Automation within Medical Writing

What does medical writing function do?

Medical writing is a highly specialized field that involves content writing and clinical research on scientific documents of different types which include regulatory and research-related documents, disease or drug-related educational and promotional literature, periodicals, publication articles like journal manuscripts and abstracts, content for healthcare websites, health-related magazines, or news. These texts can be read by anyone from a layperson to a highly qualified medical professional.

Medical writing is an umbrella term that refers to both technical and scientific writing in health, medicine, and other life science disciplines. The profession includes communicating composite data and ideas in a clear, brief, plausible, absolute, and convincing manner. It’s all about developing materials about medicine and health by collecting, organizing, interpreting, and presenting information in a manner appropriate for the target audience. Medical writers help to analyse, organize, and present the data into a variety of formats with creative work involving research, analysis, and communication for different audiences, including, but not limited to, regulatory authorities, public, patients and their caregivers, and physicians.

Trends of using Technology within Pharma and Life sciences Industry.

Many pharmaceutical and Life Sciences sectors have been seeing the regulatory standards constantly changing and evolving quickly, and spending on research and development has been rising constantly. Necessity to continuously adapt, produce, maintain, and update medical material has evolved. There is a steady shift toward accepting automation in managing these changes, the medical writing industry is also trying to adapt to this situation and is moving towards using innovative solutions which can ease the process using AI/ML/NLP/NLG solutions.

Several companies are now assessing and employing AI solutions to automate conventional writing processes that are time-consuming and tedious. As these companies have realized the importance of automation in the medical writing space, they have agreed that AI solutions can save up to 80% of the medical writer’s time and can process and manipulate large amounts of data within few minutes. Companies are adopting multiple approaches with automation. They are either developing internal automation capabilities for QC, data structuring, analysis, and generating documents, etc., or they are partnering with companies that have automation platforms.

Building AI System for Medical Writing

Increasingly, building AI systems is becoming less complex and cheaper. The principle behind making a good AI is collecting relevant data to train the AI model. AI models are programs or algorithms that enable the AI to recognize specific patterns in large datasets. The better you make AI technology, the more wisely it can analyse vast amounts of data to learn how to perform a particular task.

The process of analysing data and performing tasks is called machine learning (ML). For example, Natural language processing (NLP) gives machines the ability to read, understand human languages, and mimic that behaviour. The most promising AI apps rely on ML and deep learning. The latter operates based on neural networks built similarly to those in the human brain. Example of real-world applications of AI include Speech recognition, Computer vision, discovery of data trends, Fraud prevention etc.

Medical Writing and Technology

To build AI powered solution, one must identify the problem that needs to be solved, collect the right data, create algorithms, train the AI model, choose the right platform, pick a programming language, and, finally, deploy and monitor the operation of the respective AI system.

Medical Writing field also has a need for Automation in the industry now and want to leverage the techniques and algorithms of Natural Language Processing (NLP) and Natural Language Generation (NLG) to generate content in their areas. The data that is being currently worked on are transforming into Artificial Intelligence (AI) has made major strides in producing, processing, and mining text. These AI-powered engines can understand the context and suggest appropriate terminology. The technology is also helpful when creating intuitive material. The algorithms should be programmed properly, so that computer displays no bias. Based on its training, it offers its predictions and recommendations. Medical writers can use computer innovation and the rise of AI in the fields of NLP and NLG to their advantage while producing medical documentation.

The technology of AI/ML/NLP/NLG has certain criteria and steps as a process to create the platform. From Medical writing perspective, this may include identifying and analysing the word structure, check the syntax/grammar, make meaningful words, mapping these words to appropriate dictionaries, and setting the context of the words with the meaning of the sentence, and then interpretating the actual meaning of the sentence. AI, when clubbed with NLP and NLG, automatically extracts information from a variety of data sets, whether they are organized (structured) or unstructured. It can then analyse the extracted data to comprehend and categorize the content’s substance and context and stores the content and context data in a dynamic semantic model as per the requirement.

To meet the needs of various stakeholders, the system should be built to reflect the context of the material when it needs to be reused or repurposed. The solution needs to maintain a database of data that is conveniently searchable with natural language queries. Additionally, impact analysis needs to be done to enhance change management anytime new content is made available or updated.

Traditional Approach vs Recent Technology

With advance technology, a system can provide repeated operations with a high degree of redundancy. The time and resource that is needed to create these documents are mostly spent on gathering data from already existing sources (such as Study documents like Protocol, CSR, SAP, Narratives, Publications etc) and organizing them under appropriate section headings (as per the respective templates). AI/ML/NLP solution can put all these contents and can start creating the necessary outputs and can reduce 50-80% as compared to manual traditional approach.

Medical writing expertise would be required to assist in refining the finished documents/articles and offer an expert guidance and making sure the meaning has proper scientific interpretation.

Speeding up the content generation can enable submissions and marketing authorizations faster and produce complex documents faster as compared to traditional approach (days instead of weeks for example). The capabilities of AI/ML are constantly expanding and can be used to generate documents that need higher degree of editorial expertise such as peer reviewed articles/journals, abstracts, presentations, posters, manuscripts etc.

