7 Ways AI Can Improve Your Research Team’s Productivity

If you're involved in managing research compliance, you're probably all too familiar with the frustration of protocol approval delays. The process typically starts with submitting a protocol, followed by weeks of waiting for committee feedback. Once you get it, revisions are made, only to face another wait for final approval.

Does this sound familiar? 

For research teams, obtaining protocol approval from committees is a critical step. However, it often feels like a lengthy and drawn-out process, involving multiple rounds of revisions and delays. 

The timeline for IRB approval, for example, can range anywhere from 24 days for simple studies to up to three months for more complex ones. The delays typically result from incomplete applications or the need for additional clarification.

This is where AI can really make a difference. It can spot potential issues and offer real-time recommendations before you submit it for approval. 

This way, you can ensure that your protocol aligns more closely with regulatory requirements, thereby reducing the need for revisions. This means fewer delays, quicker approvals, and less back-and-forth communications which gives research teams more time to focus on their actual research. 

In this article, let’s look at how AI can streamline research compliance and help your team accelerate the approval process.

How AI is Integrated into Your Research Compliance Workflows

Here are a few interesting ways in which AI helps your research teams get protocol approvals faster and with fewer revisions.

1. AI-Powered Protocol Review Recommendations (IRB & IACUC)

AI can automatically review your research protocol and recommend changes based on the latest regulatory standards. Whether it's adjusting informed consent language, refining animal welfare practices, or ensuring the protocol aligns with ethical guidelines, AI helps identify potential issues before they are even submitted to the committee. 

Since protocols are complex documents, with information required in multiple sections, it’s easy for details to get out of sync. Let’s say the Principal Investigator (PI) lists medication dosage in one section. But mentions it incorrectly elsewhere. Now, AI can flag this inconsistency and prompt the PI to correct it before submission, which significantly reduces the chance of errors.

For example, imagine a clinical trial on a new cancer treatment. Instead of waiting weeks for the first round of feedback from the IRB, AI can instantly scan the protocol, identify areas where the consent form could be clearer, and suggest improvements right away, saving your team valuable time in the approval process. 

AI also analyzes informed consent language, ensuring that risks are explained in simple, clear terms that anyone can understand. If the language is too technical or lacks clarity, AI can flag it and suggest adjustments, making sure that the risks to participants and additional safeguards for vulnerable populations are properly communicated. 

This way, you can ensure that your protocol submission is already in better shape when it reaches the IRB committee, thereby reducing the number of revisions required and accelerating the process.

2. Literature Recommendations

AI can instantly recommend relevant literature for researchers and help them find similar studies and identify how their research differs, instantly. 

Instead of spending valuable time searching through countless studies, AI will pull up the most relevant research, highlighting key similarities or differences, so the Principal Investigator (PI) can take necessary actions to ensure the protocol is in alignment with the existing body of work. 

This not only saves time but also ensures that your research is positioned accurately within the current scientific landscape, reducing the risk of overlooked gaps or potential overlaps in the study.

3. Real-Time Regulations Alerts

While the regulatory framework for protocols tends to remain stable, AI ensures that when regulatory updates occur, your team is immediately alerted. 

Whether it's an update from the NIH, FDA, or other regulatory bodies, AI will notify the PI or administration about the changes, including which protocols require amendments. This proactive approach helps keep the protocol compliant and up-to-date, reducing the chances of submission delays or non-compliance due to overlooked regulatory shifts.

4. Knowledgebase for Instant Support Within the Application

AI-powered knowledge systems provide real-time assistance by answering any queries and guiding research teams through the protocol preparation process. This is one of the best ways to save time and reduce uncertainty.

Let's say your team is preparing a clinical trial protocol, and one of your new researchers is unsure if specific experimental procedures require additional safety precautions. Instead of waiting to receive feedback from research managers, they can simply ask the AI knowledge system directly. 

It scans the protocol details and instantly alerts them that specific procedures require updated risk mitigation measures, in accordance with the latest safety guidelines. The knowledge system even generates a checklist for the required documentation and suggests where to include these in the protocol. 

5. Predictive Analytics for Animal Health and Usage (LARS/LAHS)

AI predicts potential health risks of your animal subjects and usage issues based on historical data. This proactive approach helps research teams address issues early, ensuring better compliance with IACUC standards.

Suppose a research facility is running a vaccine trial using a specific breed of animal. Then, AI can help analyze the past health records of this breed and predict that certain environmental factors, such as temperature fluctuations, may lead to stress-related illnesses in some animals. 

With this information, the research team can adjust the animals' housing conditions before the issue arises, preventing delays and maintaining compliance with IACUC standards.

6. Risk Assessment of Protocols 

Once a protocol meets all necessary regulatory criteria, AI can assist by conducting a thorough risk assessment and streamlining the preparation for committee submission. While committees remain essential for final approval, AI plays a key role in reviewing protocols against established guidelines and flagging potential issues for attention.

Example: A research team at your institution submits a protocol for a study on genetically modified organisms. AI instantly cross-references the protocol with biosafety, ethical, and regulatory standards, providing an initial risk assessment. 

If the protocol meets all criteria, AI flags it for submission, ensuring that it's prepared for the committee’s final review. While the committee will still perform its in-depth evaluation, this AI-powered risk assessment helps minimize the chances of delays caused by overlooked compliance issues, ultimately speeding up the approval process.

7. Procedure Guidelines and Safety Protocol Generation 

AI can generate detailed, study-specific guidelines for research procedures when the Principal Investigator (PI) is creating the protocol, ensuring that all safety, ethical, and regulatory requirements are met. By automating the creation of these guidelines, AI helps researchers ensure that every aspect of the study adheres to best practices and is fully compliant with regulations.

Suppose your research lab is preparing for a study that involves animal surgeries to test a new cancer drug. In that case, AI scans the protocol and automatically generates a comprehensive set of safety guidelines for the procedure. This includes: 

• Anesthesia protocols
• Monitoring procedures during surgery
• Post-surgery care instructions for the animals

With these guidelines in place during the protocol creation phase, your team can be confident that all safety standards are being followed, reducing the risk of non-compliance and ensuring a smoother execution of the study.

Conclusion

The possibilities with AI in research compliance are endless. 

What we've covered so far are just a fraction of the many possibilities. For example, AI can help identify protocol deviations before they escalate into compliance issues. It can also monitor the progress of ongoing studies, flagging any discrepancies in real time.

Moreover, AI can analyze vast datasets from previous studies to predict potential risks, suggest optimizations, and even offer insights into participant recruitment strategies. Beyond compliance, AI can also enhance data integrity, improve participant engagement, and facilitate the management of third-party risk. 

The best part? All of these capabilities are integrated into our eProtocol module. From AI-powered protocol reviews to real-time compliance checks, our platform streamlines the entire process, ensuring smoother, faster approvals. 

Ready to take your research compliance to the next level? Share your Challenges with us and discover how eProtocol can transform your team's workflow.

A few benefits include:

• Faster Submissions: AI helps ensure protocols are compliant from the start, reducing revisions and accelerating the approval process.
• Fewer Delays: By catching issues early, AI minimizes the chances of your protocol being tabled or returned for further revisions.
• More Time for Innovation: With AI handling routine tasks, your team has more time to focus on designing and conducting research, rather than managing compliance.

Already using research compliance management tools? We can help integrate AI into your workflows with our deep expertise in both technology and industry. To get started, simply contact us, and one of our experts will be in touch with you shortly.
‍

Frequently Asked Questions