Pharma Tech Trends for Today and Tomorrow

Sandeep Soman – VP, Data Engineering

As a data enthusiast and technologist in the healthcare marketing domain, I am fascinated and astounded by all the ways digitization can improve the lives of our current population and further enhance value-based care and service for the future generations. Today I want to address two areas, which in my opinion are very relevant today and will grow exponentially in the coming years:

  1. Connected TV (CTV)/Over the Top (OTT) in AdTech/MarTech
  2. Artificial Intelligence (AI)/Machine Learning (ML) in Pharma

In response to our way of life during and after COVID-19, we saw the rapid digitization of not only the content itself but how we received it, for both entertainment and commercial purposes. One channel that excites me is CTV and OTT. In the past, television was limited to traditional broadcasting channels. Now, CTV/OTT has emerged as a powerful platform that combines the best of television and digital capabilities. With the increasing popularity of smart TVs, streaming devices, and on-demand services, viewers now have more options than ever to watch content on their terms.

This shift has not only revolutionized the way people watch content, but it has also opened new possibilities for marketers to reach their audience. These media allow us to reach and engage with our target audience in a way that was not possible before. By leveraging the targeting precision of digital advertising, businesses can create immersive, impactful, and personalized experiences for viewers.

CTV/OTT ads are becoming more sophisticated and are now being used for interactive experiences, such as product demos and quizzes. The measurement of the platform ads is becoming more accurate as well. With the help of innovative technologies, marketers can now track the performance of their CTV/OTT campaigns in real time.

Top CTV Advertising platforms today:

  1. Apple TV
  2. Roku TV
  3. PlayStation, etc.

Top OTT Advertising platforms today:

  1. Prime Video
  2. Netflix
  3. Disney+, Hulu, etc.

AI/ML in Pharma:
The concept of making informed decisions based on data has become common in today’s business landscape, but it is crucial within the pharmaceutical industry. With the increase in data digitization and the advancement in computational processing, real-time use cases of AI have provided the pharmaceutical industry the ability to train machine learning models to help solve or understand complex problems like potential therapeutic effects of molecules on diseased cells.

AI/ML are increasingly being applied today in these key areas:

Drug Discovery: Drug Research & Development is a lengthy, complicated process and is one of the main reasons for the high cost of drugs, but the AI/ML/Computer vision advancements have accelerated the drug discovery and manufacturing process which will eventually address the issue of drug prices.

Predicting Patient Responses: ML can be used to predict how various patients could respond to different drugs or treatments. Treatment plans can then be personalized, and patient outcomes can even be improved using the patient response predictions by ML.

Increasing Knowledge of Efficacy and Safety: ML can be used to analyze data from clinical trials and identify factors that affect the efficacy and safety of drugs. This assessment can help improve the design of future clinical trials and ensure that drugs are safe and effective.

We have overcome the challenge of not having enough data, although quality still needs to be improved. Just because data can be captured, it does not mean that it can be directly translated into the value it can deliver. It is no secret that organizations today struggle and will continue to struggle with staying on top of the quality and application of such a magnitude of data. I believe that AI tools and utilities will have a significant impact in not only the smart application of data but in the broadening of data use altogether. The new challenge we are going to face will be in the skills and resources needed to keep up with these new AI tools and utilities.

We can already see the shift in mindset towards adopting and embracing technolog. With the advent and fascination of conversational generative AI, we see workers from all domains and industries fostering the need for continuous learning and adaptability. This journey to leverage the power of digitization and technology to make a positive impact on healthcare, transform lives, and create a healthier world for generations is going to shape the future of our careers. Along this journey, there will be significant changes in workflows, and technology will inevitably advance, leading to a revolution in how we collaborate and provide value-based services to our customers.

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