AI Prompting Tips for Life Science Professionals to Get the Best Output From AI Writing and Research Tools

Life sciences professionals face some of the most demanding writing and research tasks, from clinical trial summaries and regulatory documents to academic publications. AI tools like MACg are transforming these workflows, but getting optimal results depends heavily on how you structure your instructions. Leaving AI to guess your intent based on its vast knowledge will get you some answers. However, guiding the tool with specific instructions is more likely to produce the outcome that you desire.

Mastering effective prompting can save time, boost accuracy, and streamline your workflow. With practice and experimentation, you will discover the immense value of AI platforms and join the millions of people who increased their productivity by severalfold.

General Prompting Tips

Utilize Natural Language Prompts

Why: MACg understands conversational language, making prompting intuitive.
How: Write as if you're speaking to a research assistant.
Example: "I'm drafting a white paper on drug delivery systems. Can you provide a summary of recent innovations in this field?”

Be Specific and Goal-Oriented

Why: MACg excels when it understands your query's exact purpose.
How: Instead of general prompts like "summarize this article," specify your needs.
Example: "Summarize this article, focusing on clinical trial outcomes for patients with Type 2 diabetes."

Use Contextual Keywords

Why: Relevant terms ensure MACg delivers results tailored to your field.
How: Incorporate subject-specific keywords.
Example: "Find recent studies on immunotherapy for melanoma published after 2020.”
Tip: Use terms like “phase 2 or 3 studies” "systematic review," "meta-analysis," or "case study" to refine searches.

Start Broad, Then Refine

Why: Broad prompts generate a wider pool of results, which can be refined as needed.
How: Begin with a general query, then use follow-up questions to drill down.
Example: "What are the latest treatments for rheumatoid arthritis?" Follow with, "Summarize recent studies comparing biologics to nonbiologic therapies.”

Leverage MACg's Summarization Power

Why: Summarization saves time by distilling key findings from lengthy documents.
How: Request focused summaries to fit your workflow.
Example: "Summarize this article in plain language for a non-scientific audience.”Example: "Highlight this clinical trial's methodology and primary conclusions.”

Ask for Citation Support

Why: MACg simplifies reference management by organizing and formatting citations automatically in the AMA format.
How: Include citation-related queries in your prompt.
Example: “Create a reference list from the attached documents using the title of each document as anchor text”.

Specify Content Type or Format

Why: Tailoring prompts to the output format ensures MACg delivers precisely what you need.
How: Indicate the desired document type.
Example: "Draft an outline for a policy brief on antimicrobial resistance.”
Example: "Generate bullet points summarizing key findings for a slide presentation.”

Refine Results with Follow-Up Prompts

Why: MACg adapts to follow-up queries, allowing for iterative refinement.
How: Build on previous responses.
Example: After receiving a summary, ask: "Can you add details about sample size and study duration?”

Use Date Ranges and Filters

Why: Filtering by date or study type ensures MACg focuses on the most relevant information.
How: Include timeframes or parameters in your prompts.
Example: "Find articles on gene therapy published in the last five years.”

Experiment with Creative Applications

Why: MACg is flexible and can assist with brainstorming, outlining, or localizing content.
How: Try prompts like: "Help me localize this abstract for a French-speaking audience.” "Brainstorm 5 potential research angles for a study on AI in diagnostics."

Advanced Prompting Tips

Combine Research and Writing Tasks

Why: MACg can multitask, combining insights and drafting in one workflow.
How: Include research and writing objectives in a single prompt.
Example: "Find studies on wearable health tech and draft a 500-word summary for a blog post."

Optimize for Collaboration

Why: Teams using MACg can streamline feedback and revisions.
How: Request content drafts with collaborative elements.
Example: "Generate a draft policy proposal on vaccine equity with placeholders for team input."

Test Prompt Variations

Why: Slight changes in phrasing can yield different results, especially for nuanced queries.
How: Experiment with wording.
Example: "Compare the efficacy of mRNA vaccines to traditional vaccines" vs. "What studies compare mRNA vaccines to traditional ones?"

