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In the Age of AI, Why Emotional Intelligence Is the New Competitive Edge in Indian Pharma Marketing

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In today’s AI-driven world — where scientific excellence, product claims, and competitive pricing are no longer enough to differentiate pharmaceutical companies — Emotional Intelligence (EI) is rapidly emerging as the new strategic advantage in Indian pharma marketing. As doctors face shrinking time, patients demand empathy, and competition intensifies, EI is proving to be the missing link for building trust, deepening engagement, and achieving sustainable performance excellence.

Why Emotional Intelligence Matters More Than Ever in Indian Pharma:

Even the most advanced products or AI-powered tools cannot replace human connection — something that defines healthcare.

EI impacts every core dimension of pharmaceutical performance:

1. Restoring Trust in Doctor–MR Interactions

Doctors today expect representatives who listen and respect their time, not brand pushers.
EI helps MRs:

  • Sense the physician’s mood and priorities
  • Tailor dialogue to communication preferences
  • Build trust through authenticity and empathy

A high-EI interaction doesn’t “sell” — it solves.

2. Making Patient Engagement Truly Patient-Centric

Patients living with chronic illness carry emotional burdens.
EI enables:

  • Simplified, judgment-free communication
  • Recognition of fears and frustration
  • Better adherence through compassionate guidance

3. Lifting Internal Team Performance

High-EI leaders inspire productivity by creating psychologically safe environments — crucial in an industry with intense monthly expectations.

4. Strengthening Corporate Reputation

An EI mindset naturally drives ethical behavior, transparency, and patient-first decision-making in an era of growing scrutiny.

Present Reality: Indian Pharma Is Awakening to EI:

Historically, pharma training focused heavily on product knowledge and activity KPIs.
Today, however:

  • EI is entering training rooms, but inconsistently
  • Activity metrics still overshadow engagement quality
  • Digital transformation often lacks emotional design
  • Yet — early movers are showing how EI can create real competitive advantage

This shift marks the beginning of a more evolved era of Indian pharma marketing.

Real-World Examples: Indian Pharma Teams Practicing Emotional Intelligence:

Below are recent, documented examples where EI has been incorporated meaningfully into high-impact pharma initiatives.

1. Biocon’s Compassion-Driven Oral Cancer Screening Program

Through its community-based mHealth screening initiative, Biocon trained nurses and health workers to approach villagers with empathy — addressing stigma, fear, and anxiety around cancer.

EI in action:

  • Listening to personal fears
  • Delivering sensitive conversations culturally
  • Building trust in early detection

This empathetic approach dramatically improved screening acceptance.

2. Sanofi India’s Diabetes Health Managers

Sanofi deployed trained counselors who support insulin-dependent patients like a trusted guide — not a salesperson.

One such counselor, Awmi, helped a frustrated patient overcome fear, confusion, and adherence lapses by listening and simplifying routines.

EI impact:

  • Reduced anxiety
  • Better therapy adherence
  • Stronger patient–company relationship

A clear example of EI translating into outcomes and brand loyalty.

3. EI-Driven Oncology Engagement by Indian Pharma Teams

Oncology professionals in India increasingly focus on the emotional journeys of patients and caregivers.

Their approach includes:

  • Breaking information into emotionally digestible pieces
  • Addressing stigma, fear, and guilt
  • Supporting caregiver stress

EI here directly improves therapy acceptance and patient outcomes.

4. Novartis’ Arogya Parivar: Empathy at Scale

Arogya Parivar succeeds because it prioritizes understanding over messaging:

  • Health educators speak in regional languages
  • Communication is culturally tuned
  • Trust precedes product discussion

Empathy embedded in strategy strengthened both impact and sustainability.

5. Janssen India’s Holistic Disease-Management Programs

Janssen integrates emotional and psychological well-being into patient and community engagement, particularly in immunology and mental health.

EI isn’t an add-on — it’s part of their treatment ecosystem.

The Path Indian Pharma Must Still Cover:

To unlock EI’s full potential, the industry must address persistent gaps:

1. EI must evolve from “soft skill” to strategic capability

- EI should be treated as a differentiator — not a training checkbox.

2. KPIs must reward quality, not just quantity

- The industry must move beyond call averages toward relationship metrics.

3. Digital transformation must incorporate human-like empathy

- Pharma apps, CRMs, and patient platforms must engage with emotional nuance.

4. EI must be role-modeled by leadership

- Authenticity, empathy, and ethical clarity must flow downward from the top.

5. EI must become measurable and incentivized

- If trust-building behaviors matter, they must be part of the reward system.

Conclusion: 

EI Is the New Currency of Competitive Advantage

As the Indian pharmaceutical industry navigates shrinking access, rising expectations, and intense competition, emotionally intelligent engagement has become indispensable.

AI can enhance productivity.
But EI is what builds trust.

Companies that integrate Emotional Intelligence holistically — from field force capability to patient engagement to leadership culture — will not only outperform competitors but also elevate the quality and ethics of healthcare in India.

