Webinars

Life Sciences companies are grappling with the huge impacts that the global coronavirus pandemic is creating for day-to-day lives, health systems, and the global economy. Countries and localities have instituted travel bans and social distancing mandates, including closing non-essential businesses, to help contain the spread of the virus. In-person access to healthcare providers has been limited to just patients seeking treatment. While some of these measures are likely shorter-term in nature, experts are predicting longer-term impacts throughout 2020.

Pharma companies, and their sales forces in particular, are seeing huge disruptions. Access to health care providers is reduced or eliminated in much of the world, sidelining sales reps from their normal personal promotion work. Companies are grappling with how to proactively manage these key employees (and this key asset), considering the full sales operations landscape and incentive compensation (IC) plans, during these unusual circumstances.

In this webinar session, Axtria will:

• Provide an overview of how COVID-19 is disrupting the sales force and impacting all sales operations areas, with a focus on IC.
• Discuss the key objectives sales operations leaders are focused on when considering IC changes, including employee safety, sales force engagement, and effective use of IC budgets.
• Look at the IC levers available to sales operations leaders while managing the impact of COVID-19 from a short-term, medium-term, and long-term perspective.
• Review some of the commonly used tactics and strategies that pharma companies are embracing in these unprecedented times.

Presenters:

• Asheesh Sharma, Head Commercial Excellence, Axtria
• Daniel Stewart, Director, Axtria
• Abhijit (Abhi) Paul, Director, Axtria

Pharma companies are evolving to deliver a true omnichannel experience to their key customers. While it is crucial to develop both a personal and non-personal engagement plan for a multichannel strategy, a vital missing component is to connect next-best interactions and associated messaging across channels to create a harmonized omnichannel experience.

While a rep promotes his/her brand to an HCP, it is not common for the rep to discuss the brand’s digital presence, such as a published whitepaper or upcoming webinar to ensure prescribers are on-board digital channels. On the other end, brand marketers make considerable investments to engage customers using non-personal channels, but have no direct influence or control on the personal channel.

In this webinar series, we will review key challenges of interweaving personal and non-personal promotion to build an omnichannel customer engagement strategy. We will discuss ways to leverage AI/ML techniques to mine insights from complex and messy data and convert these insights to next-best-actions (NBAs) for sales professionals and other marketing channel providers. We will examine digital analytics KEY performance metrics and share an example of how these can be optimized for an email campaign for HCPs or patients. We will also showcase pharma industry-based case studies covering: customer journeys (across multiple digital channels, the journey analytics, and its impact on CX), and the power of AI/ML-based NBA suggestions in enhancing CX.

Part 2 will be focused on operationalizing omnichannel marketing.

Presenters:

• Devesh Verma and Geeta Padbidri, Axtria (Part 1)
• Robert Mozenter and Ilker Oruc, Axtria (Part 2)

Pharma companies are evolving to deliver a true omnichannel experience to their key customers. While it is crucial to develop both a personal and non-personal engagement plan for a multichannel strategy, a vital missing component is to connect next-best interactions and associated messaging across channels to create a harmonized omnichannel experience.

While a rep promotes his/her brand to an HCP, it is not common for the rep to discuss the brand’s digital presence, such as a published whitepaper or upcoming webinar to ensure prescribers are on-board digital channels. On the other end, brand marketers make considerable investments to engage customers using non-personal channels, but have no direct influence or control on the personal channel.

In this webinar series, we will review key challenges of interweaving personal and non-personal promotion to build an omnichannel customer engagement strategy. We will discuss ways to leverage AI/ML techniques to mine insights from complex and messy data and convert these insights to next-best-actions (NBAs) for sales professionals and other marketing channel providers. We will examine digital analytics KEY performance metrics and share an example of how these can be optimized for an email campaign for HCPs or patients. We will also showcase pharma industry-based case studies covering: customer journeys (across multiple digital channels, the journey analytics, and its impact on CX), and the power of AI/ML-based NBA suggestions in enhancing CX.

Part 1 will introduce a omnichannel customer engagement paradigm.

Presenters:

• Devesh Verma and Geeta Padbidri, Axtria (Part 1)
• Robert Mozenter and Ilker Oruc, Axtria (Part 2)

With more and more specialty pharmacy products being launched (and in the pipeline) utilizing a combination of sophisticated distribution, complex dosing & administration, and high cost and high touch patient services requirements, the reliance of pharmaceutical manufacturers on specialty pharmacy is only getting stronger.

Understanding the payer’s influence on patients access and adherence to medications is also becoming increasingly important as various payers look to implement utilization management tools for high cost medications; this can significantly impact not only the patient’s brand experience but also the overall utilization of the medication.

It is more critical than ever for analytics teams to understand the power and control that payers are having on their brands, and which policies can hurt or help them in the marketplace. Rising pressures on margins have led to the prioritization of predictive analytics, as organizations look for insights to support commercial decision making.

Join this webinar to hear how one organization created a process for connecting BIN/PCN/Group Identifiers to unlock payer information and connect data sources to create a holistic data mart. Hear their case study and understand actions taken by one organization to:

• Analyze copay card buy downs by plan
• Make impactful decisions on payer contracting
• Develop refined forecast models

Presenters:

• Ashwin Athri, MBA, SVP, Commercial Data Management, Precision Xtract

This webinar will focus on breaking down the social construct in pharmaceuticals regarding the necessity of silos. The presentation will begin with a summary of silos and the types of silos that exist, both internally and externally. The pros and cons of building silos in the first place will be discussed From there, problems with silos are presented. Patrick Lencioni described silos as “a waste of resources, (that can) kill productivity, and jeopardize the achievement of goals.”

