The Oncology Center of Excellence (OCE) Scientific Collaborative supports FDA oncology staff who participate in regulatory science research, including internal research projects and collaborations with external experts. OCE research focuses on applied (rather than basic) research questions to address specific challenges encountered during the IND and NDA/BLA review process. The OCE has identified nine scientific interest areas and one cross cutting area for its applied research efforts described below.

OCE engages with external scientists using several approaches including informal collaborations, research collaboration agreements, memoranda of understanding, and sometimes provides research funding. The FDA Broad Agency Announcement (BAA) is one such research funding method. FDA funded several projects (including oncology-related projects) using the BAA in fiscal 2021.

For more information about submitting an oncology-related application to the FDA BAA, please review the OCE BAA Frequently Asked Questions.

For any questions regarding the OCE Scientific Collaborative, contact [email protected]

Scientific Interest Areas:

I. 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 to support 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:

1. Facilitate regulatory review of neoantigen-based cancer therapies by supporting research to:

• Develop, optimize and standardize algorithms for neoantigen identification. These are important to ensure the efficacy and safety of these products in the treatment of patients with cancer.
• 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.

2. Implement innovative clinical trial designs 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.

II. 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, sexual and gender minorities, older adults). 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:

3. Conduct qualitative research to perform root cause analysis to understand barriers to including underrepresented subgroups in oncology clinical trials (e.g., access to clinical trial sites, patient and/or physician preference, and/or other structural, operational or trial-specific barriers).

4. Identify best practices for enrolling underrepresented subgroups in oncology clinical trials, including patient-, physician-, and community-focused approaches. Evaluate the effectiveness of interventions designed to enroll diverse populations in oncology clinical trials such as digital technologies, decentralized clinical trials, patient/community/language navigators.

5. Characterize the prevalence of currently druggable biomarkers in racial/ethnic minorities and assess implications for enrollment in clinical trials.

6. Understand the impact of remote assessments and decentralized procedures used more frequently during the COVID-19 pandemic (e.g., e-consent, telemedicine, collecting laboratory and/or imaging data from local facilities) on underrepresented subgroups participating in oncology clinical trials.

7. Study FDA approved drugs using real world data (RWD) (e.g., electronic health records, administrative health claims, drug or disease registries, patient reported or generated health data) to improve understanding of safety and efficacy, for example through analyses of low grade toxicities or symptom function measures in underrepresented subgroups.

8. Analyze RWD to understand the impact of treating racial/ethnic minorities and older patients with approved drugs who may not have been eligible for clinical trials (e.g., because of organ dysfunction or co-morbidities).

9. Study RWD to understand patterns of care and clinical outcomes in sexual and gender minorities with cancer.

10. Develop framework for assessing clinical site readiness to achieve adequate enrollment of participants from historically under-represented racial/ethnic subgroups in therapeutic oncology clinical trials.

III. 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-- potential accelerated--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:

11. Perform analyses of clinical data to develop a better understanding of the proportion of patients with atypical response and explore the development of predictive analytic approaches to identify patients who will eventually respond to ICI treatment from those who will not respond. OCE is also interested in understanding how to distinguish among patients who have become resistant to ICI on an ongoing basis from those who may respond again upon re-challenge.

12. Develop technologies and approaches that better predict or characterize atypical response patterns to immune checkpoint inhibitors. Promising technologies for consideration include:

• Radiomic analysis of tumor images. This approach can capture features of the tumor that are not addressed by RECIST measurements and may incorporate information about changes in the tumor microenvironment in addition to information about tumor size.
• Circulating tumor DNA to monitor response to treatment by measuring cancer- associated somatic mutations at multiple time points during a patient's treatment.
• Novel approaches for immune cell profiling of the tumor microenvironment

13. Develop clinical trial endpoints that account for atypical response patterns and more fully characterize the clinical benefit of immune checkpoint inhibitors and other cancer immunotherapies.

14. Develop clinical trial designs that can help capture atypical response to ICI and other cancer immunotherapies.

15. Develop pharmacodynamic endpoints that can be used to isolate the contribution of individual components to the effect of cancer immunotherapy combination regimens.