Those that ignore it will find themselves outpaced by a more emotionally attuned industry.

— By: Tapan J. Ray

Author, commentator, and observer of life beyond the corporate corridors.

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.

Sources of Examples Cited:

  1. Biocon — mHealth Oral Cancer Screening Programme
    OPPI–EY Report: Reimagining Pharma and Healthcare in India (2023)
  2. Sanofi India — Diabetes Health Managers
    The Economic Times — “Pharma companies using health managers to help patients and earn revenues”
  3. Oncology Patient Engagement Trends
    TheOncoDoc – Redefining Oncology Pharma Marketing in India
  4. Novartis — Arogya Parivar Initiative
    Pharmaceutical Executive (PharmExec) – Country Report: India
  5. Janssen India — Holistic Disease-Management Programs
    PharmExec – Country Report: India

Navigating Potential US Tariffs: Challenges and AI-Driven Opportunities for Indian Pharma

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India’s pharmaceutical industry, reportedly supplying 47% of US generic drugs and exporting $27.9 billion in FY24, faces the threat of 10-25% US tariffs under a potential Trump policy. Major players like Sun Pharma, Dr. Reddy’s, Cipla, Lupin, and Aurobindo, reportedly deriving 30-50% of revenues from the US, must prepare despite tariffs not yet being imposed. This article examines the challenges and AI-driven opportunities, emphasizing the need to protect the Indian Patents Act, 2005, during US trade talks, with Indian and global examples.

Challenges of Potential US Tariffs:

  1. Profit Margin Pressures: Generics operate on 10-15% margins. A 10% tariff could cut EBITDA by 1-2%, while 25% could slash profits by 5%, hitting firms like Aurobindo and Zydus Lifesciences. Raising prices risks losing US market share, where generics fill 90% of prescriptions.
  2. Supply Chain Risks: The US lacks immediate alternatives to India’s generics. Building US facilities could take 3-5 years and cost six times more. Tariff uncertainty could worsen the 271 US drug shortages in Q3 2024.
  3. Competitiveness Threats: Tariffs could erode India’s cost edge, especially if competitors face similar tariff. This deters investment in India’s 20% global generic supply share.
  4. Strategic Uncertainty: Tariff uncertainty complicates planning. US facilities need 12-24 months for FDA approvals and $50-100 million, risky without clear policies.

AI-Driven Opportunities:

AI can help Indian pharma navigate tariff threats by boosting efficiency and exploring new markets. Key strategies include:

1. AI-Driven R&D for High-Value Products:

AI accelerates development of high-margin biosimilars and specialty drugs, less tariff-sensitive.

  • Indian Example: Sun Pharma, reportedly used AI in 2024 to optimize ILUMYA (tildrakizumab) trials, cutting costs by 20% and time by six months.
  • Global Example: Pfizer’s 2023 Watson AI partnership reduced rare disease drug development time by 30%, saving $120 million. Indian firms can use similar tools.

2. Supply Chain Optimization:

AI enhances supply chain resilience, cutting costs and preparing for tariffs.

  • Indian Example: Dr. Reddy’s 2024 SAP AI platform, reportedly optimized atorvastatin inventory, reducing logistics costs by 15%.
  • Global Example: Merck’s 2022 Blue Yonder AI system saved $100 million annually, cutting stockouts by 25%. Indian firms can adopt similar tools.

3. Market Diversification:

AI identifies new markets like Africa and ASEAN, reducing US reliance.

  • Indian Example: Cipla’s 2024 Salesforce Einstein Analytics, reportedly boosted East African exports by 25%, adding $50 million in revenue.
  • Global Example: Novartis’ 2023 AWS AI expanded Southeast Asia sales by 18% ($200 million). Indian firms can target similar markets.

4. AI-Enhanced Manufacturing:

AI optimizes production, lowering costs to offset tariffs.

  • Indian Example: Biocon’s 2023 Bangalore AI facility, using Rockwell Automation, reportedly improved insulin production efficiency by 22%, saving $30 million.
  • Global Example: Roche’s 2024 Siemens AI platform in Switzerland cut antibody production costs by 15%. Indian firms can invest similarly.

5. AI in Regulatory Compliance:

AI streamlines FDA compliance, ensuring market access.

  • Indian Example: Aurobindo’s 2024 Deloitte AI tool, reportedly cut FDA audit preparation time by 40% for metformin.
  • Global Example: Amgen’s 2023 Accenture AI system improved biologics approval rates by 25%. Indian firms can adopt similar tools.

Strategic Recommendations:

  1. Invest in AI: Allocate 5-10% of revenues to AI, following Sun Pharma’s, reportedly  $500 million R&D model.
  2. Protect Patents Act: In US trade talks, like the UK FTA, India must uphold the Indian Patents Act, 2005, especially Section 3(d), to preserve affordable generics.
  3. Secure Trade Agreements: Push for a US trade deal targeting $500 billion by 2030 to avoid tariffs.
  4. Diversify Markets/Products: Use AI to prioritize high-margin drugs and new markets.
  5. Partner with AI Leaders: Collaborate with Google, IBM, or SAP for tailored AI solutions.

