OCE Scientific Interest Areas

Collage image of clinical research images

Cell/gene and personalized neo-antigen-based therapies for cancer

Cell therapy is a promising new form of cancer treatment as demonstrated by recent CAR T-cell therapy approvals. New technologies are enabling rapid manufacturing of cells with tumor-killing capacity, necessitating more efficient clinical evaluation and innovative regulatory approaches.

The science of neo-antigen-based therapies for cancer is also developing rapidly, particularly since advances in genomics and proteomics allow identification of somatic mutations unique to individual cancers. Recent studies have demonstrated that high levels of somatic tumor mutations are correlated with response to immunotherapies such as checkpoint inhibitors, suggesting that individual tumor mutations (neoantigens) could be harnessed for immune targeting to develop personalized therapies such as cancer vaccines and cell therapies that target these neoantigens.

OCE is interested in supporting research related to clinical development, safety, manufacturing and quality control for cell therapy and neo-antigen-based therapies for cancer. Example OCE research interests in this scientific priority area include:

Create novel technologies and approaches to evaluate both efficacy and safety for neoantigen-based therapies that incorporate unique features of individual cancers, neoantigen and immune responses. Examples may include neoantigen-based vaccines redirecting the T-cell specificity by genetically modifying T cells with receptors specific against neoantigen-derived epitopes. (BAA Charge 1.B.)
Develop, optimize and standardize bioinformatic algorithms for neoantigen identification and development of personalized therapies. These are important to ensure the efficacy and safety of these products in the treatment of patients with cancer. (BAA Charge 1.C.)
Develop innovative trial designs (e.g., master protocols) for a group of cell or neoantigen-based therapies that were developed using a common platform (but target distinct antigens) to compare safety and clinical activity among products to identify the most promising candidates for further development. (BAA Charge 1.F.)
Develop innovative clinical trial designs to establish safety and efficacy in cell and gene therapies in randomized clinical studies where feasible. (BAA Charge 1.F.)

Health equity and special populations in oncology clinical trials

OCE is interested in understanding the factors that affect the safety and treatment response in demographic subgroups that have been historically underrepresented in oncology trials (e.g., racial/ethnic minorities, older adults, persons with disability, etc.). Risk factors, underlying differences in the disease biology, and access to healthcare may vary in these subgroups and impact outcomes in these subgroups. It is therefore critical to obtain information about these special populations to assess whether the evidence generated in clinical trials to support the safety and effectiveness of therapeutics is generalizable to the larger patient population.

Example OCE research interests in this scientific priority area include:

For more information, see The OCE Equity Program.

Immuno-oncology

Immune checkpoint inhibitors (ICI) have become the standard of care for multiple types of cancer and offer long-term disease control often with fewer (albeit unique) side effects compared to those encountered with chemotherapy. As the number of clinical trials evaluating ICIs either as single agents or in combination for the treatment of patients with cancer continues to increase, standardized approaches for predicting, identifying, and reporting side effects of ICIs becomes increasingly important.

Additionally, a large proportion of patients do not respond or become resistant to these treatments. There is a high unmet need to develop therapeutics for ICI-refractory or resistant patients, yet the field lacks a consistent definition of response for these drugs. Response is well defined for cytotoxic drugs and targeted therapies using images analyzed by response evaluation criteria in solid tumors (RECIST) criteria v 1.1; however, RECIST analyses reveal that a considerable proportion of patients treated with ICI demonstrate late response or may show initial tumor growth that can be followed by tumor shrinkage. These atypical response patterns complicate FDA’s ability to provide advice to sponsors about clinical trial design.

