In healthcare and biopharma, ensuring patient safety, product quality, and regulatory compliance has always been paramount. A Quality Management System (QMS) serves as the backbone for these priorities, providing a structured framework for risk management, process standardization, and continuous improvement.

Digital transformation in the biopharma industry isn't just about adopting the latest technologies—it's about fundamentally reimagining how clinical trials are designed, conducted, and analyzed. This shift involves integrating artificial intelligence (AI), cloud computing, and data analytics to streamline operations, accelerate drug development, and improve patient experiences.

In the evolving landscape of regulatory writing, it has become clear that creating clear and compliant documents is no longer enough. Building off the principles of lean authoring, regulatory writers must now consider holistically the experience of those who will review the documents.

In the race to bring software solutions to market, many software vendors face the challenge of balancing functionality, speed, and user experience. Often, accessibility can become an afterthought—not by intention, but due to the fast-paced nature of development. However, ensuring that authoring tools are accessible from the start offers immense benefits for all users.

AgileWriter™ is an AI tool designed specifically for medical writing, developed by experts in the field to meet the precise needs of clinical documentation. Importance of Subject Matter Experts: Involving subject matter experts (SMEs) in the creation of AI tools for medical writing ensures the tool is practical and meets user needs, avoiding misalignment and inefficiencies.

Artificial Intelligence (AI) is revolutionizing the field of cancer immunotherapy by accelerating the discovery, development, and delivery of innovative treatments. Here is a breakdown of its potential role: Drug Discovery: AI algorithms can analyze vast amounts of genomic, proteomic, and clinical data to identify potential drug targets and predict the efficacy of immunotherapies.

The curb-cut effect refers to the broad and often unexpected benefits of designing for accessibility. Originally intended to assist people with physical disabilities, curb cuts have since proven beneficial for many others—parents with strollers, delivery workers with carts, and even travelers with rolling luggage.

In the rapidly evolving landscape of artificial intelligence, ensuring that generative AI systems adhere to robust standards is crucial. The National Institute of Standards and Technology (NIST), for example, has developed the Generative AI Intelligence Profile, a comprehensive framework designed to guide the development and deployment of generative AI technologies.

In the fast-evolving biopharmaceutical industry, the integration of artificial intelligence (AI) into clinical documentation processes presents an unprecedented opportunity to enhance efficiency and accuracy across the entire value chain. By adopting a technology-agnostic AI system, biopharma companies can significantly streamline operations, reduce costs, and accelerate drug development, ultimately delivering innovative therapies to patients more quickly.

As artificial intelligence (AI) permeates various aspects of life and business, the importance of explainable AI (XAI) grows, particularly in content creation tools—especially when those are being used in a regulated environment. Explainable AI enhances user trust by making the workings of AI systems transparent and comprehensible.

In recent years, lean authoring principles have emerged as a cornerstone for efficient and effective communication. These principles, which emphasize planning, avoiding redundancy, and using precise language, are especially relevant in technical and professional writing.

The World Health Organization (WHO) has long been a guiding force in global health issues, setting standards and offering recommendations to ensure the well-being and safety of populations worldwide.

Artificial intelligence (AI) systems are increasingly integrated into various sectors, including healthcare, finance, and customer service, making their reliability and accuracy critical. However, one lesser-known issue that can arise with AI systems is confabulation (aka hallucinations, fabrications).

In an era dominated by rapid advancements in artificial intelligence (AI), the need for robust governance frameworks has never been more critical. The Universal Guidelines on Artificial Intelligence (UGAI) represented a pioneering effort to address the ethical, legal, and societal challenges posed by AI technologies.

Clinical documentation is a critical component in the healthcare and pharmaceutical industries, serving as the backbone for clinical studies, regulatory submissions, and patient care. Developing and maintaining metrics for the production of clinical documentation is essential to ensure quality, compliance, and efficiency and to be able to identify and mitigate risk during this process.

In today’s rapid digital transformation of the clinical trials space, artificial intelligence (AI) is becoming an indispensable part of meeting business goals and improving patient care and treatment.

The environmental impact of artificial intelligence (AI) is increasingly scrutinized due to the significant energy consumption and carbon emissions associated with data centers and computational processes. As a product of Synterex, AgileWriter.ai embodies a unique position in the AI landscape, integrating Synterex’s rigorous sustainability practices to mitigate environmental impacts effectively.

Artificial intelligence (AI) continues to reshape industries, societies, and economies globally. As AI technologies evolve and integrate deeper into various sectors, establishing robust frameworks to manage their development and use becomes crucial. The Organization for Economic Co-operation and Development (OECD) has taken significant steps in this direction with its Recommendation on Artificial Intelligence.

In the rapidly evolving landscape of artificial intelligence (AI), the 11 × 11 tipping point has emerged as a critical concept. This tipping point refers to the moment when AI technologies reach an optimal level of efficiency and effectiveness.

The United Nations General Assembly in March 2024 adopted a significant resolution aimed at leveraging artificial intelligence (AI) for sustainable development while ensuring it remains safe, secure, and trustworthy. This initiative underscores a global commitment to balancing technological advancement with ethical standards, human rights, and social inclusiveness.