After learning about silos and the dangers they present, advice on breaking them down, and the benefits of doing so, will be presented. The presentation will then discuss creating synergized, multichannel silos that work together and benefit each other. Such silos look at stakeholders and analyze the interactions of multiple channels. Due to the synergy of multiple channels instead of direct, top-to-bottom approaches, multichannel is a more efficient implementation of silos in the pharmaceutical industry.

Presenters:

• Mitchell Krassan, Chief Strategy & Performance Officer, TherapeuticsMD

Oncology has become one of the top therapeutic areas for the pharmaceutical and biotechnology industries and global spending is expected to approach $200 billion within the next 3 years. The industry must contend with a variety of elements that are increasingly complex including rapid changes in treatment standards and pathways driven in part by assimilation of new technologies and biomarkers. Forecasting design and development considerations for oncology were discussed in a prior webinar.

In this follow-up webinar, we will discuss data sources to support epidemiology-based oncology forecasting approaches. Data will be reviewed in terms of publicly available sources to address unique elements of oncology forecasts including epidemiology data, staging and treatment data. Additionally, securing and integrating data related to patient subsets and survival proxies will be discussed and examples of how to review, vet and integrate data will be reviewed. Live examples using SEER data will be demonstrated and challenges for alignment between data sources will be discussed. Examples of a health system epi-based model constructed using data inputs for staging, treatment, patient-subset and regimen-based progression curves will be demonstrated.

Presenters:

• Bernie Manente, Foster Rosenblatt and Xin Hang, Senior Director, Foster Rosenblatt

Oncology has become one of the top therapeutic areas for the pharmaceutical and biotechnology industries and global spending is expected to approach $200 billion within the next 3 years. The industry must contend with a variety of elements that are increasingly complex including rapid changes in treatment standards and pathways driven in part by assimilation of new technologies and biomarkers. Forecasting in this complex environment can be fraught with many pitfalls and choosing the proper approach is driven by a number of considerations related to your product, your oncology portfolio and your organization.

In this webinar, we will demonstrate considerations for developing forecasts for oncology therapeutics. Attendees will learn from real-world examples how to utilize best practices for forecast development and discuss the options for securing data to support the alternative approaches. Additionally, we will discuss elements that can have the greatest impact on forecasts and offer guidance on how to secure internal alignment on these forecasts.

Presenters:

• Bernie Manente, Foster Rosenblatt

Pharma organizations are undergoing changes where the focus is more on transformative medicines catering to unmet need and on smaller agile R&D cycles. Tackling a complex ecosystem of patients, providers, payers, and regulators among other entities requires organizations to strengthen their predictive modeling capabilities. Traditional predictive modeling can be complemented further through application of System Dynamics, Networking Modeling, and Simulation. These models enable future insights while utilizing historical behavior, provide the ability to incorporate real-world feedback instead of reliance only on linear cause-effect relationships, and account for a more exhaustive set of parameters that capture customer interactions.

Various industries are utilizing these System Dynamics and Network Modeling techniques to enhance models for product launch, market mix, and ROI optimization, among others. Pharma companies can benefit from these methods to improve their commercialization effectiveness across similar problem areas. One such instance is where we helped a pharmaceutical company leverage system dynamics to model the effect of a biosimilar launch on the market share. Being able to simulate the impact of a biosimilar launch made the organization more proactive and nimble in modifying strategies. In this webinar, we will look to answer two key questions:

• How have network modeling and system dynamics been applied by pharma and organizations across other industries to drive business value?
• How can these techniques help pharma commercialization teams tackle the uncertain and complex ecosystem?

Presenters:

• Sridhar Turaga, Head of Technology, Mu Sigma Inc.

The pharmaceutical industry today is evolving to develop patient experience as a core dimension when bringing new drugs to market. Shifting patient expectations combined with innovative technologies will have a dramatic impact on drugs and healthcare in the coming years. To cater to shifting trends, pharma companies are now turning towards patient data to power their decision making.

Real world data (RWD) accounts for 95% of the patient data, as opposed to the meagre 5% covered by clinical trials. Pharma companies are spending close to 20 Million USD annually on generating RWD-based insights. However, data fragmentation and non-standardized formats across RWD sources – coupled with incomplete and/or inaccurate data capture – raise concerns on the quality of RWD. In once such instance, the challenge was with low coverage of a key biomarker in one data source (<10%) while the coverage was better in another (>50%). We improved the coverage by experimenting with techniques such as Random Forest and Neural Networks to predict the values of the biomarker in the low-coverage dataset.

Parallelly, there is a boom in machine learning (ML) being used for data quality processes, which can aide stakeholders in overcoming the obstacles faced in the consumption of RWD. Various ML/DL algorithms can be implemented for the imputation of missing data, prediction of variables completely absent in a data source, and detect anomalies, thereby improving the completeness and accuracy of data. Effectiveness of the methods is measured through a combination of accuracy parameters, benchmarking against results from industry standard publications, and improvement in the number of potential studies. Through this webinar, we’ll be exploring:

• What are the challenges in using Real World Data for product commercialization?
• How can ML algorithms be leveraged to improve the quality of RWD sources?
• What are the RWD elements (such as biomarkers) that could enrich a study based on patient data?

Presenters:

• Bingcao Wu, M.S, Associate Director, Real-World Market Access Analytics, Janssen Scientific Affairs
• Siddhant Deshmukh, Engagement Manager, Mu Sigma

Diseases like NASH traditionally require an invasive liver biopsy to positively identify patients. When no therapies exist on the market, healthcare providers often hold off on performing a biopsy, resulting in a significant number of undiagnosed patients. By harnessing large clinical encounter data sets, we can begin to understand the patient populations at each stage and severity of disease, leading to better guidance of treatment development and delivery.

Presenters:

• Dr. Aswin Chandrakantan, Chief Medical Officer & SVP Corporate Development, Komodo Health