A “new normal” for analytics in oncology
Innovation is necessitated by defining aspects of the post-pandemic market landscape.
By: Christina Corridon, Deepika Sinha and Jeevarasan Elanchelvan
The oncology landscape continues to be in a state of constant flux — with significantly high growth complicated by crowding, innovation in modalities and expanding patient care continuum but at the same time stark socio-economic and racial disparities. These and many other trends in oncology warrant us to rethink or rather reimagine analytics. Analytics that not only supports or informs business decision-making but revolutionizes business outcomes. Join us in our journey to explore the new age of oncology analytics to address these oncology trends.
High intensity competition
The oncology space has had over 50 launches in 2022, despite a slowdown accompanying the pandemic. In the coming years, the space will grow more crowded both in terms of products and companies. With competition so fierce, businesses need to identify ways to outperform and differentiate themselves. This can be facilitated by building the right customer engagement model, enabling digital and elevating patient services:
· Personal, and non-personal engagement channels should be leveraged in a coordinated fashion to provide an optimal customer experience. Multiple established and emerging clients have implemented orchestrated journeys across omni-channels, leading to a maximum of ~2% lift in sales
· Patient identification, onboarding and adherence should be streamlined by leveraging machine learning (ML) and real-world data (RWD) to capitalize on commercial opportunities. A significant number of patients — three to four times — who were undiagnosed previously with the rare conditions have been identified in RWD as having symptoms of the said rare condition by using solutions that leverage ML techniques
· Long-term data strategies should include real-world evidence and patient outcomes
CAR — Ts and gene therapies: The next wave of innovation
Chimeric antigen receptor T-cells (CAR — Ts) and gene therapies offer the potential to be game changers in the next wave of innovation in oncology. Most CAR — Ts and gene therapies are in the early stages of their commercial lifecycle — currently, there are less than 10 CAR-Ts approved. With over 60 approvals expected in the next five years across multiple types of CAR-Ts and gene therapies, ZS has built expertise with these novel CAR-T and gene therapy products and companies so that they help clients commercialize these lifesaving products.
Given the differences that exist compared to traditional oncology drugs, some unique analytical use cases have emerged:
· The site selection process for CAR-Ts is different from traditional account targeting and will require an in depth understanding of the market
· Autologous cell therapies are manufactured using patients’ cells and involve a sophisticated and unique supply chain process tracking the journey of the cell therapy from “vein-to-vein”. Supply chain and manufacturing analytics — such as manufacturing yield optimization, logistics operations control tower, dynamic manufacturing scheduling, etc. — can optimize the overall vein-to-vein process. Utilizing supply chain and manufacturing analytics can achieve up to 20% improvement in capacity, and the associated lowering of cost of goods sold
· Education and expertise are essential for all stakeholders in the process. Oncologists need to be educated on the benefits of these therapies and pharmaceutical companies need to better understand the referral patient journey to identify key healthcare professionals to engage
Precision medicine: Evolving diagnostics landscape
Precision oncology holds great promise to reshape the future of cancer treatment. However, utilization across practices remains low. Published results during the American Society of Clinical Oncology (ASCO) 2022 annual meeting, show that liquid-based tests are proving to be as efficacious as tissue-based tests and thereby ease sample collection. Adoption in both clinical studies and real-world settings should therefore increase.
The field of precision medicine is rapidly evolving with the advent of new technologies and an increasing number of biomarker-based approvals. With an increased focus on targeted therapies, the role of biomarkers in the treatment history becomes very important. Due to increased efficiencies, rapid technical advances and increasing cost pressures, there’s an anticipated shift from conventional approaches to highly sensitive next-generation sequencing (NGS)-based applications. Liquid biopsy will continue to evolve, especially with Guardant360 CDx and FoundationOne Liquid CDx receiving approval from the United States Food and Drug Administration (FDA) and coverage from the Centers for Medicare and Medicaid Services (CMS). All of this means there will be increased adoption which will necessitate us to understand the tissue journey of patients.
The major challenge that exists with data today is that lab data is sparse and biomarker information is not present in traditional RWD such as claims. There are two ways to solve these challenges:
· Biomarker testing companies such as FMI, Guardant Health, etc. have records of patients who use or have used their lab tests and kits. Partnerships with some of them can provide real-time alerts on patients who have tested positive for specific biomarkers, thereby providing an opportunity for companies to target appropriate providers to educate them on the advantages of their therapy — improving both patient and commercial outcomes
· Further, by applying ML techniques to claims datasets we can identify up to three times more patients with positive biomarker mutations that were previously unclassified
Social determinants of health: Health equity and outcomes
Research has shown that social determinants of health (SDoH) have a high impact on patient’s health outcomes. Providing equitable healthcare to disadvantaged populations will be important to improving brand perception and ensuring that all patients receive the care they need in the long term, which ultimately is important for long-term business impact. Understanding cancer care disparities and providing equitable healthcare involves leveraging multiple advanced techniques:
· Evaluate gaps in care to allow for prioritization of areas with the highest unmet patient needs
· Determine local strategies to address a prioritized set of barriers that impact communities affected because of care disparities
· Develop a framework to link social disparities across different stages of the patient journey with drivers from secondary data to identify geographies with below-average health outcomes
· Include SDoH factors in clinical trials and generate evidence for all patient types
Multiple studies have shown that SDoH can impact up to 90% of health outcomes. [1] Identifying and improving disparities in healthcare can lead to significant business upside for healthcare companies.
Payer and provider trends
Payer control in both pharmacy and medical benefit products is increasing and there is clear evidence of share-shifts driven by formulary management. Rising payer control is essential to drive value-based oncology care, with providers consolidating and increasing levels of centralized decision-making to maintain economic viability.
Increasing control by both providers and payors has required pharma companies to understand their behavior on product preferences. It’s important to understand the behavior of providers to customize our engagement strategy. Taking a step further, understanding the local dynamics will enable a tailored engagement strategy. Understanding patient treatment pathways is essential for pharma companies to determine and get the ‘standard of care’ treatment tag. It’s also important to maximize the understanding of competitive pricing and contracting strategies available for self and competitors.
Conclusion
We must continue to adapt and evolve to meet the data and market challenges in the oncology landscape. We have touched on the following key aspects above:
· How a densely populated competitive landscape means that a step-up in the sophistication and efficiency of patient identification and the choreographing of field engagements is needed, along with an increase in emphasis on patient experience
· How CAR-T and gene therapies coming to prominence mean a different way of doing things to mainstream oncology, and this needs to be understood by us and our clients alike, whether we’re working with a traditional oncology product, client or not
· How a growing availability of data from biomarker testing companies means new avenues for patient and customer identification, particularly when combined with claims data and ML techniques
· How new knowledge on the SDoH should be leveraged to ensure the best possible patient outcomes across the board to drive commercial success
· How a dynamic payer landscape, showing both payer and provider control growth, means both competitive contracting and pricing strategies need to be understood to be effective in the oncology market
The constant flux of the oncology landscape makes it a fantastic place for advancements in analytical applications. The talking points above are a good start to a critical discussion of oncology today. In this sense, a sharp oncology solution involves us having an ear to the ground and an eye to the future. More concretely, we must contextualize our responses to business problems and continually place them in strategic roadmaps that address the dynamic character of the field.