Conclusion:

Potential US tariffs threaten Indian pharma’s profits, supply chains, and competitiveness, but they also spur innovation. AI can enhance R&D, supply chains, market diversification, manufacturing, and compliance. Examples from Sun Pharma, Dr. Reddy’s, Cipla, Biocon, Aurobindo, Pfizer, Merck, Novartis, Roche, and Amgen show AI’s potential. India must protect the Indian Patents Act, 2005, in US trade talks to maintain its generics edge. By embracing AI and strategic advocacy, India can turn tariff threats into opportunities to lead globally.

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.

Sources:

  • Trump Tariff to Push Indian Pharma Co to Embrace AI, Cost-Efficient R&D | analyticsindiamag.com
  • Donald Trump tariff relief for now: India’s pharma sector navigates an uncertain US trade future – Times of India
  • How Trump tariffs could impact Indian pharma’s $8.7 bn dream run – India Today
  • Trump Tariffs: Impact & Opportunities in Indian Pharma – www.moneymuscle.in
  • The future of India-US pharmaceutical trade – www.pharmaceutical-technology.com
  • Indian Pharma Braces For Trump Tariff Fallout – Forbes India
  • Indian pharma companies escape Trump’s reciprocal tariffs, for now – www.livemint.com
  • 5 Indian Pharma Companies That Could Be Impacted by Trump’s Tariff Move – www.equitymaster.com
  • Indian Pharmaceutical Alliance Annual Report 2024 – www.ipa-india.org
  • US FDA Drug Shortage Database, Q3 2024 – www.fda.gov
  • India-UK FTA: Safeguarding the Indian Patents Act – www.financialexpress.com

 

Indian Pharma Marketing’s AI Moment: Lead the Change or Fall Behind

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(With An Actionable AI Adoption Checklist below for Indian Pharma Marketers)

India’s pharmaceutical market is one of the most complex and exciting in the world. With over 60,000 brands battling for attention, millions of patients, and a healthcare landscape rapidly evolving, marketing here is anything but straightforward.

For pharma marketing leaders – whether you head brands, commercial strategy, or sales and marketing – the challenge is clear: how do you cut through the noise and connect meaningfully with doctors and patients? Today, its answer squarely lies in Artificial Intelligence (AI).

Global Leaders Are Already Ahead – What About Us in India?

Globally, pharma giants like Pfizer, AstraZeneca, and Novartis have woven AI deep into their marketing playbooks. They use AI to understand doctors’ prescribing habits, create content faster, and personalize engagement at scale. Meanwhile, many Indian teams still rely on broad, one-size-fits-all campaigns, manual content production, and intuition-based decisions.

But the Indian market is changing fast. Expected to nearly double from $65 billion today to $120 billion by 2030 (IBEF, 2024), the competition will intensify. The doctors and patients you want to reach are getting digitally savvy and demand relevant, personalized communication.

Unlocking Market Potential with AI:

AI can sift through massive datasets – prescription trends, regional demand shifts, and social media chatter – and reveal opportunities that traditional methods miss.

For example, Dr. Reddy’s reportedly uses AI to forecast oncology and dermatology demand regionally, tailoring messaging and supply accordingly. However, only about 25% of Indian pharma marketers use AI for segmentation and forecasting (EY India, 2024), leaving a huge gap – and opportunity.

Crafting Distinctive Brand Identities with AI:

AI doesn’t just analyze data; it helps craft brands that stand out. Cipla used AI-powered sentiment analysis to sharpen respiratory care campaigns, winning industry awards in 2024. Instead of guesswork, you get real-time insights into what doctors and patients want.

Accelerating Content Creation:

Producing multilingual, compliant, and scientifically accurate content manually is slow and expensive. Pfizer reduced content production time by 40% globally using AI. Novo Nordisk India simplifies complex clinical data for doctors through AI tools.

For Indian marketers, this means faster, fresher, and more engaging content without exploding costs.

Personalizing Engagement with Healthcare Providers:

The old “one message fits all” approach is dead. AI enables personalized outreach tailored to each doctor’s specialty, region, and prescribing behavior.

Doceree’s AI-driven campaigns in India have delivered 2.5 times more engagement than traditional outreach, proving precision pays off.

Measuring Impact and Maximizing ROI:

Many marketers struggle to see which activities actually drive prescriptions. AI-powered attribution models provide clarity, showing exactly where marketing investments perform best.

EY (2024) reports that AI attribution improves ROI visibility by up to 60%, enabling smarter budget decisions.

An Actionable AI Adoption Checklist From Me for Indian Pharma Marketers:

Start Small:

  • Pilot AI-generated content for one key brand or therapy area.
  • Deploy AI-powered social listening to monitor patient and physician sentiment.
  • Test AI-driven prescriber segmentation to prioritize outreach.

