How AI-enabled technology benefits biopharma customer service

How AI-enabled technology benefits biopharma customer service

By Simon Johns

Medical information teams are increasingly embracing artificial intelligence (AI), blending the services of human experts with those of AI agents. These AI-driven systems optimize and support organizations, enabling them to cut costs, increase access, and improve healthcare provider (HCP) and patient engagement. This trend is seeing a significant uptake in the biopharma environment. One survey showed 79% of companies targeting HCPs were currently either using or testing a combination of AI agents and human experts in their customer service. Why is this AI technology becoming so widely implemented, and what are the benefits?

Reasons to embrace AI in biopharma

Healthcare providers need round-the-clock access to medical information (MI) support. While they have limited time to spend on research, they still require up-to-date, accurate intelligence about treatments and drugs.

The COVID-19 pandemic shone a spotlight on the industry’s critical need to be able to scale product support rapidly to address unexpected high demand. The combination of the pandemic and healthcare’s increased digitization led to reduced face time with biopharma sales representatives, leaving some HCPs lacking support. HCPs want self-serve, omnichannel assistance with access to interactive, bite-sized, and easy-to-consume information, and they want it now.

Meanwhile, human labor-driven support is expensive and carries the risk of inconsistent information and poor customer service. A solution exists in the form of conversational AI technologies, using intelligent agents that can parse medical information in multiple languages and formats such as text, voice, mobile and web chat.

How AI-enabled agent technology works

Conversational AI agents can be deployed rapidly, enabling biopharma companies to address common questions quickly and easily. This frees human MI experts to engage with HCPs and patients needing more complex information and attention.

Machine learning algorithms use massive databases to train the AI agents to produce appropriate responses to most questions. This training allows them to identify adverse events or indications of product issues. The technology also uses natural language processing tools to automatically translate written and audio content for review. AI agents can even interpret non-structured narrative data where consumers use colloquial phrases like “sniffly” to describe congestion.

Conversational AI agents are not intended to take over all medical information services or to replace MI professionals since continued human-to-human communication support is likely to be required for many years to come. Instead, they are designed to increase human experts’ speed, efficiency, and utilization. By doing so, companies can accommodate the growing number of HCPs, patients and consumers who favor digital interactions.

During an initial product launch, biopharma companies might prefer to depend on human customer service agents. This is especially relevant for novel products where potential questions are not yet known and little content is available for training machine learning. However, as the algorithms continue to learn by monitoring live agent responses, conversational AI can take over a larger percentage of the inquiries.

AI agents can also be deployed as direct response tools on websites or as an alternative option for customers waiting on hold during calls or during out-of-hours. Additionally, AI agents can provide the first level of contact and address routine customer inquiries, while forwarding more complex questions to human MI experts. This hybrid blend of human and AI agents balances quality service with accurate, cost-effective customer responses.

Benefits of AI-enabled tools in customer service optimization

Delivering HCP customer service with AI-enabled systems offers biopharma organizations a whole slate of benefits.

• MI teams can manage changes in demand and the continually increasing volume of questions presented by inquirers. When unexpected surges occur, conversational AI agents can be deployed rapidly to alleviate the workflow. This has been a valuable risk mitigation strategy for manufacturers during the pandemic.
• Interactions with conversational AI agents are fast and fluid, providing the high level of detail and accuracy required in the life sciences industry. The agents are accurate, responsive, and can deliver comprehensive information and instruction in multiple languages.
• Advanced tools can access former customer interactions on which to base their responses, ask follow-up questions, and provide additional details the customer might need. This approach ensures all inquiries receive answers promptly and compliantly, and that adverse events (AEs) and product quality complaints are swiftly identified and triaged.
• The current generation of conversational AI agents uses a combination of smart technologies to provide an engaging customer experience. HCPs get timely and accurate information, regardless of whether they are looking for support via a phone call or written format.
• The technology can handle predictable changes in call demand efficiently and the increased volumes that often occur around changes in a product’s lifecycle. Examples include launching an existing product to a new market or a patient support program.

Manufacturers are discovering that many customers prefer conversational AI because the engagements are faster and equally accurate. Meanwhile, consumers have grown accustomed to digital interactions in their personal lives, and expect the same speed, accuracy, and multi-channel engagement from life sciences companies.

AI’s impact on the biopharma industry

The deployment of conversational AI agents is rapidly transforming customer service in the biopharma space. The AI agents add capacity to the industry, deliver consistent support across geographies and agents, provide 24/7 support, achieve compliance and faster response times, and meet the needs of customers who prefer to self-serve.

Biopharma companies reduce their risk of inquiry-related volume surges, cut operational costs, and optimize the delivery of medical information to HCPs and patients. These factors help to boost customer satisfaction levels by ensuring inquiries are handled in a timely fashion AEs and product quality complaints are identified and handled promptly, leading to a more robust and compliant overall environment.

Preparing for future success

Research shows that biopharma companies often face a lack of buy-in from senior leadership for AI-enabled systems, partly because of earlier unfavorable experiences with more traditional chatbot approaches. However, the increased need for scalability and capacity is driving the industry to improve its technological capability with a view to testing innovative approaches such as conversational AI and providing efficient, omnichannel HCP support.

Over the next few years, the most successful organizations will be those that use the current opportunity to rethink their MI workflows and develop hybrid human-AI models. These models will allow them to optimize their customer service by managing the volume, consistency, and reliability of responses seamlessly and compliantly across markets and languages.

Simon Johns is director of medical information and marketed product safety at IQVIA. He has more than 25 years of experience supporting customer projects across all stages of drug development and the full product lifecycle. As director of medical information and marketed product safety, he has been managing global MI projects focused on process optimization and technology enablement that drive enhanced efficiency and customer engagement. Simon is a member of the European DIA Medical Information and Communications Training Team, advising pharmaceutical companies on best industry practices, innovation and automation. He speaks regularly on topics ranging from implementing suitable technologies and innovations to optimize Medical Information to the benefits of integrating MI and pharmacovigilance to increase compliance and product value, leveraging IQVIA’s Local Affiliate Product Services (LAPS), which provide full support for MI and local country pharmacovigilance requirements.