That the drug Industry’s growth strategy now extends beyond human intelligence, across the value chain, are being vindicated by several reports, around the world since several years. Illustratively, on September 1, 2019, Novartis and Microsoft announced a multiyear alliance which will leverage data & Artificial Intelligence (AI) to transform how medicines are discovered, developed and commercialized.
The trend is going north and fast. For example, on November 28, 2023 another such report highlighted yet another interesting initiative. It reported that to advance – mind boggling generative AI and foundation models. These extend the technology’s use beyond language models, for which Boehringer Ingelheim collaborates with IBM to accelerate its pace of creation of new therapeutics.
There isn’t an iota of doubt now that AI is rapidly transforming the pharmaceutical industry, including the way companies market their products. The technology is being used in a variety of ways to improve marketing effectiveness, reach new audiences, and personalize patient interactions, among many others.
I wrote about the need to leverage AI in pharma marketing on July 26, 2021. However, in today’s article, I shall focus on the criticality of investment in collaborative partnership in the AI space including generative AI, to acquire a cutting edge in the business process, for performance excellence. Let me start with some specific areas of relevance of using AI in pharma marketing space:
Examples of the relevance of using AI in pharmaceutical marketing:
- Personalized drug recommendations: AI can be used to analyze patient data and recommend the most appropriate drug treatments for each individual patient. This can help to improve patient outcomes and reduce the risk of adverse drug events.
- Patient education and support: AI can be used to provide patients with personalized education and support materials. This can help patients to better understand their conditions and make informed decisions about their treatment options.
- Real-time feedback and insights: AI can be used to collect and analyze real-time feedback from patients. This feedback can be used to improve the effectiveness of marketing campaigns and develop new products and services.
Several years ago, on October 31, 2016, I wrote in this blog on the relevance of Artificial Intelligence (AI) in creative pharma marketing. Interestingly, today it appears that many pharmaceutical companies are fast realizing that AI is rapidly transforming the drug industry, in its entire value chain. Now from its relevance let me dwell on the examples of specific areas where the pharma companies have started leveraging AI in their marketing processes.
Several areas where pharma companies are using AI in marketing:
- Improving marketing effectiveness with targeted advertising and audience segmentation: AI algorithms can analyze vast amounts of data to identify the most effective channels and messaging for specific patient populations. This allows pharma companies to reach the right people with the right message at the right time, maximizing the impact of their marketing campaigns.
- Reaching new audiences: AI can help pharma companies to identify and reach new patient populations that may not have been accessible through traditional marketing channels. This can be especially helpful for reaching patients with rare diseases or who live in remote areas.
- Patient journey mapping and engagement: AI can be used to track patient interactions with a company’s brand, from initial awareness to post-purchase behavior. This data can be used to create personalized patient journeys, providing the right information and support at each stage of the healthcare process.
- Chatbots and virtual assistants: AI-powered chatbots can provide 24/7 customer support, answering patient questions and addressing concerns. Virtual assistants can also help patients manage their medications, schedule appointments, and track their health data.
- Personalized patient interactions: AI can help pharma companies to create personalized patient experiences that are tailored to the individual needs and preferences of each patient. This can lead to improved patient satisfaction and adherence to treatment plans.
- Predictive analytics and market forecasting: AI can analyze historical data and current trends to predict future market demand for specific products or therapies. This information can help pharma companies make informed decisions about product development, marketing strategies, and resource allocation.
- Targeted drug discovery and development: AI is being used to accelerate the drug discovery and development process by identifying potential drug candidates, predicting clinical trial outcomes, and optimizing the design of new therapies.
These point out, with the use of AI in pharmaceutical marketing, drug players can reap a rich harvest of several important benefits. Now, let me illustrate this point with some of both global and local examples of companies in this area, from available reports.
Global examples of how pharma companies are using AI in marketing:
- Novartis is using AI to personalize patient interactions and improve adherence to treatment plans.
- Pfizer is using AI to develop targeted advertising campaigns that reach the right patients with the right message.
- Merck is using AI to identify new drug targets and accelerate the drug discovery process.
- AstraZeneca is using AI to improve patient safety and reduce adverse drug events.
