The drug development paradigm is rapidly evolving from its longstanding “siloed” corporate
structure to one based more on partnerships among industry, academia, and the regulatory
agencies. These partnerships take advantage of the individual strengths that have
existed in each sector but reflect the need for enhanced collaboration. In 2016, the
White House Cancer Moonshot brought this need for increased collaboration in oncology
to the public's attention through recognition that in this era of advanced technologies
and rapid accumulation of data, there is not only a need to have knowledge readily
accessible and interactive, but also a need for strategic partnerships among public
and private sectors to allow key in silico, basic, clinical, and population‐based
experiments to be conducted that will advance the field. To help define a national
cancer research blueprint, the National Cancer Advisory Board assembled a Blue Ribbon
Panel of 28 scientific experts and other stakeholders that provided transformative
recommendations to accelerate progress against cancer after consulting more than 150
experts and reviewing more than 1,600 suggestions from the public.1 With strong bipartisan
support, the 21st Century Cures bill was passed by Congress on December 7, 2016, with
funding “to support cancer research, such as the development of cancer vaccines, the
development of more sensitive diagnostic tests for cancer, immunotherapy, and the
development of combination therapies, and research that has the potential to transform
the scientific field, that has inherently higher risk, and that seeks to address major
challenges related to cancer.”2 These new resources will help not only to implement
recommendations of the Blue Ribbon Panel, but also to encourage continued cooperation
amongst academia, government, and industry to develop new partnerships that minimize
the potential of generating additional siloes in the future.
In this issue, devoted to the implications and advances in oncology therapeutics,
novel descriptions of new paradigms for many components of the drug development process
are presented. If advanced appropriately, these partnerships have the potential to
substantially change the way the drug development paradigm is approached. The implications
of success will not only enhance the availability of better oncology therapies available
to US patients, but also make these therapies available to the global community. These
are important approaches that will need to be carefully assessed in the coming years,
but for the moment serve as a new baseline and present an exciting glimpse into the
future. It will be important for organizations, such as the American Society for Clinical
Pharmacology & Therapeutics and its membership, to take the lead in judiciously and
thoughtfully shaping and evaluating these approaches.
EMERGING DRUG DEVELOPMENT PARADIGM AND REGULATORY REVIEW AND APPROVAL PROCESS
Oncology drug development has seen tremendous progress in recent years. With the remarkable
growth in the understanding of the molecular basis of cancer etiology and the development
of novel therapeutic targets, innovative approaches in drug development and regulatory
approval pathways, the US Food and Drug Administration (FDA) has granted significant
approvals of new targeted therapies and immunotherapies (Tables
1
,
2
),3, 4 in addition to biosimilar products.5, 6
Table 1
Selected oncology targeted and immunotherapy approvals since 2013 (adapted from Blumenthal
et al
3)
Indication
Therapy (target)
Anaplastic LCL
Brentuximab vedotin (CD30)
ALL (Philadelphia negative)
Blinatumomab (CD19/CD3)
B‐cell NHL
Idelalisib (PI3K delta)
Basal cell
Sonidegib (hedgehog pathway)
Breast cancer
Palbociclib (CDK 4 and 6); pertuzumab (HER2/neu)
CLL
Ibrutinib (BTK); idelalisib (PI3K delta); obinutuzumab, ofatumumab (CD20); venetoclax
(BCL‐2/17p deletion)
Follicular lymphoma
Obinutuzumab (CD20)
HNSCC
Nivolumab, pembrolizumab (PD‐1)
Hodgkin's lymphoma
Brentuximab vedotin (CD30); nivolumab (PD‐1)
Mantle cell lymphoma, WM
Ibrutinib (BTK)
Metastatic melanoma
Cobimetinib, trametinib (BRAF/MEK); vemurafenib, dabrafenib (BRAF/MEK); Ipilimumab
(CTLA4); nivolumab, pembrolizumab (PD‐1)
Metastatic NSCLC
Afatinib, erlotinib, gefitinib, osimertinib (EGFR); alectinib, ceritinib, crizotinib
(ALK); crizotinib (ROS‐1); atezolizumab, pembrolizumab, nivolumab (PD‐1/PD‐L1)
Multiple myeloma
Carfilzomib, Ixazomib (proteasome); elotuzumab (SLAMF7)
Ovarian
Olaparib, rucaparib (PARP/ BRCA)
Renal cell carcinoma
Nivolumab (PD‐1)
Soft tissue sarcoma
Olaratumab (PDGFR‐alpha)
Urothelial
Atezolizumab (PD‐L1)
Anaplastic LCL, Anaplastic large cell lymphoma; ALL, acute lymphoblastic leukemia;
CLL, chronic lymphocytic leukemia; HNSCC, head and neck squamous cell carcinoma; metastatic
NSCLC, metastatic non‐small cell lung cancer; WM, Waldenström's macroglobulinemia.
