• Sustainability
  • DE&I
  • Pandemic
  • Finance
  • Legal
  • Technology
  • Regulatory
  • Global
  • Pricing
  • Strategy
  • R&D/Clinical Trials
  • Opinion
  • Executive Roundtable
  • Sales & Marketing
  • Executive Profiles
  • Leadership
  • Market Access
  • Patient Engagement
  • Supply Chain
  • Industry Trends

The Rise of AI in Pharma


How AI Can Improve Engagement with Healthcare Professionals (HCPs).

Chirag Bhadana

Chiraag Bhadana
Pharma marketer

As AI continues to dominate the news, maximizing its potential is on every C-suite leader’s mind. Successful AI adoption, specifically in HCP marketing, will require a thoughtful, customer-centric approach to avoid aggravating the promotional fatigue and dissatisfaction fostered by drugmakers' dash toward digital1 since COVID-19. This article provides an overview of some key areas for AI integration that can help improve the HCP customer experience today and tomorrow.

Given AI's evolving state, successful adoption will require a balanced mindset of curiosity and caution, a grasp of current and future uses, and a plan for navigating regulatory concerns. But those who use AI to deepen their understanding and relationships with HCP audiences will likely reach new levels of engagement and reward. At the same time, those who focus their efforts on short-term gains–or ignore the rising tide of AI altogether–are likely to be left behind.

Here are a few key areas where AI holds promise for the future of pharma marketing and communications.

Predictive segmentation and targeting

Joe DeLuca

Joe DeLuca
Digital and innovation strategist

Every leader understands the importance of segmentation and targeting. Reaching the right audience ensures your message connects sooner, which increases efficiencies and reduces wasteful spending. Today, machine learning models process large datasets to identify patterns and trends in HCP behavior, enabling predictive analytics for high-impact strategies that can dramatically affect the bottom line.

Advanced analytics solutions available today can analyze an incredible amount of data related to prescribing behavior and influence, allowing marketers to identify cohorts of HCPs most likely to amplify messages through their networks of influence. Harnessing these segments as priority targets can optimize marketing efforts across the board–from targeting efficiencies to establishing leadership and market presence. Additionally, these toolkits can help identify patients and support earlier diagnosis and better outcomes. For example, 81D is an advanced analytics firm that combines real-world data, artificial intelligence, human analysis, and deep healthcare domain knowledge to identify high-impact segments, thought leaders to bolster key opinion leader (KOL) strategies and undiagnosed patients to accelerate treatment decisions.

Customer Insights and journey mapping

Marketers invested in customer experience understand the power of empathic design and the value of developing personas and customer journey maps to better understand and serve audiences. Today, machine learning, language-based AI models, and conversational intelligence tools can supercharge efforts by rapidly analyzing HCP interactions across channels to detect emotions, attitudes, and pain points. These tools add rich layers of data-driven insight into the customer experiences we seek to understand and improve. Leveraging these tools early can provide a more complete picture of existing customer experiences and unlock new paths to growth as organizations plan to improve customer experiences.

Additionally, teams interested in deepening customer empathy have the opportunity to humanize their data in new ways by building interactive personas. Instead of referring to a flat summary representation of an HCP profile, custom chatbots can be trained on persona data, unlocking the ability for key stakeholders to have ongoing conversations with target audiences throughout the planning process. We are likely to see more organizations integrate LLMs with data query tools to enable conversational retrieval of data from larger databases. Imagine the ability to make waves of data instantly available to cross-functional teams using natural language.

Conversational AI and virtual assistants

We may soon say goodbye to the era of clunky websites and IVAs that are navigated screen by screen. Today’s HCPs want information that meets their needs fast. AI tools are rising to the challenge by answering questions on demand across channels. Chatbots that process language and generate images can increase marketing and sales efficiencies with 24/7 on-demand services. Implemented thoughtfully, AI-based chatbots bolster customer experiences when combined with human-level interactions. As a first point of contact, chatbots can answer product questions, link to curated assets, and recognize more complex needs for triage to human support. For HCP audiences, that could mean a sales rep or an MSL.

Today, few drugmakers employ these tactics on their websites. However, those who do it thoughtfully are likely to drive greater brand perception and speed up the consideration and trial of new products. As these tools evolve, more organizations may adopt virtual assistants to serve other functions as well, including on-demand virtual nurse practitioners who can assess patient concerns before and after appointments. Companies like Uneeq have paired ChatGPT capabilities with AI avatars that can be trained on product and customer subject matter to make this future a reality. To ensure compliance, branded bots can be trained on product information and regulatory guidelines to prevent them from going off script.