Scale Smart:

  • Integrate AI into your CRM and Customer Lifecycle Management (CLM) systems for real-time insights.
  • Implement AI-enabled marketing attribution tools to optimize spend allocation.
  • Develop AI-driven personalized multi-channel campaigns.

Build a Future-Ready Team:

  • Train your marketing team on AI tools and data literacy.
  • Collaborate with AI-focused technology partners familiar with pharma compliance.
  • Establish cross-functional teams bridging marketing, IT, and analytics.

Measure and Iterate:

  • Use AI dashboards to monitor campaign performance continuously.
  • Reallocate budgets dynamically based on AI insights.
  • Regularly update AI models with new market and behavioral data.

Conclusion: 

Thus, I reckon: Today AI Is Not a Luxury – It’s Your Lifeline

The Indian pharma market is poised for explosive growth and complexity. The brands that win will be those that embrace AI – not as a trendy tool but as the core of their marketing strategy.

Whether you lead brand strategy, commercial marketing, or sales enablement, AI will keep you relevant, agile, and ahead.

Are you ready to start and get your team moving?

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.

Revolutionizing Indian Pharma: The Rise of AI and Its Transformative Impact

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I find it fascinating that some well-established consulting firms like E&Y have recently published multiple reports on AI in the pharmaceutical industry. These reports, often released alongside industry events or as part of broader research initiatives, provide valuable insights rather than a single definitive publication.

Notably, these studies incorporate survey findings from industry executives and in-depth analyses of AI’s evolving role within the pharmaceutical sector. A closer examination of these reports reveals key takeaways that could inspire many:

  • AI is driving a major shift in pharmaceutical marketing – Around 50% of Indian pharmaceutical companies have launched AI-driven initiatives, with 25% advancing to full-scale implementation.
  • Adoption levels vary widely – The depth and scale of GenAI integration differ significantly across individual companies.
  • AI holds immense potential for productivity gains – Studies project an estimated 30-40% improvement in efficiency by 2030.

In essence, Indian pharmaceutical companies are increasingly recognizing AI’s transformative power in marketing and beyond. However, for this momentum to sustain, responsible AI governance and strategic investments in AI talent are crucial. While challenges remain, the trend signals a strong and growing commitment to AI adoption.

Its Game-Changing Impact:

AI, as it emerges, is not just enhancing pharmaceutical marketing in India—it’s redefining it, as I shall narrate below. With AI at the helm, many drug companies are unlocking unprecedented levels of efficiency, cost-effectiveness, and customer engagement. As adoption accelerates, the industry is poised for a radical transformation, delivering game-changing advantages:

  • Unparalleled Efficiency – AI-driven automation streamlines workflows, eliminates bottlenecks, and accelerates decision-making.
  • Strategic Cost Optimization – Smart resource allocation minimizes waste and maximizes return on investment.
  • Revolutionized Customer Engagement – AI enables hyper-personalized interactions, predictive insights, and real-time responsiveness.
  • Exponential Productivity Gains – AI-powered analytics and automation fast-track data processing and market intelligence.

Thus, I reckon, AI is no longer optional—it’s the driving force behind the next era of pharmaceutical marketing. As its influence deepens, Indian pharma is evolving into a smarter, faster, and more adaptive powerhouse, ready to meet the demands of an increasingly dynamic healthcare landscape.

A Look At The Depth of  AI-Powered Transformation in Indian Pharma Marketing:

A large number of Indian pharmaceutical companies are rapidly integrating AI into their marketing strategies, revolutionizing efficiency, engagement, and precision. Here are key examples of AI-driven innovations in some key areas across the industry, as compiled from available documents:

  1. Predictive Analytics for Sales Forecasting – Sun Pharma uses AI to anticipate sales trends, optimize inventory, and tailor regional marketing strategies.
  2. Chatbots for Customer Interaction – Cipla employs AI-powered chatbots to provide real-time responses, enhance engagement, and disseminate product information.
  3. Programmatic Advertising – Dr. Reddy’s leverages AI to precisely target healthcare professionals and patient demographics, boosting campaign efficiency.
  4. Content Personalization – Glenmark utilizes AI to deliver tailored digital content to healthcare providers based on their specialties and interests.
  5. Market Basket Analysis – Torrent Pharma applies AI to analyze prescribing patterns, identifying cross-selling and bundling opportunities.
  6. Sentiment Analysis – Lupin monitors social media and online discussions using AI-driven sentiment analysis to refine marketing strategies.
  7. Virtual Reality (VR) for Product Demonstrations – Zydus Cadila combines AI with VR to create immersive product presentations for healthcare professionals.
  8. Email Campaign Optimization – Biocon enhances email marketing with AI, optimizing content, subject lines, and timing for higher engagement.
  9. Voice-Activated Assistance – Aurobindo Pharma develops AI-driven voice assistants to provide instant support to healthcare professionals.
  10. Compliance Monitoring – Novartis India employs AI to ensure marketing materials adhere to regulatory standards, reducing compliance risks.

