Machine translation is the process of using computer algorithms and software to automatically translate text or speech from one language to another. Instead of relying on human translators to manually translate content, machine translation systems analyse a source text based on rules, using statistical models, or neural networks or hybrid models, to generate an approximate translation in the desired language.
As a natural language processor model, machine translation has become increasingly prevalent with advancements in artificial intelligence and machine learning. It offers a faster and more scalable solution to language translation for various use cases from document translation to website localisation and use in real-time communication.
Machine translation holds significant implications for clinical research, offering both opportunities and challenges. Clinical research typically involves collaboration among researchers, healthcare professionals, patients, regulatory authorities and institutions across different countries and regions. Machine translation fosters quicker ways of communication and collaboration by facilitating the translation of study-related documents and findings among stakeholders who speak different languages. This promotes international cooperation and expands the pool of expertise available for research endeavours.
Machine translation can also aid in the recruitment of participants for clinical trials by making study materials accessible in multiple languages. The use of machine translation improves inclusivity and diversity in clinical research, allowing individuals from diverse linguistic and culture backgrounds to participate, where in the past costs, time constraints or language barriers would have blocked such efforts. Moreover, translated consent forms, patient information leaflets, and communication materials enhance participant understanding and engagement, ensuring informed decision-making throughout the research process.
Clinical research generates vast amounts of data, including patient records, medical reports, and research publications. Machine translations enable researchers to analyse and extract insights from multilingual data more efficiently. By translating research literature and data from and into different languages, researchers can conduct comprehensive literature reviews, meta-analyses, and cross-cultural studies, leading to a deeper understanding of medical conditions and treatment outcomes.
At the same time, it must be clear that machine translation and any other kind of artificial intelligence cannot be used without adequate supervision and control by a human specialist, especially in clinical research and medical device development. In clinical research, accuracy and consistency are paramount, particularly when translating sensitive medical information and regulatory documents.
Machine translation, when coupled with human post-editing and quality assurance processes, helps ensure the accuracy and reliability of translated content usually at a quicker time to still enable the majority of benefits listed before. Adherence to regulatory standards, such as Good Clinical Practice (GCP) guidelines and International Conference on Harmonisation (ICH) requirements, is essential to maintaining the integrity of clinical trials and ensuring compliance.
Ensuring best practices in post-editing
Machine translation offers a practical solution for translation projects, enhancing turnaround times, productivity, consistency, and efficiency. However, it's essential to recognise that the quality of machine translation output does not always match that of human translation. ISO Standards are created by the International Organisation for Standardisation (ISO) with the aim of guiding companies in the process of establishing levels of consistency and quality in relation to the management, provision of services and product development in the industry. ISO certification is awarded through a rigorous audit process, during which an objective review of a company’s systems, products and processes is conducted. ISO 18587 certification provides guidelines for ensuring high-quality translations through the process of human post-editing of machine translation output.
ISO 18587 applies to the post-editing of machine-translated content in various domains, including but not limited to technical documentation, legal texts, marketing materials, and medical documents. The standard outlines best practices and specifies competencies and qualifications required for post-editors, including linguistic proficiency in both source and target languages, subject matter expertise, familiarity with machine translation technology, and knowledge of post-editing techniques. ISO 18587 certification helps ensure consistency and quality in the post-editing process, fostering trust and confidence in machine-translated content across various industries and applications.
Following a successful ISO audit, we are proud to announce that ICON Language Services has achieved ISO 18587 certification for Machine Translation Post Editing Output effective 21st November 2023. The successful audit also resulted in the renewal of existing ISO 17100 certification - the internationally recognised standard for the delivery of quality translation services. ISO 9001, the globally recognised standard for quality management, was also awarded in 2021. This means we are now the only full-service, ISO 17100, ISO 9001, and ISO 18587 certified translation provider within a global top-tier CRO, offering total harmonisation between product development processes and translation methodology.
Contact us to learn more about how we can support your language services needs.
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Digital Disruption
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Clinical trial data anonymisation and data sharing
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Clinical Trial Tokenisation
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Closing the evidence gap: The value of digital health technologies in supporting drug reimbursement decisions
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Digital disruption in biopharma
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Disruptive Innovation
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Personalising Digital Health
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The triad of trust: Navigating real-world healthcare data integration
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Patient Centricity
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Agile Clinical Monitoring
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Capturing the voice of the patient in clinical trials
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Charting the Managed Access Program Landscape
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Developing Nurse-Centric Medical Communications
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Exploring the patient perspective from different angles
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A guide to safety data migrations
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Agile Clinical Monitoring
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Using innovative tools and lean writing processes to accelerate regulatory document writing
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Current overview of data sharing within clinical trial transparency
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Navigating orphan drug development from early phase to marketing authorisation
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Procedural and regulatory know-how for China biotechs in the EU
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Early engagement and regulatory considerations for biotech
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Regulatory Intelligence Newsletter
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Requirements & strategy considerations within clinical trial transparency
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Spotlight on regulatory reforms in China
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Demystifying EU CTR, MDR and IVDR
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Transfer of marketing authorisation
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Rare and orphan diseases
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Advanced therapies for rare diseases
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Cross-border enrollment of rare disease patients
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Crossing the finish line: Why effective participation support strategy is critical to trial efficiency and success in rare diseases
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Diversity, equity and inclusion in rare disease clinical trials
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Identify and mitigate risks to rare disease clinical programmes
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Leveraging historical data for use in rare disease trials
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Natural history studies to improve drug development in rare diseases
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Patient Centricity in Orphan Drug Development
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The key to remarkable rare disease registries
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Therapeutic spotlight: Precision medicine considerations in rare diseases
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Advanced therapies for rare diseases
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Decentralised clinical trials
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Biopharma perspective: the promise of decentralised models and diversity in clinical trials
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Decentralised and Hybrid clinical trials
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Practical considerations in transitioning to hybrid or decentralised clinical trials
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Biopharma perspective: the promise of decentralised models and diversity in clinical trials
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