Use MACg for Localization and Audience Adaptation

Why: MACg's localization capabilities allow you to adapt content for specific audiences.
How: Tailor prompts for target demographics.
Example: "Simplify this scientific abstract for a patient education brochure."

Save Time with Pre-Built Prompts

Why: Having a set of go-to prompts can accelerate repetitive tasks.
How: Create a library of reusable prompts for common workflows.
Example: "Find recent research on [X] and generate a summary with key points highlighted."

Chain of Thought Prompting Tips for MACg Users

What is Chain of Thought Prompting?

Chain of Thought (CoT) prompting is an advanced technique that breaks complex tasks into smaller, logical steps. This approach allows users to guide MACg’s outputs systematically, ensuring precision and clarity—key requirements for life sciences content.

Start with the Big Picture, Then Narrow Down

Why: Life sciences tasks often involve multifaceted problems that benefit from a step-by-step breakdown.
How: Begin with a broad query and ask MACg to refine the results in stages:
Example: “Summarize recent articles about immunotherapy for lung cancer. Then highlight studies focusing on early-stage patients.”
Tip: Follow up with requests for specific insights (e.g., “What methods were used in the attached studies?”).

Use Step-by-Step Summarization for Complex Studies or Multiple Studies

Why: Scientific literature often requires careful extraction of key details.
How: Ask MACg to summarize one aspect at a time for greater clarity and detail.
Example: “First, summarize the methodology of this clinical trial. Next, describe the primary outcomes and limitations.”
Tip: Ask MACg to use a similar approach for the other attached studies. Use the document editor to compile your output or ask MACg. Use MACg’s citation tool to create well-referenced content.

Break Tasks into Logical Subsections

Why: Dividing tasks into smaller steps ensures every part of a project is addressed comprehensively.
How: Request individual components first, then combine them:
Example: “List common regulatory challenges in clinical trials. Then suggest strategies for overcoming each challenge.” “Draw a chart that shows the patient flow.” "Then, create a table of inclusion and exclusion criteria."
Benefit: This ensures your final output is complete and logically structured.

Request Analysis of Trends or Patterns

Why: Identifying patterns across studies is critical in life sciences but often time-consuming.
How: Direct MACg to analyze trends and explain their implications:
Example: “What trends are evident in recent publications on antimicrobial resistance? How do these trends compare to findings from five years ago?”
Tip: Use this method to generate content for white papers, reports, or slide decks.

Solve Problems in Sequential Steps

Why: Addressing complex issues requires a logical progression of ideas.
How: Use CoT prompting to guide MACg through problem-solving:
Example: “Outline the barriers to AI adoption in clinical trials. Then provide actionable recommendations based on recent studies.”
Benefit: This approach is useful for crafting persuasive policy briefs or research proposals.

Ask MACg to write prompts

If AI can write code and analyze complex documents it should be able to write prompts! Yes, it can.

Describe, what you are trying to write or create and ask MACg to write a prompt to accomplish this task. Another approach is to attach a document as an example, then ask MACg to analyze it and write a prompt for creating a similar document. You can edit the prompt and add any missing details. Test the prompt, edit it further if needed, and save it for future use.

Additional Resources

OpenAI Platform. Prompt engineering. Enhance results with prompt engineering strategies.

Meskó B. Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial. J Med Internet Res. 2023 Oct 4;25:e50638. doi: 10.2196/50638. PMID: 37792434; PMCID: PMC10585440.

Bell, Tavish. Utah Tech Library. AI Prompt Engineering in Health Sciences. Understanding Prompt Engineering. Be the Human in the Loop.  2024 Sep 3.

Shah K, Xu AY, Sharma Y, Daher M, McDonald C, Diebo BG, Daniels AH. Large Language Model Prompting Techniques for Advancement in Clinical Medicine. J Clin Med. 2024 Aug 28;13(17):5101. doi: 10.3390/jcm13175101. PMID: 39274316; PMCID: PMC11396764.