The large number of examples highlight AI’s growing influence in Indian pharma marketing, driving smarter, more effective, and highly targeted engagement with stakeholders.

Conclusion:

AI adoption in Indian pharmaceutical marketing is accelerating, with nearly 50% of companies initiating AI-driven projects and 25% moving toward full-scale implementation. Both domestic firms and multinational corporations (MNCs) operating in India recognize AI’s game-changing potential, driving investments to enhance efficiency, engagement, and regulatory compliance in India.

The details on AI adoption among Indian pharma companies and MNCs in India remain uncertain due to limited comparative data. However, significant investments—such as Amgen’s $200 million AI and data science center in Hyderabad (Reuters report, February 24, 2025)—reinforce AI’s growing role in shaping the future of the industry.

As AI continues to revolutionize drug marketing, Indian pharmaceutical companies and global players must focus on strategic implementation, responsible governance, and talent development. The future of pharma marketing in India will be defined by those who successfully leverage AI’s transformative power, ensuring smarter, faster, and more adaptive business strategies in an increasingly digital world.

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.

AI: The New Elixir for Indian Pharma Brand Success

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India’s pharmaceutical market is a potent brew of complexity and opportunity. For new brands, including those in the branded generics space, success hinges on navigating this labyrinth effectively. Artificial Intelligence (AI) is emerging as the alchemist’s stone, capable of transforming market challenges into competitive advantages. This article outlines how pharma marketers can leverage AI to decode market dynamics, craft compelling brand stories, and deliver personalized experiences that fuel the launch of groundbreaking brands in India:

A. Unlocking Market Potential with AI:

  • Deep Dive into Data: AI’s analytical prowess uncovers hidden market segments, regional nuances, and emerging trends. For instance, by identifying untapped rural opportunities, brands can tailor offerings to resonate deeply with local needs.
  • Precision Patient Profiling: AI creates detailed patient personas, enabling hyper-targeted campaigns across multiple channels. This granularity ensures that every interaction is relevant and impactful.

B. Forging Brand Identity with AI:

  • Brand Alchemy: AI assists in crafting distinct brand personalities that captivate the target audience. By analyzing competitors and consumer sentiment, AI helps position brands effectively. 
  • Visual Brilliance: AI-powered design tools accelerate the creation of visually stunning brand identities, ensuring a cohesive look and feel across all touchpoints.
C. Crafting Compelling Narratives with AI:
  • Content Creation Catalyst: AI can help generate engaging content at scale, optimizing it for different platforms and audiences. This ensures a steady stream of relevant content without compromising quality. 
  • Language Mastery: In a linguistically diverse country like India, AI translates content seamlessly while preserving brand voice, reaching a wider audience.

D. Delivering Personalized Experiences with AI:

  • Predictive Powerhouse: AI anticipates customer needs and behaviors, enabling highly personalized campaigns. By understanding individual preferences, brands can deliver tailored experiences that build loyalty. 
  • Digital Dominance: AI optimizes digital advertising, ensuring maximum ROI. From precise targeting to effective bidding, AI drives results. 
  • Customer Centricity: AI analyzes prescriber data to identify high-value customers, enabling tailored interactions that strengthen relationships. 

E. Measuring and Maximizing Impact with AI:

  • Data-Driven Decisions: AI provides actionable insights into campaign performance, helping marketers optimize strategies in real-time.
  • Attribution Accuracy: By understanding the true impact of marketing channels, AI helps allocate resources effectively. 

Available examples of Global Pharma Giants: Pioneering AI in Marketing:

  • Personalized Precision: AstraZeneca leads the charge with AI-driven campaigns tailored to individual patient needs, delivering highly resonant messages. 
  • Content Creation at Scale: Pfizer’s AI-powered content engine churns out diverse, on-brand materials, boosting efficiency and engagement. 
  • Predictive Powerhouse: Novartis leverages AI to forecast market trends and optimize spending, maximizing ROI with data-driven precision.
  • AI-Driven Customer Care: Johnson & Johnson’s AI-powered chatbots enhance customer satisfaction by providing instant support and freeing up human agents for complex issues. 
  • Influencer Identification: Merck uses AI to discover and engage with key opinion leaders, building strong relationships through social media insights.
  • Market Intelligence Amplified: GSK harnesses AI to analyze vast datasets, uncovering unmet patient needs and informing product development. 
  • Sales Force Optimization: AbbVie employs AI to optimize sales routes and resource allocation, boosting efficiency and productivity. 

These global pharma leaders amply demonstrate the transformative power of AI in marketing. By understanding customers deeply, creating compelling content, and optimizing operations, they are driving sales growth and redefining industry standards. 

India’s Pharma Industry: Early Signs of AI Adoption:

While concrete examples of AI in Indian pharma marketing remain elusive due to competitive sensitivities, the industry’s trajectory suggests significant AI adoption. For instance, 

  • Cipla’s precision marketing efforts likely involve AI-driven targeting of specific patient segments.  
  • Sun Pharma’s pulse on patient sentiment is probably aided by AI-powered social listening.  
  • Dr. Reddy’s might be leveraging AI to predict regional demand patterns.

