Differentiating Oncology Research Pipeline in Today’s Competitive Era
Visit our latest blog here for our latest discussion around how real-world data is powering advancements in Cancer R&D.
By Ciox CEO Paul Roma, Chief Digital Officer Florian Quarre, and VP of Life Sciences Julie Krommenhoek
Big pharma is increasingly doubling down on bets to develop new blockbuster cancer drugs. Currently, approximately 700 organizations have one or more oncology drugs in late-stage development, and 14 of the world’s largest pharmaceutical companies are focusing at least one-third of their late-stage R&D activity on oncology.
Fig: Strong late-stage pipeline of oncology with 710 molecules in 2017, which is up by 60% in a decade from 434 molecules in 2007
With cancer treatments advancing and new innovative treatment types being introduced at warp speed, it’s no wonder oncology continues to remain the most dominant therapy segment, with annual cancer spending rising to $133 billion in 2017. Spend on cancer drugs in the U.S. has doubled since 2012 and reached almost $50 billion in 2017.
Oncology will be the fastest growing therapy area, with 12.7% of CAGR during the 2016-2022 period and sales reaching an estimated $192.2 billion in 2022. Interestingly, spending on cancer medicines is heavily concentrated, with the top 35 drugs accounting for 80% of the total expenditure, signaling a critical need to demonstrate superior effectiveness and gaining rapid traction for early pipeline expansion.
Competition set to grow in the near future
The rapid growth in spending in oncology in recent years is resulting in an increase in R&D expenditures to discover novel cancer drugs.
Pharma witnessed a peak in R&D expenditure, the highest ever since 1980, by spending over 19.8% of their revenues, which adds up to a total spend of over $157 billion in 2016. Oncology as a therapy area enjoys the largest share of R&D investments in Pharma, as compared to other therapeutic areas, with around 4,500 cancer molecules (one-third of the total molecules) under development.
Clinical trial success rate has also significantly increased in oncology:
- Phase I oncology trials had a 23% chance of success in 2012, which increased to a 66% chance of success in 2016.
- Phase III oncology trials had a 40% chance of success in 2012, which increased to a 73% chance of success in 2016.
FDA approvals for NMEs in oncology
|Year||Total NME Approvals||Oncology NME Approvals||% of Oncology NMEs|
Novel therapies being launched
Advances in cancer treatment are occurring rapidly, with more patients surviving cancer than ever before. Patients are receiving the benefits of oncology experts utilizing the most innovative, life-extending therapies that are getting approvals and indication expansions in record time.
With the advent of new immunotherapies and CAR-T / gene therapies, oncology is witnessing an unprecedented era of treatment and care.
Immunotherapy: Immunotherapies gained traction because of their potential to significantly increase a cancer patient’s remission and survival. Currently, over 300 immuno-oncology therapies are in various stages of development, with trials being conducted across 27 different tumor types.
CAR-T / gene therapy: CAR-T, also known as “cancer’s newest miracle cure” has been gaining considerable momentum from pharma companies. In Aug 2017, Kymriah of Novartis became the first CAR-T to be approved by the FDA, followed by Gilead / Kite’s Yescarta in Oct 2017. In May 2018, Kymriah received second approval to treat appropriate r/r patients with large B-cell lymphoma.
New therapies such as Immunotherapy and CAR-T have the potential to treat multiple onsets and a broad array of cancer types. Development of I/O will lead to an increase in the number of oncology products catering to multiple indications, and a consequent decrease in the number of oncology products catering to a single indication only.
FDA’s evolution to enhance and streamline the regulatory process
Key FDA initiatives to modernize and streamline
- Increase in staffing
- Increase in review offices from 5 to 9
- Increase in review divisions from 19 to 30
- Development of multi-disciplinary review teams
- Centralization of review procedures
- Unifying post-market safety surveillance system
- Enhancing the patient’s voice in drug development
In June 2018, the FDA released a statement regarding its plan to modernize the drug review office structure and process. Some of the key points towards revamping are mentioned in this list.
