The pharmaceutical industry is on the brink of a major leap forward, with technology paving the way to tackle long-standing challenges more effectively. From the cumbersome clinical trial recruitment processes to the lack of tailored patient education and support, we can now count on Large Language Models (LLMs) as a new tool to significantly impact treatment outcomes and the speed at which new therapies are developed and delivered. Large Language Models present an unprecedented opportunity to address these bottlenecks, offering solutions that promise to personalize and summarize information, streamline operations, and deal with the translation between natural language and technical terms.
Here are 5 ideas our team has brainstormed about how LLMs could create improvements by easing brand-stakeholder interactions:
Customized Patient Education
LLMs can generate personalized educational materials for patients, explaining medication uses, side effects, and treatment plans understandably. They can also provide extra knowledge about the patient’s clinical details and suggest visiting a professional when needed. This adaptive approach improves patient understanding and adherence to treatment regimes, fostering better health outcomes.
Enhanced Patient Support Services
Using chatbots powered by LLMs, pharmaceutical companies can offer round-the-clock patient support. These chatbots can provide instant answers to questions about medication usage, side effects, and other treatment-related inquiries, improving patient experience and support in the channel they prefer. In the process, they can collect missing information, execute surveys, and develop a more significant relationship with the company.
Facilitated Healthcare Professional Training
LLMs can develop dynamic, up-to-date training materials for healthcare professionals on the latest pharmaceutical products and medical research findings. They can also help with busy schedules and ease onboarding onto new topics. This ensures that providers are well-informed through rich summaries and can offer the best possible care to their patients.
Enhanced Healthcare Professional Relationships
Chatbots can be of help with HPs too. Pharma companies can facilitate personalized communication strategies for different physicians, ensuring a 2-way dialog where the company receives feedback about their products and their marketing activities while having an open channel for personalized communication. Different kinds of professionals can receive the needed information in the formats they prefer, and they can even start simple processes (like an event subscription) from a simple chat channel they are familiar with.
Streamlining Clinical Trials
A collateral effect of these stronger relationships with patients and health professionals is that LLMs will not only have enriched information about their products’ usage but also the ability to build trust and be more present in their minds can pave the way to improve the recruitment process for clinical trials. After all, It feels much more natural to receive an invitation to participate in a Clinical Trial in the context of a chat where you’ve been talking about related topics. This can accelerate the trial setup and enhance the quality and reliability of clinical research.
The risks
While LLMs hold transformative potential for smoothing interactions within the healthcare and pharmaceutical sectors, their application is not without risks. Privacy and data security are primordial, given the sensitivity of health information. Conversations that involve sensitive patient information need to happen in an encrypted way, and extracted data needs to be anonymized before getting to the company’s servers. There’s also the challenge of ensuring the algorithms don’t perpetuate bias or inaccuracies, which could mislead patient education or clinical trial recruitment. Also, as always happens with LLMs, an over-reliance on technology risks diminishing the essential human touch. Balancing these concerns with the benefits of LLMs is essential for their successful integration, and you can do it by monitoring the system and adding a human-led quality review process.
Conclusions
There are a lot of other activities in Pharma Companies where LLMs are being tried like drug discovery and regulatory affairs, but we wanted to focus on the layers where there is interaction with the market because the most basic ways of incorporating LLMs (personalized summaries and chatbots) fit perfectly here. They can help increase product acceptance by healthcare professionals and patients, thus helping with commercial success and ROI. This good set of basic examples has the intention to spark curiosity. We are available to help you think in more detail how this could be adapted to your particular case! Reach out to us at hello@arionkoder.com for a free consultation.