These are early indications of a broader AI trend in Indian pharma marketing. As the industry matures, more concrete examples are expected to emerge. 

Conclusion:

Against the above backdrop, I reckon, AI is not just a tool; it’s a strategic imperative today for pharma marketers in India. By embracing AI, brands can unlock new growth opportunities, strengthen brand equity, and ultimately, improve patient health outcomes.

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.

 

The AI imperative: Propels Purpose-driven Leaders Revolutionizing Patient Care

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The winds of change are blowing in healthcare! Artificial Intelligence (AI) is poised to revolutionize how we deliver quality care to everyone. As a recent ET Healthworld article (March 3, 2024) aptly stated: “AI and technology are going to be transformative. The only way we can provide quality healthcare for the masses of the country will be through technology.” This isn’t just a future possibility, it’s a necessity with the potential to bridge the gap and ensure everyone has access to the care they deserve.

Accordingly, the leadership game in the healthcare industry is also changing. Purpose-driven leaders are harnessing the power of AI and etching their ambitious goals into company DNA. Take a recent  PharmaTimes  article (March 26, 2024) where an AstraZeneca heavyweight declared, “‘we have a bold ambition to eliminate cancer as a cause of death.’” This isn’t just about treatments anymore; it’s about… very close to curing cancer for good. This exemplifies the ‘audacious purpose’ driving their oncology leadership – a vision light years beyond mere effectiveness and safety.

Forget business as usual, healthcare is embracing a revolution! For years, experts have been preaching the gospel of Purpose-Driven Leadership (PDL), especially in healthcare. Now, thanks to visionary leaders in international and national organizations, PDL is taking off at warp speed. This article dives deep into this exciting new frontier, exploring how purpose is reshaping the healthcare landscape.

What it means:

In pharma, leading with purpose used to mean putting patients first, driving ethical innovation, and building trust. Now,the AI era supercharges this mission. This isn’t just about purpose anymore – it goes much beyond. It’s about unlocking a healthier future through transparency, collaboration, and the power of AI. 

This area is now rapidly evolving:

The leadership purpose of the healthcare business has undergone a significant shift over the years, moving from a primarily profit-driven model to one that emphasizes a broader set of goals. Thus, I believe, purpose-driven leadership (PDL) isn’t a fad of the day – it’s a global health revolution. And India’s pharmaceutical industry is no exception! While mirroring the global trend, India’s PDL journey has some unique twists. Buckle up, because we’re about to fast-forward through decades of change and explore the nuances that set India apart. As I envisage, PDL has been evolving in India, broadly following the steps as indicated below:

Early Years (Pre-1970s):

  • Organizational Focus: Primarily generic drug production for domestic needs and exports.
  • Leadership Purpose: Meeting basic healthcare needs and establishing India as a “pharmacy of the world.”
  • Overall Impact: Made essential medicines affordable for many countries, but limited focus on R&D for innovative drugs.

From the beginning of the drug price control era (1970s-1990s):

  • Organizational Focus: Balancing generic production with increasing government support for R&D – mainly reverse engineering, with an eye on process-patent.
  • Leadership Purpose: Maintaining affordability of generics while fostering domestic innovation to fast replicate patented molecules of globally successful drugs.
  • Overall Impact: India became a major player in generics, but original drug discovery lagged.

Patent Regime Shift (With Patent Amendment Act 1999, 2002, 2005):

  • Organizational Focus: Expecting stricter intellectual property regime, increasing focus on branded drugs, especially by large domestic companies.
  • Leadership Purpose: Balancing affordability with profitability and encouraging domestic innovation for new drugs.
  • Overall Impact: Growth in Indian specialty and complex branded generics, including Biosimilar drugs, but concerns about rising drug prices for newer medications.

Current Era (2000s-Present):

  • Organizational Focus: Balancing affordability with patient well-being, access to medications, and establishing a cost-effective and balanced pathway for product and process innovation.
  • Leadership Purpose: Combining innovation with social responsibility and Patient-Centricity with an emphasis on affordability and public health initiatives.
  • Overall Impact: Increased focus on R&D for new drugs, affordability programs, and public health partnerships. However, challenges remain in balancing affordability with R&D investment.

Nevertheless, the winds of change have started blowing within the Indian pharmaceutical leadership, as well. Their purpose is no longer singular – it’s a multifaceted dance balancing affordability, essential for a vast population, with the need for ground-breaking innovation to meet the unmet need. This tightrope walk defines India’s pharmaceutical future, ensuring both accessible medications and advancements in healthcare.

Examples of PBL initiatives by international and Indian companies:

It is worth noting, while some companies might announce major partnerships or product launches related to AI in the drug industry, the underlying development processes often take place over several years. However, we can explore the purpose these leaders likely aim to achieve based on examples ferreted from the public domain:

International:

  • Pfizer & IBM Watson (Clinical Trial Matching Platform):

Purpose: Launched around 2016-2017, this initiative aimed to accelerate patient access to new treatments by streamlining clinical trial recruitment through AI-powered matching.

