyderabad's RMZ Spire campus in Cybercity, a city renowned as India's pharma hub. This move aims to strengthen Agilisium's GenAI solutions, evolving them into Agentic AI solutions focused on transforming the Pharma and Life Sciences industries. This new facility will function as both a Global Delivery Centre and a Gen AI Innovation Centre of Excellence. The city's strong pharmaceutical centric business expansion and proximity to Genome Valley make it an ideal location for this expansion. Today, GCCs are a major part of India's IT and services sector, employing over 1.6 million people. According to EY, this growth will continue, with over 2,400 GCCs expected to create jobs for about 4.5 million people by 2030. The market size is expected to grow from $45 billion now to $110 billion by 2030. According to a recent report, GCCs in India are hiring 30% more fresher and entry-level talent from colleges and off-campus sources to expand the talent pool and secure more affordable talent. With rising demand for data and analytics skills in service offerings, 51% of GCCs are prioritising technology and AI reskilling for growth, according to EY. Agilisium offers a Build-Operate-Transfer (BOT) model that enables companies to design and develop a state-of-the-art Centre of Excellence for technology teams with the top 1% of talent, who are trained in Life Sciences domain knowledge. Agilisium has 20+ F500 & Global 2000 Biopharma companies, offering them support in enhancing the entire pharma-vale chain through developing future-proof Gen AI solutions through Agilisium Labs, an Innovation unit of Agilisium.

Analytics India Magazine

Thu, 20 Feb, 12:05 PM UTC

Council Post: How AI Can Be A Tool For Clinical Trials Success

The promise of AI in drug discovery has fueled big business for the pharmaceutical industry with new AI drug companies smashing funding records one after another and new partnerships between big pharma and AI startups announced nearly every month. To date, most of the focus on AI's power revolves around its ability to enable the discovery of new drug targets. This only scratches the surface of what it takes to develop a new medicine, and the hype around AI as a magic bullet misses the bigger opportunity, which is to use AI to guide every stage of the drug discovery process. With only about 12% of drugs that enter clinical trials ultimately earning FDA approval, there is significant untapped potential for AI to improve the design of clinical trials, increase the predictability of trial outcomes and improve the overall efficiency of the clinical trial process. Not all AI is created equal. Many kinds of AI tools can be used in the drug development process. However, given that the ultimate goal of a clinical trial is to learn whether a therapeutic candidate is safe and effective so that it can benefit patients, there are several ways that leveraging a biology-first approach to AI can improve the potential for a successful clinical trial outcome. This type of approach, where AI serves as a tool informed by biological indicators, not only serves the patients participating in the study but also offers the potential to accelerate the process of the drug's approval to benefit a broader population of patients ultimately. Understanding how a drug works can help companies choose the best way to run a clinical trial. AI can quickly assimilate massive amounts of data gleaned from an analysis of patient tissue, blood, and urine samples, enabling researchers to make sense of the mechanism of action and why it's safe at both the population and individual levels. Following a phase 1 trial we conducted with patients with several different types of cancer, our AI models helped us understand how the drug changed the cancer's metabolism, which explained why the drug worked better in patients with more aggressive tumors than in patients with less aggressive tumors. Armed with this information, we prioritized our future drug development activities to focus on patients with more aggressive cancers. Different patients have different biology -- different genetics and different biological manifestations of disease. These characteristics can be critical to a person's success or failure with a therapy being studied because patients who metabolize a therapy at different rates might experience the therapy's effects differently -- both in terms of the medicine's safety and its treatment effect. With the help of AI modeling, leaders can help predict which types of patients are most likely to respond to therapy and be able to tolerate it. By knowing this information and selecting only patients likely to benefit and tolerate a therapy, trial sponsors can manage risk and improve their chance of a positive clinical trial outcome. Even the best-planned trials, backed by the most rigorous science, can have unexpected results. AI modeling can help shed light on adverse events and help companies understand -- on a biological level -- why those events occurred. This enables the company to modify their clinical protocols to attempt to limit toxicities in future trials or to understand why some patients experienced safety issues and others didn't so that the company can select patients less likely to experience safety issues in future studies. Sometimes, AI can help us identify ways to mitigate safety issues with simple changes to the trial protocol, such as how our company addressed bleeding events by adding vitamin K to a drug being studied to treat cancer. Other times, AI modeling can elucidate safety issues that can't be overcome, allowing the company to pivot more quickly. Some conditions, such as cancer, can best be treated with combinations of therapies. Still, it can be challenging to know which therapies can be combined safely and effectively and which might be effective when combined but not safe. AI can help model each scenario being considered, helping not only to understand which therapies can be used in combination or at what dosages but also to understand whether the combination therapies should be administered at the same time or sequentially. When clinical trials don't meet their endpoints, AI can help researchers understand why, helping fuel iteration and catalyze opportunities for future exploration. AI modeling, leveraging insights gleaned from biological samples, can power an iterative process of designing, building, testing and learning that is the hallmark of biomedical innovation and the opportunity for AI to speed learning and innovation in drug discovery and development. Taking a broader view of AI's benefits in drug discovery and development is truly the path forward, as the pharmaceutical industry seeks to overcome decades of productivity declines and align with socioeconomic pressures to reduce the cost of therapeutics that ultimately reach the market for patient benefit. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?

Forbes

Tue, 16 Jul, 12:03 PM UTC

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