HOW EULARIS HAVE ACCELERATED OUR CLIENTS GROWTH

How We Helped Clients with Clinical Trials

Clinical trial patient recruitment – Sometimes it can be difficult to find patients with rarer conditions or specific biomarkers for participation in clinical trials. Eularis solved this challenge using big data to find these patients for our client trials.

Clinical trial document redaction – Due to disclosure requirements and privacy laws, all personal data (PD) relating to patients, study administrators, and any other individuals named in the reports and company confidential information (CCI) had to be redacted or blacked out prior to publication for disclosure and transparency requirements. AI can be configured to automatically identify Personal Identifiable Information (PII), PD, and CCI the same way a human would be trained to identify them. The process of identifying and redacting sensitive information therefore becomes automated and significantly more accurate. Layered on top of the technology is a team of domain-specific experts. The client internal redaction team performs a thorough quality control (QC) review of each and every document, ensuring the highest level of accuracy. Findings and resolution of findings are documented on a quality review checklist form and are then seamlessly integrated into the system and used to refine the accuracy of the tool in real time.

Clinical Study Report (CSR) writing – It can take an internal team 4-6 weeks to write a regulatory-compliant CSR and take around 250 hours of team time and cost around $25,000 of internal resources for each one. By creating AI to write CSRs we can complete a CSR that is 80 – 90%complete in less than an hour after it is programmed saving time and avoiding additional delays to get the drug to market.

Faster time to reimbursement – By using a combination of AI techniques Eularis can identify the factors affecting time-to-reimbursement for newly launched medicines post market approval, as well as provide insight into what to include in, or leave out of submissions for formulary inclusion and find other important considerations and insights that have worked in the past to accelerate time-to-reimbursement by formulary or country body

How We Helped Clients in Market Access

Pricing –Eularis can evaluate outcomes and perceived value from real world data, even while in clinical trial stages, to model price elasticity and price/volume trade-off to determine profitability and uptake from different price points to optimize your launch market access.

Faster Reimbursement To ensure financial success of a drug, one needs to understand and incorporate the real payer drivers (for each payer influencing the decisions) in your strategy for each stage of development and commercialization. Eularis can use sophisticated AI techniques, you can develop the submission documents utilizing both the drivers for that formulary as well as the optimal language shown in previous submissions to work best for that formulary committee.

Faster Insights for Market Access Analytics Teams

Eularis can implement AI solutions to create an integrated, clean, big data source, then AI can be applied to create rapid answers automatically.  The platform is layered with Natural Language Processing (NLP) so the queries could be put in as one would ask a human. What used to take up to a week to analyze was reduced to 15 mins in the automated platform. On top of that the answers are also in visualizations as well which meant they were game ready for executive presentations as well. This system was described by one team as ‘game changing’ as after implementation 70-80% of queries were automatic leaving the analysts time to focus on where they could add value (rather than repetitive calculations) and deliver insights that are game ready for the Heads of Divisions.

How We Helped Clients in Sales and Marketing

Go-to-Market Planning

As every pharma marketer knows, the first 6 months are critical for the success of 85% of pharma products. In fact, within 12 weeks’ post-launch, the ultimate sales of the brand can often be predicted. Since you want to give your product launch every opportunity for success, the pre-launch months are crucial for understanding and shaping the ways in which your new product can be most profitable. Big Data, AI and Machine Learning can ensure you’re making the best data-driven decisions for your go-to-market strategy. 

Brand Growth

Eularis supports pharma brands and company growth in multiple ways using Artificial Intelligence powered analytics and tools to ensure you are data-driven and maximize competitive advantage and results. We determine the best choice of approach for our clients after a thorough situational analysis of the market, brand and competitors, the data available, and a business value assessment. Each brand portfolio and situation require different approaches to succeed. Some of the approaches we have planned and implemented include, but are not limited to:

Earlier patient diagnosis – In conditions in which it can be difficult to diagnose a patient for a primary care physician due to the symptom complex, Eularis use AI to assist the physicians make an earlier diagnosis in order to ensure speedy treatment which is essential in conditions in which irreversible damage occurs without early treatment.




Patient flow – Patients move through a diagnosis and treatment process in a unique way. AI and machine learning maps patient flow from real world data (e.g. claims data and EHR data) to identify the real and granular relationships between symptoms, tests, treatment choices, changes, and decisions.



Market structure – Using big data we evaluate the market landscape including disease overview, market dynamics, patient journey, customer understanding (both patient and physician), future trends and opportunity identification. Using big data and AI for this offers the added advantage of real time data feeding in and therefore allowing observation of the dynamic changes as they happen.