  • Sanofi & Google DeepMind (Protein Folding Simulations):

Purpose: Partnership, which most likely began around 2019-2020. This collaboration focuses on using AI to revolutionize drug discovery by allowing for highly accurate and efficient design of new medications.

Indian: 

  • Sun Pharma (AI-powered Chatbots):

Purpose: This initiative leverages AI to improve patient education and medication adherence, ultimately aiming to improve patient health outcomes.

  • Dr. Reddy’s Laboratories (AI for Drug Discovery):

Purpose: Their use of AI focuses on identifying promising new drug targets through advanced data analysis, aiming to accelerate drug development for unmet medical needs.

The way forward for Indian drug industry leaders:

Indian pharmaceutical leadership can leverage AI to:

  1. Innovate for patients: Develop targeted drugs and personalized treatments using AI-powered discovery and data analysis.
  2. Expand access: Optimize supply chains and fight counterfeits with AI for affordability and patient safety.
  3. Build trust: Use AI Chatbots for patient education and address concerns through social media analysis.
  4. Be ethical: Prioritize data privacy and transparent AI for responsible use. Comply with the Uniform Code of Pharmaceutical Marketing Practices (UCPMP)
  5. Collaborate for impact: Partner with AI experts and open-source initiatives to accelerate healthcare solutions for India.

This approach allows Indian pharmaceutical leadership to lead with purpose by putting patients first and leveraging AI for a healthier future.

The differences between the older and the AI Era:

The key differences between the old days and the AI era, in the steps Indian pharmaceutical leaders take towards leading with purpose, lie in the scale, speed, and precision achieved through AI:

Old Days:

  • Limited data: decision-making relied on smaller datasets, leading to fewer targeted solutions.
  • Manual processes: drug discovery, supply chain management, and patient education were labor-intensive and time-consuming.
  • Reactive approach: identifying patient needs and concerns often happens after the fact.

AI Era:

  • Massive data analysis: AI can analyze vast amounts of patient data, genomics, and healthcare information, leading to more precise drug targets, personalized treatments, and proactive solutions.
  • Automation and optimization: AI automates tasks and optimizes processes, accelerating drug discovery, supply chain management, and patient communication.
  • Predictive capabilities: AI can analyze data to predict patient needs and identify potential issues before they arise, allowing for a more proactive approach.

Essentially, AI empowers Indian pharmaceutical industry leaders to move beyond traditional methods and achieve their purpose goals with greater efficiency, precision, and impact.

Conclusion:

Now is the time to forget the old limitations! AI is a game-changer for the Indian pharmaceutical industry’s mission to improve healthcare for all fueled by PDL. Here’s how:

  • From blind guesses to laser focus: AI analyzes mountains of data to pinpoint precise drug targets and personalize treatments, leaving limited information in the dust.
  • Slowpoke to speed demon: AI automates tasks and streamlines processes, accelerating drug discovery and patient communication at warp speed.
  • Playing catch-up to leading the charge: AI predicts patient needs and flags potential problems before they arise, enabling a proactive approach that revolutionizes healthcare.

This isn’t just leading with purpose anymore; it’s unleashing the power of purpose-driven healthcare solutions that will delight patients with their outcomes. Thus, I reckon, with AI, propelled by its leadership’s inclination and drive, Indian pharmaceutical companies can deliver better healthcare solutions faster and with a much greater impact.

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.

A Transformational Approach To Patient-Driven Pharma Marketing

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This new-era approach to gain a cutting-edge in drug marketing is fast gathering winds on its sail – the world over and is being accepted as a transformational one, in tandem. It is primarily a two-pronged approach that involves merging or convergence of RWE (real-world evidence) and AI (artificial intelligence) into a unified approach for tasks like healthcare research, drug discovery, and patient care optimization.

However, in the context of this article, the process would involve a perfect synthesis between RWE (Real-World Evidence) and AI (Artificial Intelligence) for achieving a cutting edge in patient-driven marketing. A well-crafted shift to this strategic direction, I reckon, holds immense potential to revolutionize the way pharmaceutical companies connect with patients and build trust in today’s complex market environment.

Provides benefits both to patients and drug companies in equal measure:

Following reasons may give a sense of how this transformational strategic initiative provides benefits both to patients, as well as the drug companies in equal measure, which, consequently, makes this fusion or synthetization is so crucial:

1. Unveiling Deeper Patient Understanding:

  • AI-powered insights: AI excels at analyzing vast amounts of RWE data, uncovering hidden patterns and relationships that might escape human analysis. This translates to a deeper understanding of patient journeys, preferences, and unmet needs.

