What Will The Year Hold for Pharma?

Here are some possibilities for the year.

1. Drug pricing challenges continue leading to increases in generics and biosimilar use in many markets
Drug prices are a popular target when attempting to reduce overall healthcare expenditure. For most primary care drugs there are generics and biosimilars available. As budget issues continue to be a central issue for payers, companies facing generic or biosimilar challenges will need to price for outcomes and value while becoming more innovative in how they approach this. Eularis have helped companies use big data and Artificial Intelligence to find the optimal pricing point for maximum profit to pharma while getting maximum payer buy-in. Eularis also use big data and AI to price for biosimilar entry.

2. Artificial Intelligence and tech integrated more into pharma
Tech in terms of molecular engineering and gene editing (think CAR-T and CRISPR-CAS9) have had impressive developments leading the way towards eliminating conditions like Muscular Dystrophy and Cystic Fibrosis and making significant strides in personalized cancer treatment. Now with blockchain being integrated with health records and big data and AI being implemented from discovery to R&D to clinical trials to sales and marketing, we are looking at the future which has already begun changing approaches and results.

3. Growth in non-traditional pharma competitors
We have already seen companies such as FujiFilm, Google, Amazon and Apple all making more and more inroads into the healthcare market using big data and AI to enable their progress. Companies that are innovating will soon force big pharma to change their current outdated business models if they wish to sustain competitiveness.

4. More focus on specialty drugs
For many decades pharma companies focused on diseases that affected large populations to ensure return on their heavy investment required to get the drugs to market. Now that means that those markets are hypercompetitive (think antihypertensives!) and therefore difficult to make strong returns. Now companies have replaced this focus into the next big thing – specialty pharma and rare diseases. They have less competition (if any in many rare disease cases) and therefore are more lucrative than hyper-competitive mass markets. Artificial Intelligence is perfected suited to rare diseases as finding rare disease patients is like finding a needle in a haystack – something AI is perfectly suited to and something Eularis have had great success in.

5. Personalization and Omni-channel increase
Several sources, and personal experience, show that 60% of adults use at least two devices every day. It is a common phenomenon to start a search on your Smartphone and finish the task later on your laptop or desktop. Cross-device connection isn’t that difficult these days, yet it’s a powerful customer-centric approach that meets your customer where they are in their customer journey. As a marketer, your real goal is to provide your customers with a seamless experience irrespective of device, channel and content i.e. always on, always right, always valuable omni-channel marketing. Take this idea in combination with personalized multi-channel marketing and you get Next Best Action Modeling. You could think of Next Best Action Modeling as a customer-centric approach that helps your customers take the “next best action” after they complete one action. It’s similar to Amazon’s recommendations – since you bought x, you may also be interested in y. When done well, it’s incredibly powerful. Next best action modeling changes the paradigm. Instead of finding the next customer, it focuses on finding the best proposition for the customer to add value to them and be relevant for what they need at that time. This is a customer rather than product focused approach and it treats each customer as an individual person within the context of their individual behaviors (past and present), needs and preferences. Eularis has used Next Best Action Modeling as part of several projects. The foundation of NBA is a combination of data and advanced AI (artificial intelligence) modeling to ensure that the most likely outcome is predicted from a set of interactions with a customer or customer segment. To be successful, it needs to be well-planned.

6. More M&A
When one examines both the patents expiring over the next decade (around $17 billion will be lost to pharma companies) and the serious amounts of debt many of the top 20 pharma companies find themselves in currently, the ground is fertile for pharma take-overs. My first thought was Google and Amazon or even Apple taking them over but in reflection, why would they want to be saddled with them when they can built a better business model version from the ground up more effectively. Amazon is probably the most likely to be the winner in healthcare now that they have entered the pharmacy space as well. We predict that both BMS and Astra Zeneca will get acquired (probably by other big pharma such as Roche), but Teva, a once strong option, is another strong bet with $35 billion in debt on its balance sheet in the coming few years.

7. Growth in China
One hears a lot about growth in Asia but most of this is driven by China. China is already around 25% of the global healthcare market and this is growing. The government are focusing on a Healthy China plan which aims to transfer more from government to private insurers and the ongoing vast increases annually in population mean health will become even bigger business in China.

If you need help with solving challenges with big data and Artificial Intelligence that you have been unable to solve with traditional market research and analytics, be it faster reimbursement, value pricing, clinical trial recruitment, personalized omni-channel and multichannel marketing, custom sales messaging, identification of up-and-coming key opinion leaders (KOLs) or something completely different, contact us to discuss whether your challenge is one suitable for an AI approach. Eularis specialize in big data analytics in pharmaceutical industry and have experience solving many challenges in this space.