Unlocking the Potential of AI in Life Sciences

Embracing AI for Data Extraction, Writing, and Standardization

Written by Lisa Helmonds, VP Quality & Operations and Sumaiya Reza, VP, Business Development

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AI is transforming how we manage and analyze data. As adoption increases, we must not be afraid to embrace it, since it is here to stay.  It's vital for industry professionals to get accustomed to using AI tools, including use in tasks like data extraction and automated writing. With increased use, will come increased comfort in leveraging the technology further in the near future.  The benefits of these tools are becoming evident across multiple areas. Industry experts emphasized the importance of data clean-up and standardization for use.

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Data extraction refers to the process of retrieving specific data or information from various sources, such as databases, documents, websites, or other structured or unstructured formats. The extracted data is then typically used for analysis, reporting, or integration into other systems. It's a key step in data processing pipelines like ETL (Extract, Transform, Load) workflows, frequently used in fields like business intelligence, data analytics, and machine learning. The process often involves:

• Identifying the target data.
• Extracting it without altering the source.
• Converting it into a usable format, if necessary.

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Automated writing refers to the use of artificial intelligence or software tools to generate written content with minimal human involvement. This can range from creating articles, reports, and emails to crafting creative pieces like poems or scripts.

The process often relies on natural language processing (NLP) algorithms and machine learning models that understand language patterns and context. It enables efficiency and scalability in tasks that require substantial written output. Automated writing is widely used for:

• Generating marketing content like blog posts or ad copy. (And yes, we used it to aid in this discussion).
• Summarizing documents or articles.
• Drafting repetitive communications (e.g., customer support emails).
• Assisting with brainstorming and generating ideas.

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It is important to keep in mind that this technology is a tool to get you started in writing your documents.  You must put your own style, knowledge and specific examples to truly make it unique, and to ensure its relevance and accuracy to the specific application.  

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Data Standardization is the process of converting data into a consistent format to ensure uniformity and compatibility across different systems, applications, or datasets. It plays a vital role in preparing data for analysis, integration, or sharing by eliminating discrepancies and inconsistencies.  It includes:

• Formatting: Ensuring all data follows a uniform format, such as date formats (e.g., MM/DD/YYYY) or units of measurement (e.g., meters vs. feet).
• Consistency: Harmonizing naming conventions, such as using "California" instead of mixing "CA" or "Calif."
• Data Cleaning: Removing errors, duplicates, and irrelevant information.
• Normalization: Adjusting numerical data to a common scale without distorting its distribution, such as scaling values between 0 and 1.

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AI in Action: Areas of Immediate Application in the Life Sciences Industry

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Within the regulatory realm, the development of Fast Healthcare Interoperability Resources (FHIR) standards may be a focal point for both regulatory agencies and the industry. This standard is a set of rules and specifications for the secure exchange of electronic health care data. It is designed to be flexible and adaptable, so that it can be used in a wide range of settings and with different health care information systems. The standard describes data formats and elements (known as "resources") and an application programming interface (API), (not to be confused with Active Pharmaceutical Ingredient) for exchanging electronic health records (EHR). The industry has already started harnessing AI in several areas including:

• Regulatory Submissions - to compile and write submissions (e.g., Quality Overall Summary (QOS), summarizing all Module 3 components of a filing package, etc.).
• Regulatory Agency Responses - to help support the generation of responses to agency questions and evaluate submissions in advance of what might get flagged.

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In supply chain management, AI is used to:

• Source, Contract, and Manage Suppliers to collect and analyze market insights and efficiency gains in supplier management processes leading to a reduction of data gathering, contract writing and semi-automated negotiations.
• Optimize inventory management.

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In pharmaceutical development, AI is used for:

• Literature Review to screen and summarize information for new molecules screening (docking into a protein or target for drug discovery), processes, or analytical characterization opportunities which can increase speed to the clinic.
• Automated Scientific Report Writing for process development, analytical development, validation summaries, etc.