Example OCE research interests in this scientific priority area include:

Perform analyses of clinical data to develop a better understanding of the proportion of patients with atypical response and/or resistance and explore the development of predictive analytic approaches to identify patients who will eventually respond to ICI treatment from those who will not respond (BAA Charge 1.C.)
Develop biomarkers and/or pharmacodynamic endpoints to demonstrate the effect of ICI in cancer immunotherapies or as part of a combination regimen in treatment-naïve and immunotherapy resistant settings (BAA Charge 1.D.)
Develop technologies and approaches that better predict or characterize atypical response patterns to ICI such as radiomics, circulating tumor DNA, and/or novel approaches for immune cell profiling of the micro-environment (BAA Charge 1.D.)
Support clinical outcome assessment research to improve understanding of the side effects of ICIs (BAA Charge 1.E.)
Develop clinical trial endpoints that can help capture atypical response patterns to more fully characterize the clinical benefit of ICI and other cancer immunotherapies (BAA Charge 1.F.)
Develop clinical trial designs that can help capture atypical response to ICI and other cancer immunotherapies and can facilitate therapeutic development in immunotherapy resistant settings (BAA Charge 1.F.)
Research that can improve prospective planning of clinical trials and analysis in the presence of non-proportional hazards for time-to-event endpoints (BAA Charge 1.F.)
Analyze RWD to understand the utilization of complementary in vitro diagnostics and impact on utilization of cancer immunotherapy as a single agent or as part of a combination regimen (BAA Charge 1.J.)

For more information, see the Immuno-Oncology Program.

Oncology patient-focused drug development

Cancer patients experience disease symptoms and symptomatic treatment side effects that can impact their ability to function and other aspects of their health-related quality of life. OCE is interested in supporting research focused on developing approaches to assess the patient experience that will complement existing survival and tumor information.

Symptomatic adverse events and overall side effect impact are critically important to patients and improved analysis and visualization of symptomatic adverse events is a priority. In addition, the OCE is interested in exploring the utility of a single overall side effect global impact question that can be used to summarize overall side effect burden.

Physical function is another important patient-centered outcome that is a focus area of OCE research efforts. In particular, OCE is interested to learn more about the impact of different technologies, recall periods and different data collection platforms for gathering physical function data in oncology clinical trials.

FDA has identified the use of electronically captured patient-reported outcome (ePRO) physical function scales and wearable technologies as promising drug development tools to inform future development of oncology clinical trial endpoints. OCE is interested to understand the impact of using different measurement techniques on assessing physical function in a prospective natural history study of advanced cancer, particularly (1) wearable technologies (e.g., MIT E4 watch, actigraph accelerometer); (2) electronically captured patient-reported approaches (e.g., PROMIS ® physical function item bank) and (3) traditional clinician-based assessments (e.g., ECOG or Karnofsky performance status) and performance outcomes (e.g., 6-minute walk test or other PerfO). The research would analyze these data sources and their association with global anchor questions and other important clinical events such as hospitalizations, treatment changes, concomitant/supportive medication use and palliative procedures and survival.

Example OCE research interests in this scientific priority area include:

Investigate the sensitivity and measurement characteristics of existing patient-reported or digitally derived physical function measures in patients with rare and ultra-rare cancers (BAA Charge 1.E.)
Investigate open label bias: evaluate the impact of patient knowledge of their treatment on patient-reported outcomes in cancer clinical trials (BAA Charge 1.E.)
Evaluate differences in measurement characteristics in core patient-reported outcomes collected in US versus ex-US oncology patient populations or between various US demographic subgroups (BAA Charge 1.E.)
Study existing methods and develop novel methods to measure patient-reported symptomatic ocular toxicity in patients receiving anti-cancer therapy (BAA Charge 1.E.)

For more information, see the Patient-Focused Drug Development Program.

Oncology safety

Many advances have been made in the treatment of cancer with an increasing number of treatment options available to oncology patients. With the introduction of newer treatment approaches, little is known about the differential rate and severity of side effects and toxicities. Many cancer patients are living longer but at the same time they are experiencing an increase in symptom burden due to exposure to multiple lines of cancer therapy.

Some toxicities are acute while others become chronic. Often, the extent of the toxicity burden is unknown until the drug is administered to a large population of 'real-world' patients with comorbidities that were not included in a clinical trial, or until long-term follow-up uncovers late-onset toxicities. The natural trajectory, as well as the underlying mechanisms of many toxicities, is not well understood. There are no clear predictors of who may experience these symptoms and toxicities and why they vary in severity and duration from one individual to another.

