Maximize the full potential of AI in clinical research—without risking security, compliance, or ethics.

The use of AI tools such as ChatGPT is rapidly emerging in clinical research. From drafting reports and summarizing data to generating insights from complex datasets, these tools are transforming the way work is done. However, with this increased reliance on AI comes a critical need for well-defined policies that guide their use. Without clear guidelines, the risks—ranging from data breaches, the release of confidential information, as well as compliance failures—can outweigh the benefits, exposing any organization to new liabilities.

For companies conducting clinical research, establishing a robust AI policy is not just about mitigating risks; it's about ensuring that AI tools are used efficiently and ethically. In this post, we offer best practices for building an AI policy that meets the unique needs of clinical research, ensuring security, compliance, and operational excellence.

Why AI Policies Are Essential for Clinical Research and BioPharma Companies

Clinical research operates in a highly regulated environment, where data privacy, patient confidentiality, and intellectual property are of significant importance. Biopharma companies, in particular, work with sensitive information, such as clinical trial data, patient health records, patient identifiable information, and proprietary research. Introducing AI tools into these components without proper guidelines and oversight could result in unintended consequences, including data breaches or non-compliance with industry regulations.

A comprehensive AI policy helps to ensure that tools like ChatGPT are used responsibly. By clearly defining the boundaries of AI usage, companies can reduce risks, safeguard data, and ensure compliance with both industry standards and legal requirements. In addition, a well-implemented AI policy positions your organization as forward-thinking, ready to leverage the benefits of AI while mitigating potential pitfalls.

Common Questions When Setting AI Policies

When our clients approach us about AI policy development, several key questions consistently arise.

- Who is responsible for creating the AI policy? Typically, developing an AI policy is a collaborative effort. IT, Legal, and HR departments all have a stake in its development. IT ensures that the policy addresses data security, Legal covers compliance, and risk management, and HR manages the human aspect—training, communication, and enforcement.

- How should the AI policy be communicated? Clear & frequent communication is critical. The policy should be introduced through training sessions, webinars, and internal communications that explain not just what the policy is, but why it exists, what it is intended to solve, and how it protects both the company and its employees. Education ensures that employees understand the rationale behind the guidelines and the consequences of non-compliance. The policy should also be periodically re-communicated.

- Who enforces the AI policy? Policy enforcement typically falls to IT and HR, with oversight from Legal. IT may monitor AI usage for compliance, while HR ensures that all employees are trained and held accountable. Regular audits and assessments can help ensure that the policy is being followed, and any breaches are dealt with swiftly

Risks of Not Implementing AI Policies

Failing to implement a solid AI policy can lead to a range of serious risks:

- Data Leaks and Security Threats: One of the biggest concerns with AI tools is their handling and crowd-sourcing of sensitive information. AI platforms, especially third-party tools, may store or process data externally, share confidential data in public domains freely, thereby increasing the risk of data exposure & leaks. This is especially concerning in clinical research, where patient confidentiality and proprietary data must be strictly protected.

- Legal and Compliance Issues: Without a clear policy, companies risk potential non-compliances to regulations such as GDPR, HIPAA, or clinical trial data protection laws. This can result in costly lawsuits, regulatory penalties, and damage to the company’s reputation. Moreover, AI tools themselves may not be compliant with certain regulations if used improperly.

- Ethical Concerns: AI has the potential to introduce bias into decision-making processes or data analysis. Without proper oversight and technical/procedural guidelines, these biases can affect clinical outcomes, research validity, and even patient safety. Ensuring that AI tools are used as a supplement to human expertise, rather than a replacement, is key to maintaining ethical standards in clinical research.

Best Practices for AI Policy Development

Creating an effective AI policy requires a structured approach. Here are the best practices we recommend:

- Identify Key Stakeholders: Include representatives from IT, Legal, HR, and other relevant business units/departments. Bringing together a diverse group ensures that all aspects of AI usage—security, compliance, ethics, and practicality—are considered in the policy.

- Set Clear Parameters for AI Usage: Define exactly how and which AI tools are to be used (and not to be used) in your organization. This includes specifying which tasks can be automated, how data should be handled, and the level of human oversight required. Be explicit about prohibited uses to prevent misuse of AI tools.

- Develop a Training Program: Training & Awareness is essential to ensure employees understand the policy and know how to use AI tools responsibly. Training should cover not only the practical uses of AI usage but also the critical importance of data security, regulatory compliance, and ethical considerations.

- Establish Monitoring and Audit Procedures: Regular monitoring ensures that the AI policy is being followed. Conduct periodic audits to identify any policy breaches or areas where the policy might need updating. Monitoring should be done in a way that balances oversight with trust in employees, maintaining a healthy work environment.

Conclusion

As AI tools like ChatGPT become more prevalent in clinical research, having a well-defined AI policy is essential for ensuring security, compliance, and efficiency. Organizations that proactively establish these policies will not only protect themselves from legal and ethical risks but also position themselves to fully leverage the power of AI in their clinical research projects.

By taking the time to create a thoughtful AI policy—one that is crafted collaboratively and communicated, carefully enforced, and regularly updated—biopharma companies can confidently embrace AI as a tool for innovation and growth.

The Authors

 Sean Diwan, Chief Information & Technology Officer

Adrea Widule, Senior Director, Business Development