Additionally, in recent years, the FDA has come up with several new pathways through which drugs can be available more rapidly.
- In 2012, the FDA introduced two pathways through which drugs can receive early approvals:
- Accelerated approval and
- Breakthrough therapy
- In 2018, FDA added the Competitive Generic Therapy (CGT) channel
- FDA also introduced a Limited Population Pathway for Antibacterial and Antifungal Drugs
In July 2018, the FDA released the Biosimilar Action Plan (BAP) in order to strike a balance between the innovation and the competition in the U.S. biologics market. The BAP also tends to influence behaviors beyond the FDA’s direct control. The BAP ultimately aims to create a competitive market that would deliver benefits to the patients and the public while providing incentives to innovation in the biologics space. The Biosimilars Action Plan focuses on four areas:
- Improving the efficiency of the biosimilar development and approval process
- Maximizing scientific and regulatory clarity for biosimilar developers
- Developing effective communications to improve the understanding of biosimilars among patients, clinicians, and payers
- Reducing the gaming of the FDA requirements as well as attempts to unfairly delay competition
The FDA’s regulatory revamp, new policies and shifting focus will further support several new types of treatments entering the oncology market:
|1||Wide range of approvals for cancer indications||Keytruda approved for a wide variety of cancers like advanced melanoma, metastatic cervical cancer, non-small cell lung cancer (NSCLC), head and neck, urothelial carcinoma and gastric cancer|
|2||Biomarkers in oncology||In 2017, Keytruda became the first drug to get approval based on a biomarker rather than tumor location; accelerated the approval process for drugs targeting PD-L1 as a biomarker|
|3||Women’s health||Olaparib approved beyond ovarian cancer, targeting patients with certain types of breast cancer|
|4||First-in-class approvals||Kisqali, Spinraza, and Lutathera approved for various first-in-class indications|
|5||Previously delayed approvals being expedited||Stivarga, the first FDA approval for a liver cancer drug in nearly a decade|
|6||Drug approvals benefit from new policies||Arikayce for rare lung disease is the first time a drug is approved under the Limited Population Pathway|
Resultant impact of these combined forces
All trends mentioned above translate simultaneously into an opportunity and competition for pharma companies, depending on how the organization is positioned.
Pharma today needs to compete not only on the basis of the strength of R&D pipelines and treatment portfolios, but also on the outcomes they produce and the ability to demonstrate evidence in a prompt and appropriate manner. The window of opportunity to create an impact is limited, as newer treatments will mature and come to market faster than before, resulting in a greater urgency to demonstrate evidence.
We anticipate four key drivers of new opportunities for pharma in this competitive era:
|New indications||Identifying new indications faster and demonstrating evidence|
|New business models||Risk-sharing|
|New access strategies||Identifying the right patients early in the course of treatment|
|New pricing models||Value-based and differential pricing|
Shifting gears on evidence strategy
All the macro and micro indicators combined to create a perfect storm for pharma to shift gears on its evidence strategy and make it a core focus for differentiation.
Business opportunities empowered with better evidence
Changing approach to evidence
With these new opportunities, there is a shift in data and evidence requirements as well. When it comes to oncology, real-world evidence research demands a Digital Patient Clone™ of the patient to understand deeper nuances and outcomes and, at the same time, a “representative universe” to ensure that the outcomes are reflective of what is happening in the real-world.
Ciox Health believes that the researchers should be in the ‘design seat’ of any aggregated data set. To enable this, Ciox Health curates and refines the criteria to develop a longitudinal view of the patient, thereby helping pharma establish direction of causality. Ciox Health’s mission is to help life science organizations execute vital clinical data-based analyses by quickly and securely sharing the right health information about the right patients, at the right time. Ciox Health can help remove the largest barrier to using clinical data: the digital manifestation of a patient in the U.S. is created in fragments and dispersed across the health care system.