For most of the toxicities caused by cancer treatment, no approved mitigating therapies or evidence-based management strategies are in place. There is a lack of mechanistic insight into these adverse events, difficulties in objectively measuring treatment-related toxic effects and insufficient studies validating pre-clinical biomarkers in the clinical setting.

Example OCE research interests in this scientific priority area include:

Develop improved and standardized approaches to collect and analyze cardiotoxicity data in the context of clinical trials to support new indications (BAA Charge 1.J.)
Develop improved and standardized approaches to collect serious toxicities such as cytokine release syndrome and neurotoxicity across a drug class, e.g., bispecific T cell engagers (BAA Charge 1.J.)
Develop approaches for collecting medical product safety data from RWD sources to expand understanding of the safety profile of approved oncology products in clinical practice (BAA Charge 2.A.)
Conduct analyses using RWD sources in cancer patients with a history of or active COVID-19 infection to evaluate increased severity of known drug adverse reactions or new toxicities, longitudinal sequelae, and residual toxicity (BAA Charge 2.A.)
Analyze RWD to help understand which patients are most likely to experience cardiotoxicity (or other types of severe toxicity) during cancer treatment (BAA Charge 2.A.)
Develop improved and standardized approaches to collect and analyze cardiotoxicity data in the context of post approval clinical trials and clinical practice (BAA Charge 2.C.)
Conduct basic, translational or clinical studies that investigate the underlying causes of cardiac toxicities associated with approved oncology agents (BAA Charge 2.C.)
Develop novel approaches to utilizing AI/ML to mine different data sources (e.g., EHRs, claims data, clinical trial data) for safety signal identification and/or characterization of oncology therapeutics (BAA Charge 2.C.)
Develop models and/or new translational study designs to better understand the mechanisms of toxicity underlying causes of recent safety alerts issued by FDA oncology (BAA Charge 2.C.)
Develop tools and/or algorithms to identify adverse reactions such as cytokine release syndrome, or other immune-related adverse events to eliminate the need for manual adjudication (BAA Charge 2.D.)

Oncology trial designs, endpoints and statistical methodologies

OCE provides detailed advice to sponsors about appropriate clinical trial designs, including statistical analysis methods. Rapid technological developments have increased sponsors’ interest in developing novel endpoints and interest in using data sources other than information collected during traditional clinical trials to support regulatory submissions.

OCE is also interested in research to define and validate novel clinical trial endpoints and how these endpoints perform relative to traditional endpoints used in clinical trials to support regulatory approval oncology products, such as Overall Response Rate, Progression-Free Survival, and Overall Survival. Collecting traditional oncology endpoints is labor-intensive and normally only performed in the context of a clinical trial, so it is unclear whether data collected during the course of clinical care will provide comparable information.

Example OCE research interests in this scientific priority area include:

Develop statistical methods to assess bias and misclassification when RWD is used in estimating treatment effect (BAA Charge 1.F.)
Multi-disciplinary research that includes expert clinical and statistical input addressing how external control data can be used as supportive data to isolate the treatment effect of experimental combination therapies (BAA Charge 1.F.)
Develop innovative clinical trial designs to find the optimal dose for oncology therapeutics (BAA Charge 1.F.)
Research relating to the design and analysis of pragmatic trials, for example using cluster randomization techniques (BAA Charge 1.F.)
Develop statistical methods for ruling out detrimental treatment effects on overall survival in clinical trials of indolent cancers (BAA Charge 1.F.)
Evaluate statistical methods for intercurrent events in oncology clinical trials, including but not limited to cross-over, treatment switch, treatment discontinuation, or other events that could induce informative censoring (BAA Charge 1.F.)