2. Crafting Personalized Engagement:

  • Tailored communication: By leveraging RWE and AI, pharma companies can move beyond generic marketing messages. They can tailor their communication to specific patient segments, addressing their unique concerns and delivering relevant information about treatment options.
  • Empowering patients: Access to clear, personalized information empowers patients to actively participate in their healthcare decisions. RWE and AI can provide insights into potential benefits and risks, allowing patients to make informed choices alongside their healthcare provider.

3. Optimizing Marketing Strategies:

  • Enhanced targeting: Traditional marketing often involves a scattershot approach. RWE and AI enable precise targeting, reaching the right patients with the right message at the right time. This improves marketing ROI and ensures patients receive relevant information about potential treatments.
  • Data-driven decisions: By analyzing RWE data, AI can identify trends and predict patient behavior, allowing pharma companies to optimize their marketing strategies and campaigns for maximum impact.

4. Demonstrating Real-World Value:

  • Moving beyond clinical trial data: Clinical trial data, while essential, doesn’t always translate perfectly to real-world settings. RWE provides a more holistic picture of drug effectiveness and safety in everyday clinical practice, building trust with patients and healthcare professionals.
  • Supporting regulatory approvals: RWE, backed by AI analysis, can provide robust evidence to support regulatory applications for new indications or expanded use of existing drugs.

These are a few reasons why this novel approach is gaining traction across the world.

Some recent global and Indian examples related to the synthesis of RWE & AI in patient-driven drug marketing:

Let me now give just 5 examples each for both global and Indian companies, as available in the public domain, of how pharmaceutical companies are deriving benefits from this process.

Examples from global companies:

1. AstraZeneca: Analyzed RWE data from EHRs to identify subgroups of patients who respond best to their lung cancer drug Tagrisso. This enabled them to target marketing efforts towards these specific groups, leading to increased adoption and sales.

2. Roche: Employed AI to analyze social media data to understand patient sentiment towards their hemophilia drug Hemlibra. This helped them tailor their marketing messages to address patient concerns and anxieties, improving patients’ experience.

3. Pfizer: Leveraged RWE from registries to demonstrate the long-term effectiveness and safety of their pneumococcal vaccine Prevnar13 in older adults. This data supported regulatory approval for a new indication, expanding market reach.

4. Novartis: Utilized AI to analyze large datasets from clinical trials and RWD to predict patient response to their heart failure drug Entresto. This personalized treatment approach improved patient outcomes and reduced hospital readmissions.

5. AbbVie: Used RWE to identify factors influencing physician prescribing behavior for their immunology drug Humira. This data helped to tailor their marketing efforts towards relevant healthcare professionals, enhancing brand awareness and adoption.

These are just a few examples, and the field is constantly evolving. As RWE and AI technologies become more sophisticated, we can expect even more innovative Patient – Centric marketing approaches from global drug companies.

A few examples from domestic Indian companies:

While the use of RWE and AI in patient-driven drug marketing is still at an earlier stage in India compared to global giants. This is mainly due to the relatively nascent stage of adoption in India. As the field evolves, we can expect more examples of innovative applications for greater impact in the future. That said, there are some interesting examples emerging, such as:

1. Sun Pharma: Launched a mobile app called “SunRx” that leverages AI to analyze past medication history and suggest personalized recommendations for over-the-counter (OTC) products. This app uses patient data anonymously and adheres to privacy regulations.

2. Cipla: Partnered with a US-based AI company to develop a platform that analyzes RWE data from patient registries to identify new treatment opportunities for complex diseases like chronic kidney disease. This data will be used to inform future drug development and marketing strategies.

3. Dr. Reddy’s Laboratories: Implemented a pilot program using AI to analyze social media data to understand patient sentiment towards their diabetes medication. This helped them identify key concerns and tailor their communication strategies accordingly.

4. Glenmark Pharmaceuticals: Leveraged RWE data from electronic health records (EHRs) to demonstrate the real-world effectiveness of their respiratory drug Brocacef. This data was used to support regulatory approval for a new indication, expanding market reach.

5. Lupin Limited: Partnered with a healthcare analytics company to analyze claims data and identify patient segments with unmet needs. This data will be used to develop and market targeted solutions for these specific patient groups.

It’s important to acknowledge here that the Indian drug industry faces several challenges in adopting RWE and AI for patient-driven marketing in the country. These include access to high-quality and standardized RWE, scarce availability of skilled professionals for building and implementing industry-oriented AI-based solutions. Besides, the regulatory framework for using RWE data in marketing is still evolving, while robust ethical frameworks and transparent data handling practices are essential for this process to be sustainable.

Conclusion:

Synthesizing RWE and AI in pharmaceutical marketing is not just an option now, but a critical step towards a more Patient-Centric and data-driven approach that benefits both patients and pharmaceutical companies. By addressing the challenges and ensuring ethical practices, this powerful combination can pave the way for a future where patients are empowered partners in their health journeys, and pharmaceutical companies can deliver targeted, effective marketing that truly benefits patients.

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.

How Pharma Growth Strategy Now Extends Beyond Human Intelligence

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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:

As reported:

  • 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.

Conclusion:

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.