It is also gathering momentum within Indian healthcare industry:
As AI technology advances across the globe, we can expect to see more and more innovative applications of AI within different areas of the Indian healthcare industry, including pharma marketing. Encouragingly, several organization specific initiatives are now being reported on the use of even generative AI in the healthcare space. These include, as reported:
1. Targeted advertising and audience segmentation in India:
- Sun Pharma is using AI to target its marketing campaigns to specific patient populations based on their demographics, medical history, and online behavior. This has helped the company to increase the reach and effectiveness of its marketing campaigns. For example, in 2023, Sun Pharma partnered with an AI startup to develop a new algorithm that can identify potential patients for its diabetes medication Lipaglyn. The algorithm uses data from patient electronic health records, social media, and wearable devices to create a profile of each patient. This information is then used to target Lipaglyn ads to patients who are most likely to benefit from the medication.
- Dr. Reddy’s Laboratories is using AI to segment its patient audience based on their risk of developing certain diseases. This information is then used to develop targeted marketing campaigns that promote the company’s preventive healthcare products. Illustratively, in 2023, Dr. Reddy’s Laboratories launched a new marketing campaign for its cholesterol medication Ezetimibe. The campaign uses AI to target ads to patients who are at risk of developing heart disease. The AI algorithm uses data from patient demographics, medical history, and lifestyle factors to identify patients who are at high risk.
2. Patient journey mapping and engagement:
- Apollo Hospitals is using AI to track patient interactions with its brand and create personalized patient journeys. This includes providing patients with relevant information and support at each stage of their healthcare journey, from diagnosis to treatment to follow-up care. Even in In 2023, Apollo Hospitals launched a new patient engagement platform that uses AI to provide patients with personalized information and support throughout their healthcare journey. The platform includes a chatbot that can answer patient questions, a virtual assistant that can help patients schedule appointments, and a personalized health dashboard that tracks patient progress.
- Fortis Healthcare is using AI to develop chatbots that can answer patient questions and provide 24/7 customer support. This has helped the company to improve patient satisfaction and reduce call center costs. As reported, Fortis Healthcare’s 2023 AI initiatives demonstrate their commitment to leveraging technology for better patient care, efficient operations, and improved healthcare experience. By integrating AI across various departments and functions, they are paving the way for a more intelligent and personalized future of healthcare in India.
4. Predictive analytics and market forecasting:
- Cipla is using AI to predict future market demand for its products. This information is then used to optimize the company’s supply chain and production processes.
- Lupin is using AI to forecast the potential success of new drug candidates in clinical trials. This information is then used to make informed decisions about which drugs to invest in further development.
5. Drug discovery and development:
- Glenmark Pharmaceuticals is using AI to identify potential drug targets and design new therapies. This has helped the company to accelerate the drug discovery and development process.
- Syngene International is a contract research organization (CRO) that uses AI to analyze preclinical data and predict clinical trial outcomes. This information is then used to help pharmaceutical companies make informed decisions about their clinical trial programs.
Despite a plethora of pathbreaking and business performance enhancement opportunities that advanced application of AI offers, there are also some key challenges, which need to be effectively addressed by engaging with the Indian policy makers and the regulators. These areas include:
- Data privacy: Pharma companies need to be careful to protect patient data when using AI. This includes obtaining patient consent for data collection and using anonymized data whenever possible.
- Transparency: Pharma companies need to be transparent about how they are using AI in their marketing campaigns. This will help to build trust with patients and regulators.
- Regulatory compliance: Pharma companies need to ensure that their use of AI complies with all applicable laws and regulations.
That said, regardless of these challenges – as I wrote on July 15, 2019, about the potential of disruptive impact of AI in Indian pharma marketing – such initiatives are fast gaining momentum.
Which is why, more often, an organizational growth strategy has now the scope to germinate beyond the human intelligence of marketers. In this scenario, I reckon, those pharma companies who will be capable enough to overcome these challenges, whatever it takes, to get the best of rapidly advancing technology of AI – will be better positioned to excel in the future.
By: Tapan J. Ray
Disclaimer: The views/opinions expressed in this article are entirely my own, written in my individual and personal capacity. I do not represent any other person or organization for this opinion.