Pediatric oncology

The development of drugs for children and adolescents with cancer involves unique biological, clinical, societal and economic challenges. Pediatric drug development usually leverages efforts in adult drug discovery and development. Recent observations made possible through large scale pan-cancer genomic profiling across multiple pediatric cancers suggest that more than 50% of childhood cancers express druggable (approved, targeted drugs available) molecular aberrations. However, some targeted agents developed for adults are not effective in children. For example, immune checkpoint inhibitors have transformed treatment for several adult cancers but are less effective in most pediatric cancers because of diminished neoantigen expression due to low mutational burdens. Insufficient availability pre-clinical of appropriate preclinical models for pediatric cancers is also a major obstacle to advancing the field and is critical to identify promising molecular therapeutic products for pediatric cancers.

Examples of OCE research interests in this scientific priority area include:

For more information, see the Pediatric Oncology Program.

Precision oncology

Implementation of precision oncology has grown rapidly in recent years, with dozens of gene- and protein-based markers used to define enrollment criteria for oncology clinical trials and included in drug labels as companion or complementary diagnostics, pharmacogenomic or safety markers. There is a continued need to further understand the role of different biomarkers in oncology including identifying groups of patients who respond (or do not respond) to different treatments, better understanding disease progression and resistance mechanisms, and identifying high risk populations.

Several exciting technologies are advancing precision oncology, including measuring molecular changes in circulating tumor DNA isolated from plasma, and radiomics, an emerging science that uses algorithms to extract features from medical images that are invisible to the human eye. Combined with advanced machine learning algorithms, radiomics can improve disease detection, characterization, staging, as well as assessment and prediction of treatment response. A related field, radiogenomics, assesses the relationship between imaging features and gene expression. Work in this area is advancing rapidly since extensive imaging and genomic information are routinely collected in oncology clinical trials.

Example OCE research interests in this scientific priority area include:

Develop novel selection/response biomarkers using algorithms combining different types of medical images including radiology images (e.g., CT, PET) and/or histopathology images combined with novel analysis approaches such as radiomics and artificial intelligence/machine learning (BAA Charge 1.C.)
Identify and explore approaches to validate biomarkers (including liquid biopsy biomarkers) for escalation/de-escalation of treatments in the neoadjuvant, adjuvant and advanced disease settings (BAA Charge 1.D.)
Conduct studies to compare the analytical and clinical performance of local and centralized molecular tests used for patient enrollment on cancer clinical trials (BAA Charge 1.D.)
Conduct studies to understand why tumors located at different organ sites with molecular alterations in the same target respond differently to therapies to inform future potential tumor agnostic drug development (BAA Charge 1.D.)
Conduct retrospective or prospective studies/biomarker evaluations to understand if there are differences in response to targeted cancer treatment based on somatic vs. germline alterations of the target gene. A particular area of interest is to improve understanding of any differences in activity of PARP inhibitors in patients with BRCA mutations vs. other individual homologous recombination repair (HRR) mutations (BAA Charge 1.D.)
Develop methodologies to assess RWD as supportive evidence generation (clinical trial design; use of real world data for liquid biopsy diagnostics that are assessing multiple cancer types simultaneously for early detection indications (multicancer early detections; [MCED]) along with the data from prospective clinical studies that are needed as clinical validation for MCED assays (BAA Charge 1.J.)
Studies, including registries, to understand the epidemiology and rates of biomarker testing in patients with cancer, such as studying the prevalence of rare genomic subsets of clinical interest in patients with cancer (BAA Charge 1.J.)

For more information, see the Precision Oncology Program.

Rare cancers

Identifying candidate drugs and testing their effects in rare populations can be challenging and time consuming. Investigating approved drugs potentially offers a more efficient pathway for drug development for rare cancers. Use of decentralized elements in clinical trials including telemedicine and incorporation of other pragmatic features into clinical trials are also areas of interest for OCE but have not been widely implemented.

