Artificial Intelligence (AI) has been a fixture in technology for decades, evolving from machine learning to the cutting-edge capability of Generative AI, deep-learning models that create original content. This technology is set to revolutionise pharmacy practice, offering innovative solutions to improve efficiency and enhance patient care.
If you’re a pharmacy professional, understanding and responsibly adopting this powerful tool is crucial. After reading this, you’ll be equipped to understand Generative AI, use it legally and ethically and integrate it into your daily work.
What is generative AI and why does it matter to pharmacists?
AI, in its broader sense, is already active in healthcare, from improving breast cancer screening detection rates to predicting patient falls. In pharmacy specifically, AI systems are already streamlining operations, such as automated dispensing, stock forecasting and prescription verification. Generative AI takes this a step further.
Generative AI models, often Large Language Models (LLMs) trained on vast datasets of text, can instantly analyse data, identify patterns and generate original content in response to a query. Think of it as a sophisticated, creative research assistant.
In the pharmacy setting, this translates to:
- Expediting drug discovery: Analysing massive datasets to identify drug candidates, predict efficacy and safety and reduce costs.
- Streamlining daily tasks: Automating time-consuming administrative work, allowing pharmacists to focus on patient-facing care.
Practical applications in your day-to-day
Generative AI can act as a powerful «jumping-off point» and efficiency booster for common tasks:
| Application | Generative AI Use Case |
| Communication | Drafting professional emails, creating tailored patient communications or refining existing text for a specific tone (e.g., authoritative or friendly). |
| Time-saving summaries | Uploading a meeting transcript or a lengthy preparatory document to instantly generate a one-page summary, key discussion points and action items. |
| Training & strategy | Creating outlines for training sessions on new clinical guidelines (like NICE asthma guidance) or drafting initial job descriptions and strategic plans. |
| Research & data | Assisting with literature reviews, interacting with research papers to extract data and using software to speed up data analysis for insights and predictive analytics. |
| Automation | Automating patient communication for medication reminders and condition-related information/resources. |
The secret to getting the best out of these tools? Prompt Engineering. By following a structured approach, defining the Context, clearly stating the Task (using action verbs), giving the AI a Persona (e.g., «You are a pharmacist»), including an Example for structure and specifying the desired Format and Tone, you can significantly refine the quality and relevance of the output.
Here are some examples of how the format above can be used:
- You are a pharmacy owner (persona) and you want to launch a new travel health and vaccination clinic in your pharmacy (context). Ensure all staff are correctly trained on the new service protocols (goal). Create a training module outline for the new travel health clinic (task). Include sections on legal requirements, consent procedures, vaccine storage and the patient consultation process (example/format/tone).
- You are a superintendent pharmacist (persona). A new member of the dispensing team is struggling to meet the required speed and accuracy targets (context). Provide constructive feedback and a clear improvement plan (goal). Draft an email to the team member setting out performance expectations and an action plan for improvement (task). Use a professional yet supportive tone, referencing specific, measurable targets and offering dedicated training support (example/format/tone).
The principles of prompt engineering apply to both text and image generation, though image prompts require language related to photography. For guidance, a quick reference are the Midjourney guide, Gemini guide, Microsoft Copilot guide, while the DALL-E 2 prompt book offers extensive style information.
Legal and ethical imperatives for AI use
With great power comes great responsibility. The rapid adoption of Generative AI requires pharmacists to navigate a new ethical and legal landscape. The Royal Pharmaceutical Society (RPS) is supportive of AI, but emphasises its responsible and effective use.
Though the General Pharmaceutical Council (GPhC) lacks explicit AI guidance, existing standards require pharmacy professionals to:
- Ensure AI supports person-centred care.
- Maintain continuous professional development on AI.
- Guarantee AI systems meet data protection and patient confidentiality rules.
- Use professional judgement and clinical experience to interpret AI outputs and make final decisions.
Key considerations for ethical and legal practice:
- Patient data is sacred: You must never input patient-identifiable data, sensitive business information, or colleagues’ names into free-access, third-party AI tools, as this data is often stored and used for further model training, risking breaches of patient confidentiality.
- Verify, Verify, Verify: Generative AI can suffer from «hallucinations», generating convincing but factually incorrect or biased information. Professional judgement remains the final safeguard. Always cross-reference clinical information with trusted, evidence-based resources.
- Accountability is yours: The responsibility for the legal and ethical use of the AI and the verification of its outputs, lies entirely with the user: the pharmacist. Use your Continuous Professional Development (CPD) to stay informed on AI and its responsible integration.
- Transparency with patients: The General Pharmaceutical Council (GPhC) standards still apply. Ensure that any use of AI supports person-centred care and be transparent with patients about its role in their care.
Best practice checklist
As AI continues to evolve at a breakneck pace, adopting a proactive stance is vital.
- Check for a policy: See if your workplace has an official AI use policy. If not, advocate for one to set clear guidelines.
- Protect confidentiality: Assume any information entered into a free-access tool is no longer private.
- Validate clinical outputs: Treat all AI-generated clinical information as unverified until confirmed by a reliable source.
- Master the prompt: Invest time in learning prompt engineering to make your AI interactions more efficient and effective.
Generative AI is a game-changer, a tool that, when wielded with professional integrity and informed caution, can unlock immense efficiency gains and allow pharmacists to enhance their critical, patient-facing roles. The future of pharmacy is already being written and it’s time to start prompting.