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In life science manufacturing, AI is used for:

• Equipment Reliability to send alerts and reduce downtime.
• Monitoring Process Performance - to provide early warnings on processes that are not in control and build on existing measurement to create a model, and much more.

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Balancing Innovation and Risk Management

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While AI's potential is enormous, it's important to maintain a few levels of separation between the active pharmaceutical ingredient (API) and patient-impacting processes. Keeping AI applications appropriately removed from direct patient outcomes helps to mitigate regulatory risks and complexities.

Specific points that are important to look out for when using AI applications are:

• Data considerations (integrity/security, power usage, storage).
  • Costs and limitations for increased power usage & data storage should be assessed before using AI for confidential information.
  • These applications can generate hallucinations (e.g., make up data AND/OR references AND/OR provide out-of-date information, etc.).
  • NEVER upload confidential information, it becomes part of the overall dataset that others may be able to access and utilize.
  • For your confidential information, you should implement a company-specific Generative Pre-trained Transformer (GPT) so it can be trained on your specific information. GPT stands for Generative Pre-trained Transformer. It is a type of artificial intelligence model designed to generate human-like text and here's how it works:
    • Generative: It creates new content, such as sentences, paragraphs, or even entire articles, based on the input it receives.
    • Pre-trained: The model is trained on vast amounts of text data before being used, enabling it to understand language patterns, context, and various topics.
    • Transformer: This refers to the specific architecture of the model. Transformers are advanced neural networks designed to handle sequences of data, making them particularly effective for tasks involving language processing.
• Be sure to choose the AI application that best suits your needs.  Consider a fee-based application if needed.  
• Always double check references.
• Data needs to be cleaned up and standardized for use with the AI tools.

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AI in Action: Areas of Immediate Application in Your Personal Life

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From a personal perspective, you can use AI to help with many of your routine tasks. AI has an impressive range of uses that can simplify life, spark creativity, and enhance productivity! Here are some ways you can use AI in your daily routine:

• Personal Organization: AI assistants like scheduling tools or reminder apps can manage calendars, set reminders, and help you stay on top of tasks.
• Health & Wellness: Many apps use AI to track fitness goals, provide workout recommendations, or even guide meditation and mindfulness sessions. We already use it with our smart watches, phones, etc.
• Financial Management: AI tools can analyze spending habits, set budgets, and even offer investment insights.  Our banks do this now.
• Entertainment: AI powers personalized recommendations on streaming services, music apps, or gaming platforms, tailoring content to your preferences. They do this now just by analyzing what you watch or listen to and make suggestions.
• Home Automation: Smart home devices use AI to adjust lighting, temperature, and security settings based on your habits and preferences. Does Ring, Nest, etc. ring a bell?
• Travel Planning: AI can recommend destinations, provide real-time updates on flights, or create personalized itineraries. Now we have our own personal travel agent.
• Creative Assistance: From writing stories or lyrics to generating unique art, AI tools can help with creative projects and ideas.
• Learning & Skill Development: AI can serve as a tutor for academics, language learning, or even hobbies like cooking or playing an instrument.

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AI is an exciting tool and when used correctly it can provide increased efficiencies and improve time to market for life-saving products, as well as helping you organize your personal life. As with everything in the life sciences industry, you must use a risk-based approach to implementing AI to ensure proper use of this technology to ensure success.  Whether you're looking for efficiency, exploration, or a creative companion, AI has something to offer in every corner of your life.

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The future is here now and it’s time to embrace this new technology. The more we learn about it, the more productive we will be with using these AI applications.  And, remember, while AI tools can give a great starting point, you still must add your personal style, wisdom, and knowledge to complete your writing content.

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AVS Life Sciences works with many talented AI professionals that can help you learn more about how to effectively use AI to improve your work/life balance.

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Let us know how we can help you as our industry moves forward with the implementation of new concepts and innovation. For more information, please reach out to us at info@avslifesciences.com.

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