• Written by Sonali Subhadarsini, Product Manager

In theory, agentic AI workflows in pharmaceuticals should streamline processes and reduce the administrative burden on staff, but in practice, these systems often struggle to cope with the unique demands of a highly regulated industry, where change control overhead, batch record review, and deviation investigation time can be crippling, and even the most seemingly straightforward tasks, such as a shift supervisor checking the maintenance log, can become mired in bureaucracy.

Pharmaceuticals' unique challenges

The pharmaceutical industry is subject to strict documentation rules and validated processes, which can make it difficult to implement agentic AI workflows, as even small changes to a process can require extensive documentation and approval, and the review of batch records, for example, is a time-consuming task that requires a high degree of accuracy, and while an AI system can assist with this task, it is not a replacement for human oversight, as the category manager will still need to verify the results and ensure that they are accurate and compliant with regulatory requirements.

Furthermore, deviation investigation time can be a significant bottleneck in the implementation of agentic AI workflows, as any deviation from the expected outcome of a process must be thoroughly investigated and documented, which can be a time-consuming and labor-intensive process, and one that requires a high degree of expertise and attention to detail, as the investigation must be conducted in accordance with strict regulatory guidelines, and the results must be thoroughly documented and approved.

Defining an agent

An agentic AI workflow is distinct from a chatbot or other simple AI system, as it is capable of taking multi-step action, using a variety of tools and systems, and adapting to changing circumstances, and it is this ability to use tools and adapt to changing circumstances that sets an agent apart from a simple chatbot, and allows it to perform complex tasks, such as managing inventory or scheduling maintenance, and while a chatbot may be able to answer questions or provide basic support, an agent can take action and make decisions, and it is this ability to take action and make decisions that makes an agent so valuable in a pharmaceutical setting.

The key characteristics of an agent are its ability to use tools, its possession of state, and its ability to pursue a goal, and it is these characteristics that allow an agent to perform complex tasks and adapt to changing circumstances, and while a simple chatbot may be able to answer questions or provide basic support, an agent can take action and make decisions, and it is this ability to take action and make decisions that makes an agent so valuable in a pharmaceutical setting, where the ability to adapt to changing circumstances and make decisions quickly is critical.

Human approval and oversight

One of the most common mistakes made when implementing agentic AI workflows is to remove the human approval step too early, as while an agent can perform complex tasks and make decisions, it is still important to have a human oversee the process and verify the results, and this is particularly true in a pharmaceutical setting, where the stakes are high and the consequences of error can be severe, and while an agent can assist with tasks such as batch record review, it is still important to have a human verify the results and ensure that they are accurate and compliant with regulatory requirements.

Most people get wrong the idea that an agent can replace human oversight entirely, and this is a mistake, as human oversight is still essential in a pharmaceutical setting, where the ability to adapt to changing circumstances and make decisions quickly is critical, and while an agent can assist with tasks such as scheduling maintenance or managing inventory, it is still important to have a human oversee the process and verify the results, and for more information on how to implement agentic AI workflows effectively, you can visit our website at AsscherAi.

Failing differently

An agent fails differently from a model, as an agent's failure is often more subtle and may not be immediately apparent, and it is this subtlety that makes it so important to log and monitor an agent's actions and decisions, and to have a human oversee the process and verify the results, and this is particularly true in a pharmaceutical setting, where the stakes are high and the consequences of error can be severe, and while an agent can assist with tasks such as batch record review, it is still important to have a human verify the results and ensure that they are accurate and compliant with regulatory requirements.

In order to effectively log and monitor an agent's actions and decisions, it is necessary to have a clear understanding of the agent's goals and objectives, as well as the tools and systems it uses, and it is also necessary to have a system in place for tracking and verifying the agent's actions and decisions, and for more information on how to implement this type of system, you can contact us at AsscherAi.

Limitations and wrong choices

Agentic AI workflows are not a solution for every problem, and there are certain situations where they are not the best choice, such as in situations where the process is highly variable or unpredictable, or where the stakes are extremely high, and in these situations, it may be better to use a different type of system or approach, and it is also important to consider the potential risks and limitations of agentic AI workflows, such as the potential for bias or error, and to take steps to mitigate these risks, such as by implementing robust testing and validation procedures.

Furthermore, agentic AI workflows may not be the best choice for situations where the primary goal is to answer a single question or provide basic support, as in these situations, a simple chatbot or other type of system may be more effective, and it is also important to consider the potential costs and benefits of implementing an agentic AI workflow, and to carefully evaluate whether the benefits outweigh the costs, and to consider alternative approaches or solutions.