Key Opinion Leader mapping/ Influencer mapping /Thought leader mapping – By utilizing AI to map opinion leaders we can identify much more accurately who is critical t develop relationship with (including who are declining in influence and who are up-and-coming influencers). This approach allows real time updates to networks and means you can access continuous insights, and allows identification of the physicians for different aspects of the company including for early stage development, clinical development, medical education, sales and marketing and medical science liaison (MSL) activities.


Segmentation & Targeting – Using AI to segment physicians allows a more comprehensive approach to segmentation rather than the traditional decile approach. Targeting the doctors who are most likely to prescribe new drugs in this therapeutic area, AI and machine learning can laser target the right targets for your new drug. 



Quantifying the Customer Value Proposition – What is your unique and compelling value proposition? How does it differentiate from alternatives? What do you deliver that is superior to alternatives and something the customer can’t get from another brand? What is the perceived value experience you deliver your customers?



Positioning –All pharma products have something great clinically, but it is not enough to win a strong position in many cases. These days positioning has more to do with customer attitudes toward a product than the product itself.  Now with big data and AI we have access to a 360 view of the customers and therefore can combine facts with feelings to define a victorious positioning strategy. 



Messaging – Developing overall messaging in line with your value proposition while delivering customized individual messages for your targeted audience to improve their customer experience and help keep them engaged is now possible with big data and AI.



Precision Physician Targeting – Use AI to target the physicians who are most likely to be converted to prescribing your drug. AI laser targets the right physicians for your sales and marketing.

Predicting doctor switch and how to retain them – AI and machine learning can predict whether a physician will be switch to or away from your brand. This insight can help pharma marketers spot potential problems before they occur and keep customers engaged.



Identifying individual messaging for individual doctors – The right messaging is essential to attract and retain doctors. AI can help pinpoint the key concerns so they’re addressed succinctly to make your sale force effectiveness unsurpassed.



Creating custom details in real time for individual doctors – Imagine the power of receiving a personalized message tailored to your needs, at just the right time for decision making. Increasing sales force effectiveness has never been so easy with the help of big data and AI.   



Predictive Patient Insights – AI and machine learning can predict whether individual patients will stop adherence to their drug in advance of the event. This insight can help the patient adherence teams know what is needed to retain adherence for specific patients. This is especially useful for drugs with nurse liaison or brand ambassadors or helplines for the patients. 



Omni-channel Marketing – Statistics show that 60% of adults use at least two devices every day. Whether it’s timing, the task or desire for a larger screen/keyboard, it is a common phenomenon to start a search on your Smartphone and finish the task later on your desktop. Your real goal is to provide your customers with a seamless experience irrespective of device. As you know, the customer journey typically consists of 20-30 touchpoints with a brand before prescribing or purchasing. Successful marketers add value to the customer at each touch point – no matter the device — and provide a strong and cohesive experience across devices. Using big data and AI, Eularis can help you create the perfect real-time, omni channel experience.



Next Best Action Modelling – By using the power of big data and AI next best action modelling allows marketers to offer up the best messages and content, in the right channel, in the right sequence at the right time for each individual customer. This both magnifies the customer engagement while leading the customer rapidly through the customer journey to your brand.



Marketing Mix Optimization and Resource allocation – Which channels are most effective and which add no value for your target customers? AI can develop and refine your marketing mix allocation to maximize the results of your spend.

Rare Disease Patient Identification – Using big data and AI, Eularis have successfully identified rare disease patients online, and led them to self-diagnose and seek out the available treatment.



Beyond the Pill – This idea references offering more than just the drug itself, so to create complementary services and solutions to the drug to help their customers – and diversify revenue sources. These programs is gaining traction due to the realization that medicines alone may not achieve the clinical outcomes which are required in the current payer environment. To date most of these have been more ancillary services than real beyond the pill offerings. However, today, with all the big data available about customers (both patients and physicians) from sales force data to social media data, browsing data, wearables data, sensor data and more, pharma can now integrate that data to design customer centric programs that offer more value to their customers than the pill alone.  If your programs are solving greater challenges for the customers, they themselves can become a powerful reason to choose your brands.

Channel Focus and Allocation – Which channels can you best reach your target customers? Where do they prefer to engage? How can you identify which channel combinations are best for which customers? Big data and AI deliver this insight.

The data is there for your successful pre-launch marketing plan. Our AI technology and skilled pharma industry experts can help you make sense of it.