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Showing 25 results
  • Video
    Feb. 10, 2026

    Everest Group’s PEAK Matrix® Assessment assesses RTSM providers through the lens of buyer impact and delivery capability. In this deep dive, Nisarg Shah, Practice Director, and Kayva Murki, Senior Analyst, analyze the RTSM provider market in…
  • Video
    Feb. 10, 2026

    The PEAK Matrix® Assessment provides a structured evaluation of RTSM providers’ strengths, scale, and differentiation in the market. Nisarg Shah, Practice Director, and Kayva Murki, Senior Analyst, explore the major growth drivers accelerating RTSM adoption. They…
  • Video
    Feb. 10, 2026

    Everest Group’s PEAK Matrix® Assessment evaluates RTSM providers based on market impact and vision & capability. In this video, Nisarg Shah, Practice Director, and Kayva Murki, Senior Analyst, unpack findings from the inaugural RTSM PEAK Matrix®…
  • Provider Compendium
    Dec. 30, 2025

    Enterprises are repositioning quality from a downstream testing activity to a strategic engineering capability embedded across the software development life cycle. As digital, cloud, and AI initiatives scale, expectations are moving beyond defect identification toward resilience,…
  • Provider Compendium
    Dec. 17, 2025

    Life sciences organizations are increasingly prioritizing automation, configurability, and real-time visibility to support modern clinical trial requirements. As adaptive designs, decentralized models, and global multi-protocol studies become more prevalent, the role of Randomization and Trial Supply…
  • PEAK Matrix®
    Nov. 25, 2025

    With global and adaptive clinical trials’ rising complexities, life sciences organizations are increasingly adopting intelligent Randomization and Trial Supply Management (RTSM) platforms to enhance operational efficiency, ensure regulatory compliance, and safeguard patient integrity. RTSM systems have…
  • PEAK Matrix®
    Nov. 13, 2025

    Enterprises are elevating quality from a downstream test phase to a strategic engineering discipline woven through the software development life cycle. As digital, cloud, and AI programs scale, expectations shift from defect detection to resilience, velocity,…
  • Viewpoint
    Nov. 10, 2025

    As enterprises accelerate digital transformation and embrace next-generation technologies such as AI, generative AI, and cloud-native platforms, managing quality at scale has become increasingly complex. Traditional tool-centric quality approaches fall short in addressing fragmented processes, inconsistent…
  • Blog
    Nov. 04, 2025

    In an era of increasingly complex clinical trials, Risk-Based Quality Management (RBQM) has emerged as more than a regulatory mandate, it is a strategic imperative. Traditional monitoring methods, reliant on exhaustive on-site visits and 100% Source…
  • PEAK Matrix®
    Oct. 29, 2025

    Enterprises are reimagining quality as a strategic engineering function rather than a downstream testing activity. As a result, demand for specialized Quality Engineering (QE) services is growing rapidly across industries. This analysis shows how the specialists…
  • Tech Provider Spotlight
    Oct. 14, 2025

    Clinical trial complexity continues to increase with hybrid study models, diverse data sources, and growing regulatory expectations, making traditional oversight models inadequate. Conventional monitoring approaches reliant on 100% source data verification and frequent on-site visits are…
  • Provider Compendium
    June 27, 2025

    CTMS platforms centralize and streamline every aspect of a clinical trial – planning, site coordination, patient tracking, budget oversight, document management, and regulatory compliance – into one unified, cloud-based system. The increasing trial complexity, the growing…
  • Viewpoint
    June 27, 2025

    Clinical trials are becoming more complex due to the adoption of decentralized models, increasing data volumes, and greater regulatory scrutiny. Conventional approaches centered on 100% Source Data Verification (SDV) and uniform on-site monitoring are inefficient, costly,…
  • May 12, 2025

    Risk-Based Monitoring (RBM), once seen as a breakthrough in clinical trial oversight, now faces challenges in keeping up with the growing complexity and regulatory demands of modern trials.While it brought significant improvements in monitoring efficiency, now…
  • State of the Market
    May 07, 2025

    The life sciences R&D engine is rapidly digitizing, and clinical development software now sits at its center. This report sizes the global clinical trials technology market at nearly US$6.5 billion for 2025 (8-10% CAGR) and dissects…
  • Provider Compendium
    Feb. 28, 2025

    Decentralized and hybrid designs add more complexity to clinical trials, generating vast data volumes from diverse sources. This complexity creates significant data management challenges. In response, sponsors are adopting unified clinical Data and Analytics (D&A) platforms…
  • Viewpoint
    Feb. 21, 2025

    The clinical trial landscape is fundamentally transforming with generative AI adoption. Historically, trials have relied on manual processes for protocol design, database lock, and regulatory documentation, often leading to inefficiencies, rising costs, and prolonged development timelines.…
  • Provider Compendium
    Feb. 14, 2025

    Electronic Data Capture (EDC) systems are integral to clinical research, enabling clinical data collection, storage, and management. EDCs mark a significant shift from paper-based case report forms to digital and web-based trial data collection. The COVID-19…
  • PEAK Matrix®
    Nov. 12, 2024

    Due to decentralized and hybrid designs, the growing clinical trial complexity generates vast data volumes from diverse sources and creates significant data management challenges. In response, sponsors are increasingly employing unified clinical data and analytics (D&A)…
  • Viewpoint
    Oct. 29, 2024

    The clinical development landscape is rapidly evolving, with hybrid trial approaches and the growing use of RWD/RWE. Clinical trial sponsors are increasingly challenged to manage the vast volume of data generated during multiple, simultaneously running trials.…

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