Ref: http://www.accessdata.fda.gov/scripts/cder/daf/
Table 2
FDA‐approved drugs with companion diagnosticsa (updated from Pacanowski and Huang
20164)
Drug generic name (trade name)
Biomarker and diseasea
Device trade name(s)
Afatinib (Gilotrif); Gefitinib (Iressa)
EGFR mutations in non‐small cell lung cancer
therascreen EGFR RGQ PCR Kit
Erlotinib (Tarceva); Osimertinib (Tagrisso)
EGFR mutations in non‐small cell lung cancer
cobas EGFR Mutation Test V2 (for both tissue and plasma)
Pembrolizumab (Keytruda)
PD‐L1 expression in non‐small cell lung cancer
PD‐L1 IHC 22C3 pharmDx
Crizotinib (Xalkori)
ALK rearrangements in non‐small cell lung cancer
VYSIS ALK Break Apart FISH Probe Kit, VENTANA ALK (D5F3) CDx Assay
Tramatenib (Mekinist); Dabrafenib (Tafinlar)
BRAF mutations in melanoma
THxID BRAF Kit
Vemurafenib (Zelboraf); Cobimetinib (Cotellic) with Vemurafenib
BRAF mutations in melanoma
COBAS 4800 BRAF V600 Mutation Test
Trastuzumab (Herceptin)
HER2 expression in breast cancer
INFORM HER‐2/NEU, PATHVYSION HER‐2 DNA Probe Kit, PATHWAY ANTI‐HER‐2/NEU (4B5) Rabbit
Monoclonal Primary Antibody, INSITE HER‐2/NEU KIT, SPOT‐LIGHT HER2 CISH Kit, Bond
Oracle Her2 IHC System, HER2 CISH PharmDx Kit, INFORM HER2 DUAL ISH DNA Probe Cocktail
Trastuzumab (Herceptin); Pertuzumab (Perjeta); Ado‐trastuzumab emtansine (Kadcyla)
HER2 expression in breast cancer and gastric cancerb
HER2 FISH PharmDx Kit, HERCEPTEST
Olaparib (Lynparza)
BRCA variants in ovarian cancer
BRACAnalysis CDx
Rucaparib (Rubraca)
BRCA alterations in ovarian cancer
FoundationFocus CDxBRCA Assay‐ next generation sequencing
Cetuximab (Erbitux); Panitumumab (Vectibix)
EGFR expression in colorectal cancer
DAKO EGFR PharmDx Kit,
KRAS mutations in colorectal cancer
therascreen KRAS RGQ PCR Kit, cobas KRAS Mutation Test
Imatinib mesylate (Gleevec)
c‐kit expression in gastrointestinal stromal tumors
DAKO C‐KIT PharmDx
KIT D816V Mutation Aggressive systemic mastocytosis
KIT D816V Mutation Detection by PCR
PDGFRB gene rearrangement myelodysplastic syndrome/ myeloproliferative disease
PDGFRB FISH
Deferasirox (Exjade)
Liver iron concentrations in non‐transfusion dependent thalassemia
Ferriscan
Venetoclax (Venclexta)
17p deletion in chronic lymphocytic leukemia
Vysis CLL FISH PROBE KIT
a
Includes only indications for which an FDA‐cleared or ‐approved companion diagnostic
is available.
b
Gastric cancer indication is for trastuzumab only.
