For some time now, patients have faced ever-complex therapy decisions. As scientists and healthcare professionals advance our understanding of diseases and develop cutting-edge treatments, patients and their caregivers often struggle to grasp what these therapies truly mean for them. They must consider whether the potential health outcomes outweigh the side effects, impact on quality of life, and financial costs. Many layers of efforts are placed by various industries to combat these barriers for patients. We aim to make discoveries and communications faster and easier in the research consulting field. This focus helps patients navigate their treatment options with greater clarity and confidence.
The role of research consulting organizations
The Research Consulting Organization (RCO) works with various pharmaceutical and biotech companies on Clinical Research (CR), Regulations, Medical Information (MI), Safety, and more. By partnering throughout the lifecycle of patient treatment, we identify Artificial Intelligence (AI)-enabled solutions that form the cornerstone driving innovation. AI efforts can provide faster answers to critical patient questions and reduce risks in decision-making. This is especially true in MI, which directly interacts with patients and their support team on treatment-related questions.
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Benefits and challenges of AI in healthcare
One of the most significant advantages of AI is harnessing and processing massive data, including learning and customizing per-user behavior. With this trait, adopting AI in this field can be challenging, as the priority is to stay impartial and protect patients’ private or sensitive information. One approach to integrating AI is enhancing internal workflow using AI, rather than introducing an AI-powered platform directly to patients. What if AI can help our subject matter experts find the information faster to progress the research and deliver answers to customers? How about assisting in crafting responses in a way patients can understand better, and enhancing the internal documentation process and quality monitoring to improve our services?
In Clinical Research, the specialists review massive clinical trial data for study design and execution. AI-powered tools, such as a chatbot for internal use, leverages the latest natural language processing (NLP) and machine learning algorithms to provide a seamless experience for teams navigating complex data queries, regardless of size or development stage. This can enhance confidence and overall success in clinical research, providing patients with opportunities for more comprehensive therapy options.
In Safety, the specialists check local literature for any adverse event reports to monitor the effectiveness and safety of the treatment products. This can be automated by a computer program that visits a list of websites, searches for product information in a specified time period, and captures the relevant information. This tool reduces the manual workload for safety specialists and provides the ability to scale up, accommodating new products or globalizing search efforts. The extensive search efforts can protect patients from therapies that could pose more significant risks.
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Enhancing information dissemination
In Medical Information, the specialists also go through hundreds to thousands of documents to respond to an inquiry. A keyword is imperative to find the right documents, sections, and paragraphs. With AI, the keyword search doesn’t stop at simple character matching in the system. The capability to process natural languages and learning power aid in searching synonyms, and frequently related terms, and correct misspellings. For example, the keyword ‘ingrdient’ can search for documents with not only the ‘ingredient’ but ‘component,’ ‘excipient,’ ‘formulation,’ ‘gluten,’ etc. This enables the specialists to review more relevant documents in the first search, reducing the need for multiple keyword variations and ultimately shortening the time required to deliver accurate and complete information to the customers.
Medical Information teams are composed of healthcare professionals like pharmacists, nurses, and life science professionals who are highly skilled in disseminating complex scientific or clinical information to any level of common parlance. AI can further enhance this process in several ways:
- AI can quickly summarize and reference extensive clinical documents, allowing specialists to review information more efficiently.
- AI can create a response draft based on the information the specialists extract from the reference documents to aid internal documentation and information delivery.
- AI can analyze the customer’s language choice during the conversation to suggest vocabulary the customer is more accustomed to understanding the information.
These capabilities collectively enhance the quality of the interaction and overall customer journey.
The generative AI also supports multiple service lines in creating and formatting various documents such as protocols, regulatory submissions, patient narratives, and custom responses based on the relevant dataset. AI significantly reduces the time and effort required by specialists for the initial draft, ensuring consistency in formatting and language for regulatory compliance and clear communication. The capability allows for handling a much larger volume of documents, enhancing the scalability of operations to include more products or countries.
We believe AI use in patient care must go alongside our teams who have been experts for decades in this field and can make final decisions when it comes to delivering the scientific and clinical exchange to our customers. This approach ensures the safety of our patients and communities before advancing further automation. With this, quality control is another area we aim to utilize AI in multiple service lines in our organization. As our specialists and AI tools collaborate, AI can identify customer intent, sentiment, accuracy, and completeness of the documents, possible adverse events, or product complaints, which are critical elements in fulfilling core functions. AI-supported quality control enables quicker performance feedback for our teams and enhances overall operations and performance.
Future direction and ethical considerations
The integration of AI in Research Consulting Organizations represents a significant advancement in healthcare communication and support. By leveraging the power of AI, we can offer timely and accurate information to our customers. This not only enhances the quality of care and patient satisfaction but also optimizes operational efficiency. As we continue to refine and expand AI capabilities, we remain committed to maintaining high standards of data privacy and ethical considerations. Embracing AI is not just about adopting new technology, it is about pioneering a future where innovation and compassion work hand in hand to improve health outcomes for patients.
Photo: metamorworks, Getty Images
Rajul Jain has over 19 years of international experience in Medical Information (MI), Pharmacovigilance (PV), Technology, and Program Management. With an extensive educational background including an MBA, Engineering degree, PMP, Medical Affairs Competency Certificate (ACMA), and various other healthcare certifications, she brings a wealth of knowledge to her roles. She is currently a President of Medical Information in ProPharma with responsibility for oversight and expansion of global contact center operations. Prior to this, she managed all of the MI programs for IQVIA and technology and automation solutions for MI/PV programs. Rajul is passionate about improving business processes and fostering innovative solutions in the healthcare and pharmaceutical industry.
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