Personalized content and channel delivery

AIs can analyze vast amounts of data on healthcare provider preferences, behaviors, and past interactions to generate highly personalized content to meet the needs of HCP audiences. Today, more companies employ AI models to assemble and curate the most effective content from a centralized pre-approved repository and deliver tailored message flows across channels.

Platforms like Salesforce and Veeva use machine learning to predict HCP behavior, needs, and preferences. They support optimized customer journeys and sequence tailored non-personal messaging flows across the ideal mix of channels (email, webinars, digital ads, etc.). Veeva’s CRM Bot can even assist sales reps in generating personalized content at scale. Organizations that lack the tech stack but have funds earmarked can experiment with the support of third-party platforms run by Medscape and others.

While Salesforce, Veeva, and others have delivered AI-optimized content and channel delivery, we can expect these AI capabilities to become more sophisticated for use in new scenarios, including peer-to-peer education. While virtual product theaters and speaker programs have been employed for some time, we can expect these offerings and their real-life counterparts to become more immersive, intelligent, and customizable, adapting to known customer profiles. For instance, by entering an NPI number, these experiences can drive the next-best actions with educational content that meets known or predicted needs, delivered by an avatar they can relate to (e.g., a registered nurse avatar addressing a fellow nurse practitioner). As time marches on, the applications will become exponential, and those who leverage curiosity and experiment today will stand to gain the most.

Regulatory compliance: the path ahead

There is currently no PhRMA2 guidance that exists today for regulating the use of AI in promotional communications with healthcare providers. What this translates to unfortunately is a mistrust and potential misuse of AI to more efficiently communicate the benefits of the product to HCPs. For Regulatory teams, it is a challenge to figure out where such tactics lie from a compliance-perspective with the FDA. Another important challenge is scientific accuracy itself. Today, we trust medical literature and top scientific journals as prima facie accurate and these journals can be cited and sourced for OPDP3 submission purposes to the FDA. However, with AI, we are still grappling with data inaccuracies. In a recent survey conducted by market research firm Vanson Bourne in the United States and Europe, more than 40% of companies experienced data inaccuracies, hallucinations, and data biases in their AI output.4 In a highly regulated environment such as biopharma, it is important to address these challenges before one can begin thinking about the wide-spread adoption of AI.

U.S.-led organizations should look to their European counterparts as a first step. The European Parliament formally adopted the EU Artificial Intelligence Act (AI Act) earlier this year. The AI Act aims to ensure that AI systems in the EU are safe and respect fundamental rights and values. In the coming months and years, we are expected to see more regulation of AI, including guidelines from a legal and regulatory perspective.

The good news is that AI tools are emerging that can audit promotional content against compliance guidelines and regulations, flagging potential issues and suggesting edits to ensure materials meet all requirements before distribution. Examples include SmileGPT Content Copilot by Smile.AI and Red Marker’s AI Compliance Platform. As AI evolves, adopting compliance tools like these can add a much-needed layer to regulatory and compliance workflows, helping streamline the review process in this brave new era.

Ultimately, companies (large and small) that swiftly learn and experiment with AI, using both imagination and critical judgment, will be positioned ahead of the competition. Organizations that break down silos and proactively promote cross-discipline collaboration between commercial, medical, and regulatory teams may experience short-term pains but will be primed for growth and resilience in a market that is bound for monumental and unprecedented changes in the years to come.

The above article is one of a series of articles exploring AI's role and its implications for the biopharmaceutical industry. Co-authored by Chiraag Bhadana (Pharma Marketer) & Joe DeLuca (Digital & Innovation Strategist).


  1. Missakian, Natalie. Don't Spam Us, Healthcare Professionals Plea, As They Seek Qaulity Over Quantity From Pharma Marketers. Fierce Pharma. Jan. 4, 2022. https://www.fiercepharma.com/marketing/hcps-want-less-clutter-more-relevance-from-pharma-marketers-survey-shows
  2. Pharmaceutical Research and Manufacturers of America (PhRMA). https://phrma.org/en
  3. The Office of Prescription Drug Promotion (OPDP). FDA. https://www.fda.gov/about-fda/center-drug-evaluation-and-research-cder/office-prescription-drug-promotion-opdp
  4. AI Data Quality Issues Cost Enterprises Hundreds of Millions. SDX Central. https://www.sdxcentral.com/articles/news/ai-data-quality-issues-cost-enterprises-hundreds-of-millions/2024/03/
Recent Videos
Related Content