Adapted from the FDA's List of Cleared or Approved Companion Diagnostic Devices (In
Vitro and Imaging Tools), http://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/InVitroDiagnostics/ucm301431.htm.
For example, with the marked clinical efficacy of crizotinib for non‐small cell lung
cancer (NSCLC), various second‐generation anaplastic lymphoma kinase (ALK) inhibitors
have been or are being developed, mostly for use in crizotinib‐resistant settings.
Central nervous system (CNS) antitumor activity is critical for specific ALK inhibitors
to be used for first‐line treatment to reduce or delay the rate of brain metastasis
in patients with ALK‐positive NSCLC.7 Currently, many bispecific antibodies are being
developed for cancer immunotherapy. Yuraszeck et al.8 described unique challenges
and experiences in the preclinical and the clinical development of blinatumomab, a
bispecific T‐cell engaging antibody, pointing out the critical need to optimize dose
and schedule of combination therapy and the potential utility of quantitative systems
pharmacology and other pharmacometric tools (e.g., physiologically based pharmacokinetic
modeling). Another area of active development is cancer prevention. Today, vaccination
is available to prevent some cancers, for example, human papillomavirus (HPV) vaccine
for the prevention of cervical, vulvar, vaginal, and anal cancers. The strong evidence
from the literature also shows that vaccination with hepatitis B vaccine can reduce
the incidence of hepatocellular carcinoma. However, development of agents to prevent
cancer whose causes are not associated with infection, although promising, is more
challenging and still at an early stage.9
The FDA has provided various regulatory pathways to expedite the development and approval
of drugs. For 2016, 73% of the approvals of novel drugs used one of the expedited
pathways, and of the six oncology drugs approved for therapeutic or diagnostic purposes
(atezolizumab, flucidovine‐18, gallium Ga 68 dotatate, olaratumab, rucaparib, and
venetoclax), all were designated Priority Review, four Breakthrough Therapy Designation,
four accelerated approval, and one Fast Track designation.10 As pointed out by Blumenthal
et al.,3 the FDA has approved several breakthrough‐designated drugs based on expansion
cohorts in phase I clinical trials. In addition to this novel “seamless drug development”
paradigm,11 the increasing use of master protocols that are genomically driven, including
basket trials (such as the NCI‐MATCH trial12) and umbrella trials (such as Lung‐Map13),
is promoting important collaborations among stakeholders for efficient development
of oncology drugs. While the traditional time‐to‐event endpoints (progression‐free
survival (PFS) and overall survival) are generally used for regular approval, objective
response rate (ORR) and duration of response (DoR) can often be used for accelerated
approval, especially in single‐arm trials.3 However, these latter data (ORR and DoR)
that may be used for drug approvals may not be suitable for health economic appraisal.14
In addition, the use of PFS as evaluated via RECIST (Response Evaluation Criteria
in Solid Tumors) may not be appropriate for locally administered oncolytic viral therapies.15
The use of model‐informed drug development (MIDD) strategies has increased in the
past few years. PDUFA VI (for fiscal years 2018–2022) included a commitment to “facilitate
the development and application of exposure‐based, biological, and statistical models
to derive from preclinical and clinical data sources.”16 To optimize individual dosing
regimens, it is critical to have appropriate clinical pharmacology studies, including
timely food effect evaluation,17 dose‐ranging trial designs, and best practices in
pharmacometric methodologies.18 Despite the increasing use of MIDD in drug development
and regulatory review, the use of models to inform dosing in specific subpatient groups
to improve treatment outcomes appears to be limited and requires wider interdisciplinary
collaborations.19
ACCELERATING THE PROGRESS AGAINST CANCER: NATIONAL INFRASTRUCTURE PILOTS AND PARTNERSHIPS
An average cancer patient may be seen by more than a dozen different providers during
his/her individual patient journey. The ability to aggregate a patient's data is currently
difficult, if not impossible. A major recommendation from policy and research experts
is to enable the creation of a learning healthcare system for cancer that will allow
us to glean knowledge and experience from every cancer patient.20, 21 Only then will
we be able to use data to enhance, improve, and inform the journey of every cancer
patient from the point of diagnosis through survivorship. This can be thought of analogously
to Waze, a community‐based traffic and navigation app in which millions of drivers
work together daily toward a common goal of finding the best route to their destinations.
