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The Pill is Now a Commodity – Can ‘Beyond the Pill’ Models Work in India?

The pill is now a commodity that many of these companies provide at heavy discounts, making money off everything ‘beyond the pill’. Investors are betting heavily on the potential of technological innovation to transform the way healthcare is delivered. The Economic Times reported that in 2021, India recorded investments of $77 billion across 1,266 deals including 164 large deals worth $58 billion. While the money reduced in 2022, the reason wasn’t a lack of faith in this business model. Meanwhile, the pharmaceuticals industry that is most affected by this quiet but rapid change, is grappling with its entrenched culture. Its current business is so profitable that everything else pales in comparison. ‘Build, measure, learn, build again’ – a mantra of the health tech industry is alien to pharma that doesn’t learn, build or measure after launching a product. Pharma also thinks of its customers as doctors alone and does precious little to connect with patients, or caregivers. People who are not sick do not feature on their radar at all. These are cultural values that keep pharma focused on the pill and discourage thinking beyond it. A social media poll conducted by MedicinMan showed almost predictable responses. 100+ respondents who work in the pharma industry in India were quite clearly divided. 48% of them wanted to know what beyond the pill actually meant, while 23% wanted to know how to execute it. The rest felt that the ultra-competitive environment in the Indian generics market required very high share-of-voice tactics (19%), or that their customers demanded product information (9%).

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The pharma industry in India is entering a very interesting variant of the post-digital marketing era. The term “post-digital marketing” is used to depict a state where the lines between physical and digital blur considerably for a customer. However, in the context of pharma, this means a state where the industry has stopped questioning the need for digital and has begun to implement very interesting digital marketing initiatives.

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COVID-19 has accelerated the shift in how pharma was engaging with HCPs, professional organisations and even patients in India from a sales to more of a scientific, unbiased and balanced marketing communications. As one of the business leader from a prominent MNC said, “For the first time we are seeing a certain shift in HCP’s preference for scientific communication for innovators companies. MSLs and scientific operation teams will be playing a key role in the near future.”

Is Pharma’s Business Model like McDonald’s? ...

Is Pharma’s business model like McDonald’s? Doing things over & over again without innovation? McDonald’s is famous for its Hamburger University, a training facility at the McDonald’s Corporation global headquarters in Chicago, Illinois. It instructs high-potential restaurant managers in restaurant management. More than 5,000 students attend Hamburger University each year and over 275,000 people have graduated with a degree in Hamburgerology. Sound familiar? Pharma’s training has been on similar lines – hire people continuously and put them through the grind of mugging up essentials of drugs for diseases that the particular company sells. While the McDonald’s model is ideal for its business of replication, it has outlived its utility in healthcare and drug companies are in danger of being reduced to mere suppliers of drugs to new digital platform businesses unless they learn to innovate.

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Saturday, May 3, 2025
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Bengaluru

Role of AI Across Pharma Industry

Introduction

Artificial intelligence (AI) is increasingly pivotal in driving innovation and efficiency as the pharmaceutical industry evolves. From drug discovery to patient care, AI applications are reshaping how companies approach challenges and opportunities in healthcare.

This article explores the diverse AI applications within pharmaceuticals, highlighting key impact areas, their effects on healthcare delivery and patient experience, and their potential to create personalized medicine.


1. Drug Discovery and Research

  • Key Insights: AI-driven platforms can reduce the cost and time of drug development by up to 50% (Mak & Pichika, 2019).
  • Notable Companies: Evotec, Roche, Sanofi, GSK.
  • Impact on Healthcare Delivery: Faster drug discovery leads to quicker availability of new treatments, addressing urgent medical needs.
  • Personalized Medicine Connection: AI can identify specific patient profiles that would benefit from novel therapies, enabling tailored treatment options from the development phase.

2. Clinical Trials

  • Key Insights: AI can potentially redesign clinical trial processes, making them more adaptive and personalized (Bertagnolli et al., 2020).
  • Notable Companies: Eli Lilly, Janssen, Novartis, Sanofi.
  • Impact on Healthcare Delivery: More efficient trials reduce the time it takes to bring new drugs to market, increasing the overall speed of therapeutic innovations and improving patient enrollment.
  • Personalized Medicine Connection: AI allows the selection of participants based on genetic and demographic profiles, resulting in more effective and targeted therapies.

3. Patient Care

  • Key Insights: AI tools can lead to more tailored healthcare, improving efficacy and adherence (Topol, 2019).
  • Notable Companies: Eli Lilly, Novartis, Pfizer.
  • Impact on Patient Experience: Personalized treatment plans enhance patient engagement and satisfaction, leading to better health outcomes and adherence to treatment protocols.
  • Personalized Medicine Connection: AI algorithms analyze individual patient data to recommend customized treatment regimens, enhancing therapeutic effectiveness.

4. Diagnostics

  • Key Insights: AI-driven diagnostics can outperform traditional methods in accuracy and speed (Esteva et al., 2017).
  • Notable Companies: Bayer, Amgen, AstraZeneca.
  • Impact on Patient Experience: Faster and more accurate diagnoses lead to timely treatments, significantly enhancing patient outcomes and reducing anxiety associated with waiting for results.
  • Personalized Medicine Connection: AI can analyze individual patient data to help identify specific conditions, leading to more targeted and effective diagnostic approaches.

5. Biomarker Discovery

  • Key Insights: AI accelerates biomarker discovery, paving the way for precision medicine (Li et al., 2020).
  • Notable Companies: Roche, AstraZeneca, Amgen, Pfizer.
  • Impact on Healthcare Delivery: Identifying relevant biomarkers enables targeted therapies, leading to more effective treatments tailored to individual patient profiles.
  • Personalized Medicine Connection: AI can pinpoint biomarkers that can predict patient responses to specific therapies, allowing for personalized treatment strategies.

Conclusion

AI’s transformative role across these applications demonstrates its potential to revolutionize the pharmaceutical industry. By enhancing efficiency, reducing costs, and improving patient care, AI is setting new standards for innovation and collaboration. As these technologies continue to develop, stakeholders must navigate ethical considerations and ensure equitable access to maximize AI’s benefits for global health, further advancing the cause of personalized medicine.


References

  • Bertagnolli, M. M., Sartor, O., & Chabner, B. A. (2020). The Future of Clinical Trials in Precision Oncology. Nature Reviews Clinical Oncology, 17(5), 277-284.
  • Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., et al. (2017). Dermatologist-level Classification of Skin Cancer with Deep Neural Networks. Nature, 542(7639), 115-118.
  • Jorgensen, J. T. (2018). Drug-Diagnostics Co-Development in Cancer Immunotherapy. Journal of Personalized Medicine, 8(3), 35.

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