GENINVO’s assistance with Automation 

Due to advances in data collection/processing/reporting systems, there always has been real-time demand on the availability of “clean data,” for further processing, which leads to better time management. With advancements in technology, multiple options became available to the medical writers that provided meaningful alternatives to speed up the medical writing process. 

With enhanced communication systems and automation opportunities, the said challenges are addressable in today’s world with GENINVO’s automation. GENINVO automation tools help to check the document readiness for submission within minutes and lets the medical writers to focus on the scientific content. GENINVO also provides AI/ML/NLP/NLG enabled tools/solutions for generating and content authoring medical writing deliverables with good quality and in quick time. 

GENINVO’s DocQC™ is a tool for automation of Quality Control (QC) checks that have historically required multiple, time-consuming cycles of manual review. Checks of various complexities are programmed leveraging cutting‒edge technologies. DocQC™ enables your Medical Writers to maintain their focus on the science, analyses, and presentation of results. 

Summing up

Automation and AI Techniques (NLP/NLG) are both real and here to stay. They have exciting prospects in the future of Medical Writing and is not a threat but can only support in getting the deliverables faster with Quality.

By Ramesh Venkataramana, Director Innovative solutions and strategy, GENINVO 

19th May, 2023

More Blogs

Transforming Document Creation in Life Sciences with DocWrightAI™ – GenInvo’s Advanced AI Assistant!

Transforming Clinical & Regulatory Medical Writing through the Power of AI!  GenInvo is leading the way by accelerating the availability of…
Read More

Embracing the Digital Era: The Transformative Power of Digitalization in Medical Writing

In recent years, the widespread adoption of digitalization has revolutionized various aspects of society, and the field of medical writing…
Read More

Data Masking and Data Anonymization: The need for healthcare companies

In the healthcare industry, the protection of sensitive patient data is of utmost importance. As healthcare companies handle vast amounts…
Read More

Artificial Intelligence in the Healthcare Domain: How AI Reviews Clinical Documents

Let’s know what Clinical Documents are.  Clinical Documents are written records or reports documenting various aspects of patient care and…
Read More

Importance and examples of usage of Data Anonymization in Healthcare & Other sectors

Data anonymization plays a critical role in healthcare to protect patient privacy while allowing for the analysis and sharing of…
Read More

Data Anonymization and HIPAA Compliance: Protecting Health Information Privacy

Data anonymization plays a crucial role in protecting the privacy of sensitive health information and ensuring compliance with regulations such…
Read More

Automation of Unstructured Clinical Data: A collaboration of automation and Medical Writers

In the field of healthcare, clinical data plays a crucial role in patient care, research, and decision-making. However, a significant…
Read More

Quality Control of the Methods and Procedures of Clinical Study

Methodology section of the Clinical Study Report (CSR) provides a detailed description of the methods and procedures used to conduct…
Read More

Automated Quality Control: Get the best out of your Clinical Study Report Review 

What are Clinical Study Reports?  Clinical study reports (CSRs) are critical documents that summarize the results and findings of clinical…
Read More

Clinical Study Results: Quality Control on study findings and outcomes

Clinical Study Reports, or the CSRs, are comprehensive documents providing detailed information about the design, methodology, results, and analysis of…
Read More

Big Save on Time > 60%, A case Study: DocQC™ Tested on 25 Studies.

Medical Writers have provenly spent a lot of time historically, in reviewing the Clinical Study Reports. Clinical Study Reports, or…
Read More

Data Anonymization in the Era of Artificial Intelligence: Balancing Privacy and Innovation

Data anonymization plays a crucial role in balancing privacy and innovation in the era of artificial intelligence (AI). As AI…
Read More

Automated Quality Control: Get the best out of your Clinical Study Report Review

What are Clinical Study Reports?  Clinical study reports (CSRs) are critical documents that summarize the results and findings of clinical…
Read More

Data Redaction: Safeguarding Sensitive Information in an Era of Data Sharing

Data redaction is a technique used to safeguard sensitive information in an era of data sharing. It involves selectively removing…
Read More

Building a Strong Foundation: Robust Metadata Repository (MDR) Framework for Automated Standard Compliant Data Mapping

Pharmaceutical and biotechnology companies operate within a constantly evolving regulatory landscape, where adherence to standards set by organizations like the…
Read More

Digitalization of Medical Writing: Balancing AI and Rule-based algorithms with Human Supervision in Medical Writing QC

What is Digitalization of Medical Writing?  The digitalization of medical writing refers to using digital technologies and tools to create,…
Read More

The Rise of Differential Privacy: Ensuring Privacy in the Age of Big Data

The rise of differential privacy is a significant development in the field of data privacy, especially in the age of…
Read More

Role of Intelligent Automation: How Intelligent Automation transforms the Clinical Study Document Review in Real Time

Clinical Study Reports play a critical role in assessing the safety and efficacy of new medical treatments. Review of these…
Read More

Automation on Clinical Study Report: Improve the Speed and Efficiency of document review. 

Clinical Study Report (CSRs) are critical documents that summarize the findings and results of clinical trials. These reports require a…
Read More

Digitalization of Quality Control in Medical Writing: Advantages Digitalization brings for the critical aspects of Quality Control

Quality control in medical writing is a critical aspect of ensuring the accuracy, clarity, and reliability of medical documents. It…
Read More

Contact Us​

Skip to content