Drivers that take local roads are able to share their experiences with similar drivers,
while at the same time providing useful information to high‐speed drivers that choose
to take highways. While both may arrive at the same destination, their shared individual
experiences will help inform the next driver who must determine the best path to take
on a similar journey. To achieve a “Waze for cancer,” we must go beyond the traditional
notion of simply aggregating data and move towards a structure that allows for reuse
of harmonized data, as demonstrated by the National Cancer Institute's (NCI's) Genomic
Data Commons and NCI Genomic Cloud Pilots.20 Orthogonal datasets from the same patient
that will allow machine learning algorithms to challenge existing dogmas will also
be needed. The partnership among the Department of Veterans Affairs, Department of
Defense, and NCI will challenge the status quo by examining a patient's genes (genomic
analysis), the expression of these genes in the form of proteins (proteomic analysis),
as well as medical images associated with the same patient to create the nation's
first system in which cancer patients are routinely screened for genomic abnormalities,
proteomic information, and imaging to match their tumor types to targeted therapies.
The Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network will
generate molecular datasets from thousands of patients, so that when clinical annotation
is layered on top, the network will help to predict which patients will respond to
which therapies.22 This analysis could either inform new combinations or use existing
novel therapies within the newly established NCI formulary23 to better understand
primary resistance and secondary resistance in patients. To provide temporal molecular
characterization of patients for machine‐learning purposes, subsets of data being
harmonized and generated by a public–private partnership, Blood Profiling Atlas in
Cancer (BloodPAC), could be used.24 BloodPAC brings together 25 state‐of‐the‐art biotech
companies, pharmaceutical partners, and academic labs focused on developing assays
to analyze blood. The collaboration has already shared raw data from over a dozen
studies and will work with the APOLLO network through the Department of Defense. Finally,
data elements describing immediate patient response from APOLLO and BloodPAC will
be developed and defined in a uniform manner with input from Centers for Medicare/Medicaid
(CMS) and FDA, enabling multidimensional analysis of these datasets by other payers
to assess whether similar approaches will improve health outcomes for their relevant
populations, as described broadly by the CMS Oncology Care Model.25 The examples given
above, and included in this issue, represent only a snapshot of infrastructures and
partnerships that will be needed. In 2017, continued implementation of these efforts
will lay the foundation critical to achieving the ambitious recommendations from the
NCI Blue Ribbon Panel with additional funding opportunities updated on a routine basis.26
CONCLUSION AND FUTURE DIRECTIONS
Also as part of the Cancer Moonshot program, on June 29, 2016, the FDA was instructed
to leverage the skills of regulatory scientists and reviewers across the various product
centers (drugs, biologics, and devices) to create the Oncology Center of Excellence
(OCE). The goal of the OCE is to further expedite the development of new combination
products and support an integrated approach to addressing cancer as a disease.27 On
January 19, 2017, the agency formally announced the establishment of the OCE and appointed
Dr. Richard Pazdur as OCE director.28
The OCE will seek to emulate both academic and cancer care centers, which are increasingly
organized in multidisciplinary models to enhance collaboration that is critical when
confronting a complex and rapidly evolving disease such as cancer.29 The OCE will
continue to incorporate the patient view into regulatory decision‐making and will
support innovation to better integrate the multiple disease and diagnostic options
to further patient care.29
DISCLAIMER
The views expressed in this article are those of the authors and do not necessarily
reflect the official views of the FDA or NCI.
CONFLICT OF INTEREST
The authors declare no conflicts of interest.