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Blog, Comment & Insight

For Pharmaceutical Marketing Analytics

Driving Pharma Value with Digital Transformation

Posted by Dr. Andrée Bates | Nov 27, 2017 8:38:04 AM

The area with the most venture capital in start-ups is AI powered digital health. Pharma companies also are investing a lot in these areas but are clearly finding it difficult to keep up with all the changes. On the one hand we see numerous pharma companies aiming at digital transformation, and then we see those same companies using outdated technologies or un-strategic piecemeal approaches.

It is understandable that because the changes currently happening are in a logarithmic scale with big data, AI, mobile, cloud computing, internet of things, sensors and more and it may be difficult to keep the pace. However, it appears many pharma are going about this in a piecemeal way and finding it difficult to know what trends will last and be disruptive, and transformative, and which are fads. I was in a meeting recently when a company was discussing moving to Hadoop as a platform when anyone in tech is already considering Hadoop old technology due to its’ failure to deliver and have moved onto Kafka or Spark some time ago. Bobby Johnson ran Facebook’s Hadoop cluster many years ago stated “the fact that Hadoop is still around is a "historical glitch.” This just illustrated how Pharma lack of speed of adoption is leaving them behind and out of date. Although many in pharma are aware of the disruptive potential of AI and digital health, and are experimenting with options, most appear to find it difficult to know what initiatives are going to create the strongest business results, and how to scale up quickly and adapt quickly to changes.

 

To start considering what is the optimal way to go about this, one needs to consider the factors that will change healthcare to stay ahead of the curve.

1. Focus on Outcomes

The need to demonstrate superior patient outcomes in the real world and the value of a drug is critical to both market access and retention of market access. Ways Eularis work in this area is utilizing the power of big data and AI to customize dossier applications for success to both speed up reimbursement ensuring faster access, as well as using beyond-the-pill solutions which wrap the drug in services that assist patients and ensure superior outcomes (for example predicting patients who will cease adherence in advance and implementing approaches to avoid that outcome).

2. Patient Engagement

Patients today are taking more initiative for control of their health than ever before due to the availability of information and online apps and tech available. One survey showed that more than 85% patients were confident in their ability to take responsibility for their health and knew where to access apps and resources to help them. Pharma need to be considering the patient flow and patient journey and understanding what patients need at each stage of their journey and providing resources to engage patients at each stage as they make health decisions. This will play an increasing role in the patient decision. Eularis work in this space by utilizing next best action modelling to serve up the right next content, in the next best digital channel for that individual patient to move them along their journey in an optimized way.

3. New Competitors

I have discussed this for many years but now it is clear that many non-traditional companies are moving into pharma as well as health. Google have made no secret of their work in genomics. Apple and Amazon have moved into both healthcare and drugs in various ways also. These companies tap into big data with AI and link these to EHR and claims data to deliver clinical support and soon that will include drugs. What they are doing, pharma themselves could do, if they gave a little more innovative thought to the process.

4. Greater Access to Information

The information from the internet, apps, online communities and social media, means that access to healthcare information has never been more readily or easily available. Even access to physicians is now virtual with new companies that allow an immediate physician virtual consultation. Discussions and both accurate and inaccurate information about your drugs is happening everywhere without your input despite you being the authority on your products. Pharma can use the power of AI to build the capabilities to both identify these in real time and react to them in real time to correct misinformation with evidence in the most appropriate and compliant way.

5. Process Efficiency and Speed

Pharma companies need to utilize technologies to make their business processes more efficient. Ways Eularis are doing this for our clients is automating clinical trial reports, automatically creating optimized drug dossier compilation for faster reimbursement, automating multichannel marketing for mass personalization for greater impact, creating automatic identification of Key Opinion Leaders (KOLs) and up-and-coming KOLS of the future and a whole lot more.

So what does this mean for where Pharma should be focusing to drive value? 

Some obvious areas are automated and optimized market access dossier submissions and pricing – both driven by AI – for faster access and value pricing for optimal profit, personalized patient and physician sales and marketing based on AI powered insights for optimal customer engagement and sales results.

One of the powers of AI is to personalize at scale. By combining all the big data on customers (patients, physicians or payers) we can identify what they need and want, even before they themselves know. This ability to personalize all interactions is a key driver of value in any industry and certainly in pharma. One of the advantages we have in pharma is the increasing use of sensors and apps for health from sensors injectables and drugs to diabetes app sensors and more. We already have access to all this information. For example, Eularis have data deals for patient information from app providers in many therapy areas including diabetes, respiratory, cardiovascular, oncology and more. By integrating this data and analyzing it in real time we have the potential to influence patient health outcomes while developing a stronger more valuable relationship with the customers via beyond-the-pill services where the drug is only one part of the offering. We can automatically monitor various aspects of a patients’ health from drug ingestion to smart watch signals and send automated helpful services where relevant or send reports to their physician that fit automatically into their EHR and alerts to their physician if urgent treatment is needed. For physicians we can more deeply understand why they make the prescribing decisions they do in different patient situations, and automatically identify patient prescribing opportunities in advance by linking lab and patient population data with claims data and physician data so we know when a patient has got results that mean a decision to prescribe a drug in our class is imminent for an individual physician so our rep or other NPP can be delivered with what the physician needs to know at that time.

Another example of personalizing at scale is for rare disease. We have been able to successfully identify undiagnosed rare disease cases using AI in two different ways. One using face recognition and letting it loose online to identify patients from photos online (click here to read this case study). . Another from mining medical records to find patients with the exact symptom match for specific rare diseases. In fact, we could also do this to identify patients for inclusion in clinical trials.

Other personalization can be done through sales and marketing with next best action modelling. We now have access to enough data to be able to truly personalize the patient or physician NPP and sales rep experience so that the customer accesses the content and channel and frequency that they want, when they want it.

In all these cases, although drugs are still part of the equation, the key to maximizing both patient outcomes and pharma profit is personalization to the individual needs of each customer when they need it. By combining data from EHR, lab and diagnostic results, and other data and analyzing with AI we can identify and predict success patterns to drive forward results for both our customers and our product and company.

So many options – where to begin.

The way to figure out what to do has to be driven by strategy.

Many digital teams within pharma do various piecemeal initiatives which are rarely driven by the company or brands strategic needs and therefore, despite being ‘cool’ they are not delivering real financial results.

To deliver real financial results, companies are well advised to plan the roadmap for their AI starting with their challenges and objectives and planning what would be the optimal way to meet these, rather than starting with a project for the sake of it. Another point to remember is that these projects take a lot of high level expertise to deliver this kind of value. They are not quick and cheap instant projects. For real results, the real work has to be put in. One reason Eularis get the kinds of results we do is that we do these projects properly and thoroughly and do not use a one size fits all approach. Each brand and company has different needs and different challenges and objectives, and different data accessibility depending on the country. However, with expert thorough planning, real (and significant) financial results can be met while engaging and optimizing each customer interaction.

For a confidential discussion on how your company or brand can achieve strong results from AI, contact us at Eularis (http://www.eularis.com)

Topics: Marketing Insights, Business Analytics, Digital Marketing, Digital Innovation, Big Data

Written by Dr. Andrée Bates