“Hey there, fellow curious minds! Today, I want to take you on an exhilarating journey through the incredible world of Generative AI. From its humble beginnings to its mind-boggling present, this remarkable field of artificial intelligence has revolutionized the way we create, imagine, and dream. As an AI language model myself, I’ve had a front-row seat to witness the awe-inspiring evolution of Generative AI. So buckle up, get ready to be amazed, and let’s embark on a captivating adventure through time to explore the mind-bending capabilities of this cutting-edge technology. Get ready to have your imagination stretched to new limits!”
ChatGPT-4

 
This month, last year –  2022, the world had no idea of the Generative AI (Gen AI) revolution that was about to transform the way content was created and generated. Fast forward to November, Open AI launched the AI chatbot ChatGPT and ushered in a new age of communication technology. 

Over the past decade, we have seen that the advancements in the world of AI have not just evolved but leapfrogged, making it an integral part of our daily lives, from virtual assistants like Siri and Alexa to self-driving cars and drones to generating convincing stories and lifelike images.

So how did it all begin?

The history of AI spans over nine decades, from the early attempts at creating machines that mimic human intelligence to the recent breakthroughs in deep learning and generative models.

During the early days, rule-based or keyword approaches were prevalent, which evolved into more complex machine learning algorithms that can learn from data and improve over time. In recent years, deep neural networks like RNN, CNN, and LSTMs have emerged as powerful techniques for training models to recognize patterns in data. This has led to breakthroughs in areas like computer vision, speech recognition, and natural language processing. 

Major strides were made in the field of Generative AI through robust architectures like transformers which enabled transfer learning. This breakthrough has facilitated the seamless transfer of knowledge from one system to the other. Advances in computing power and the availability of large datasets to train these transformers have made them powerful, enabling the potential to leverage Generative AI in industrial applications. 

Over the years, at Tiger Analytics, we helped companies embrace AI and machine learning capabilities enabling them to find innovative ways to improve business performance, efficiency, speed, and consistency of service. Now with the advent of Generative AI, we are seeing a shift in industry expectations and the evolution of solutions across different use case scenarios. 

Here’s a side-by-side comparison:

AI has continued to transform businesses and the way they operate on a day-to-day basis. Generative AI has now begun rewriting the rules of the game. As companies rush to become early adopters, working with the right team and the right advisors who understand the technology’s potential to deliver value will help shape critical decisions.

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For a long time, Pharma companies have been seen as ‘drug providers’ with a highly transactional relationship with patients. However, with the advancements in data analytics in recent years, the Pharma industry has now adopted a radically different approach aiming to be a ‘partner in every patient’s journey at every step of the way’. The impact of this approach is most imminent in rare disease therapies where patients require continuous support and engagement (from caregivers and the drug provider). Pharma companies – via their Patient Services organization – work tirelessly to ensure that the patients get easy access to therapy, remain on therapy, and the caregiver/patient needs are taken care of.

With the help of advanced analytics and AI, it is now possible to personalize the patient’s journey and provide actionable intelligence to the Patient Services team for proactive interventions to drive optimal health outcomes. For example:

• AI can help identify key drivers of therapy discontinuation and “never-start” patients
• Turnaround time metrics can help identify any bottlenecks across the patient care continuum

Role of Advanced Analytics (AI Solutions) in the management of Patients and Caregivers

Capturing the holistic experience of a patient can be a challenging task for Pharma companies as there are multiple channels and touchpoints – Support centers, Clinics, Pharmacies, Insurance, caregivers, HCPs, Trainers, etc. For meaningful results, it is imperative to aggregate all this information that is received from the variety of data sources and create a holistic 360° view of the patient journey – to analyze the overall patient experience and inform the patient outreach strategy.

Over the past years, at Tiger Analytics we have collaborated with leading Pharma companies to answer the most pertinent questions in the Rare Disease treatment space in order to design a framework for the holistic 360° view. These questions can be categorized across the analytics complexity spectrum:

1. Descriptive Analytics

a. What is the size of the treatment program?
b. What are the discontinuation and never start rates?
c. How do they change over time?

2. Correlations /Explanative Analysis

a. What are the key drivers leading to discontinuation of therapy?
b. Is there a correlation between continued financial aid through copay programs and time on therapy?

3. What if Analysis

a. What if we decrease our copay support?
b. How elastic is the shipment metric w.r.t size of co-pay support?

4. Predictive Analytics

a. Can we predict who is most likely to drop off therapy?

5. Prescriptive Analytics

a. What are some of the actions to be taken by Field Service Managers?

A major multinational Pharma company chose us at Tiger Analytics as their AI partner to enable them to become a more Patient-centric organization. Through our bouquet of AI interventions, we helped create a 360° view of patient experience to enable the leaders in Patient Engagement & Experience teams to keep a pulse check on the various patient outreach programs and monitor their operational efficiency.

How it works

The Tiger Analytics team provides end-to-end data and AI solutions to empower the client team in answering the above complex business questions. Our solution leverages various data feeds received from multiple touchpoints – HealthCare Prescribers, Insurance providers, Pharmacies, Patient demographics, etc. These data inputs are then transformed into actionable insights where we combine our expertise in Data Engineering, Data Science, App Engineering, and BI reporting, and to further deliver to our client tangible outcomes via continuous improvements through end-user feedback.

With the help of our team of Data Engineers, Data Scientists, and industry experts we develop capabilities and roadmaps for the analytics journey for Patient Services and other associated functions. The analytics support provided by Patient Services organizations is of great benefit to Patient Service Managers, Account managers, Therapeutic Area leads, and other associated functions like Patient Engagement, Vendor Management, etc.

With the foundational pillars and analytical capabilities in place, any Pharma company can therefore make a shift from just being a drug provider, to a support system and care partner, offering patients of rare diseases and their caregivers much-needed support during their very difficult patient journey.

Source:

The future of treating rare diseases | World Economic Forum (weforum.org)

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