The Oncology Digital Patient Clone™
One novel approach is called the Digital Patient Clone™ construct. Ciox Health has introduced a new method which is defined by the researcher and can be iteratively enhanced with new data elements from existing and emerging data sources as researchers test and refine hypotheses. As oncologists refine their data elements, they build new selection criteria which Ciox Health uses to engage its network and platform to find, acquire and transform data from patients that fit the specific profile.
The oncology digital patient clone and related information exchange platform allow researchers to have access to structured data sets on a project-by-project basis. After researchers test early hypotheses, they can refine and expand the data elements they are interested in, analyzing those elements against the original cohort profile. Ciox Health’s dynamic data model allows the researcher to define new patterns, search with new criteria endpoints and achieve new outputs for clinical models. By introducing this platform, it improves the ability to run ‘big data’ predictive analytics, identifying correlation and causation between cohort populations and subgroups with different risk exposures and characteristics of interest.
Access to such high-quality evidence in the new age of speed and nuance is no longer something that a stakeholder can individually drive effectively (whether it is an academic medical center or an insurer or a technology vendor), as it does not bring in the complete 360-degree view sought in today’s era. It is only when like-minded stakeholders across the entire healthcare spectrum come together with a shared objective of moving the treatment paradigm forward that can we expect this to happen.
We at Ciox Health have recognized this opportunity and developed a clinical information-sharing platform that has the potential to remarkably change cancer research by digitally stitching the patient back together for oncology researchers. With access to digital health records from a health information exchange that covers a large and representative proportion of the patient population in the United States, spanning across the majority of states through a network of hospitals and academic medical centers, we have access to the most in-depth oncology evidence network in the US.
Moreover, we are continuously augmenting this patient network with the addition of new EMRs, patient registries, payer data, and additional sources to enable a complete 360-degree view of cancer treatment like never before.
|Ciox Health Solutions Enables…||…Pharma to Create RWD Vault|
Real-World Data Acquisition
Has a HealthSource platform to expedite the acquisition of consented health data and meet study parameters
Clinical Research Ecosystem
|Continuous Access to Data
By leveraging Ciox Health solutions, Pharma can optimize the use of EHRs in clinical trials and research studies without compromising quality and data integrity
Connectivity to Source
Generate transformational insights from the existing source data through the use of OCR, NLP and Machine / Deep Learning
A standard Ciox Health workflow includes abstracting the data from electronic records in a traditional manner and also conducting a robust validation of study guidelines by clinicians and data custodians to ensure the veracity of the results. Moreover, the ability to rapidly conduct population analytics at an early stage helps validate some of the key assumptions and define the right cohort and outcome definitions. Some of our pre-defined abstraction and NLP packages allow extraction of deep insights in almost near real-time manner like never before. Lastly, the unique consent management set-up within our research network allows for an opportunity to enroll patients for further studies and proactive outreach if required.
The research ecosystem involves a variety of stakeholders and Ciox Health ensures that it functions as a collaborative connection between all the stakeholders for the common goal of helping the patient. Ciox Health serves a large volume of clinical data irrespective of its operational variabilities, still enabling seamless data exchange and compatible data analytics. Moreover, given the tight technical integration and workflow automation, our HealthSource platform compresses this workflow in an unprecedented manner, where research results are ready within just weeks instead of months or years.
Ciox is a health technology company working to solve the clinical data illiquidity challenge, providing transparency across the healthcare ecosystem and helping clients manage disparate medical records. When stakeholders do not have timely access to the complete clinical picture of patients, critical decisions about patient care, medical outcomes research, disease prevention, reimbursement, and payments are sub-optimized.
Ciox’s scale, expertise, expansive provider network and industry-leading technology platform make it the most reliable clinical data company in the U.S. Through its standards-based technology platform, HealthSource, Ciox helps clients securely and consistently solve the last mile challenges in clinical interoperability.