OCE is interested in supporting research to assist drug development for rare cancers, including molecularly-defined subsets (e.g., RET-positive lung cancers) of more common tumors, and all pediatric cancers such as:

Investigations using text mining and/or artificial intelligence to analyze, assess, and interpret the scientific literature and other public databases of genomic and transcriptomic analyses in rare cancers to identify drugs that have been used against molecular targets relevant in rare cancers (BAA Charge 1.C.)
Investigations to characterize the plasma membrane surfaceome of healthy cells/tissues and ultra-rare tumors such that logic gated CAR-T cell therapeutic approaches can be encouraged, and potential on-target, off-tumor safety issues can be identified (BAA Charge 1.C.)
Innovative approaches to identify new biologically-driven opportunities for clinical development of previously approved drugs (or drugs for which development has been discontinued) in rare cancers (BAA Charge 1.D.)
Development of methods to incorporate use of telemedicine and/or decentralized approaches (e.g., collecting laboratory and/or imaging data from local facilities) for patient assessments to facilitate enrollment of patients with rare cancers (BAA Charge 1.F.)
Development of the infrastructure for a coordination network and data repository for patient-level data across institutions and internationally to support drug development and regulatory decision-making for ultra-rare tumors (BAA Charge 1.F.)
Studies, including registries, to investigate the natural history of rare cancers to provide clinical and scientific context to inform the design and interpretation of clinical trials. This work could involve analyses of registries and/or other RWD (BAA Charge 1.J.)
Investigations to explore opportunities to develop appropriate external control arms using real world evidence or clinical trial data to support the clinical development of new drugs for rare cancers (BAA Charge 1.J.)

For more information, see the Rare Cancers Program.

Oncology Real-World Data and Real-World Evidence

Developing approaches to evaluate, integrate, and facilitate the use of oncology real-world data (RWD) (e.g., electronic health records, administrative health claims, drug or disease registries, patient reported or generated health data) to generate high-quality real-world evidence (RWE) is an active area of regulatory science as noted in the 21st Century Cures Act.

Methodologically rigorous research which expands upon the need to evaluate innovative study approaches such as clinical trials including pragmatic elements, or other prospective designs including development of RWD resources through high quality registry studies to accelerate clinical development of new drugs in oncology are encouraged. Specific examples of interest are included in the immuno-oncology, health equity and special populations in oncology drug development, oncology trial designs, endpoints and statistical methodologies, pediatric oncology, oncology safety, and rare cancers sections.

Evaluation of innovative applications of RWD to clinical drug development, including epidemiologic and statistical approaches, specifically scientific methods research to enhance evaluation and assessment of RWD through evaluation of bias, confounding, or other potential threats to study validity. Examples include investigations to explore appropriate uses of externally controlled designs in clinical drug development (BAA Charge 1.J.)
Explore and define RWD quality through a research study or framework development to consider factors including data reliability and relevance including (but not limited to) factors such as collection missingness, specificity, sensitivity, data validation, data harmonization, data provenance, interoperability, data linkage, and the potential capability to make accurate inferences from the available data or improve standardization efforts in the source data towards learning healthcare systems (BAA Charge 1.D.)
Methods-focused research using artificial intelligence or machine learning approaches
- to analyze, assess and interpret the scientific literature or currently available evidence in a novel way (BAA Charge 1.J.)
- to apply to RWD to enhance knowledge of novel study methods and understanding potential uses in regulatory science including evaluation of data quality, e.g., developing AI/ML approaches to process unstructured data (or in combination with structured data) or approaches to data transparency (BAA Charge 1.J.)
- to understand approaches to improve introduction of pragmatic elements into clinical trials such as understanding clinical site selection or enhancement of representation to advance health equity (BAA Charge 1.J.)
Develop, define and test real world endpoints from oncology RWD that could be used to generate real world evidence (RWE) to complement traditional clinical trial data submitted to FDA, particularly the development of measures of real-world response (BAA Charge 1.D.)

U.S. Food and Drug Administration

OCE Scientific Interest Areas

Cell/gene and personalized neo-antigen-based therapies for cancer

Health equity and special populations in oncology clinical trials

Immuno-oncology

Oncology patient-focused drug development

Oncology safety

Oncology trial designs, endpoints and statistical methodologies

Pediatric oncology

Precision oncology

Rare cancers

Oncology Real-World Data and Real-World Evidence

Further Information