16. Develop biomarkers to identify patients who will be responsive to particular cancer immunotherapeutics or immunotherapeutic combination regimens.

17. 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.

18. Support research in two areas to improve understanding of the side effects of ICIs:(1) develop technologies that better identify patients at risk for development of serious adverse reactions with ICIs; (2) develop standardized approaches for identifying and reporting side effects in clinical trials evaluating ICIs.

IV. 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:

19. Investigate measurement characteristics for new and existing patient-reported global items quantifying overall side effect impact such as the FACIT GP5 item for patients undergoing anti-cancer therapy.

20. Evaluate differences in clinical outcome measures of physical function in an advanced cancer patient cohort undergoing treatment by prospectively capturing data from: (a) electronic PRO; (b) wearable technologies; (c) performance outcomes; and (d) clinician assessment (e.g. ECOG/Karnofsky).

21. Conduct a prospective study to compare the sensitivity and measurement characteristics of patient-reported physical function items using a 7-day recall period versus no recall period using a well-defined PRO physical function scale such as the PROMIS physical function bank.

22. Implement PRO symptom and functional measures using ePRO in advanced cancer patients using the FDA MyStudies application to test feasibility, accuracy and ease of use.

23. Investigate the sensitivity and measurement characteristics of existing patient-reported physical function measures in patients with rare and ultra-rare cancers.

24. Develop longitudinal analysis and visualization methods to communicate physical function trajectory over time in patients with advanced/metastatic malignancies.

25. Investigate individual-level change (i.e., responder definition) and meaningful change thresholds for PRO symptom measures using qualitative research methods to inform future quantitative studies in advanced cancer patients.

26. Investigate open label bias: evaluate the impact of patients knowledge of their treatment on patient-reported outcomes in cancer clinical trials.

VI. 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:

27. 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.

28. Develop approaches using RWD sources to evaluate the toxicity profile of approved products in cancer patients with a history of or active COVID-19 infection including any increase in known drug adverse reactions or new toxicities, longitudinal sequelae, and outcomes.

29. Develop improved and standardized approaches to collect and analyze cardiotoxicity data in the context of clinical trials and clinical practice to better understand the cardiotoxicity profile of both investigational and approved drugs.

30. Analyze clinical data collected in real world settings to help understand which patients are most likely to experience cardiotoxicity (or other types of severe toxicity) during cancer treatment.

31. Conduct basic, translational or clinical studies that investigate the underlying causes of cardiac toxicities associated with approved oncology agents.

32. Conduct translational studies that investigate underlying causes of recent safety alerts issued by FDA oncology. Examples in oncology include safety alerts indicating that the use of atezolizumab and paclitaxel in patients with previously untreatable inoperable locally advanced or metastatic triple negative breast cancer does not work to treat the disease, multiple myeloma clinical trials that showed an increased risk of death in patients receiving venetoclax in combination with bortezomib and dexamethasone, and the use of immune checkpoint inhibitors and immunomodulatory agents as compared to control groups.

VI. 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 in electronic capture of medical record and claims data has increased sponsors’ 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 real world endpoints that can be collected from Electronic Health Records (EHR) and how real world 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:

33. Develop novel statistical approaches for using external controls in oncology trials, which could supplement concurrent control arm data. External controls have the potential to reduce patient enrollment and clinical trial costs, but new methods are needed to mitigate challenges including (1) population differences such as mismatched eligibility criteria between external control and clinical trial patients; (2) differences in exposure (e.g., use of prior therapies) and outcomes (e.g., endpoint assessments such as rules for censoring observations in time to event endpoints, differences in criteria of assessments, etc.) between external control and clinical trial patients; and (3) different sources of bias (i.e., measurement, selection and confounding). Use of external data is further complicated by rapidly evolving standards of care and the approval of new drugs and biologics.

34. OCE is particularly interested in supporting multi-disciplinary research, that includes expert clinical and statistical input, addressing how external control data can be used to isolate the treatment effect of experimental combination therapies. In this situation, external data for each component of the combination may be used to estimate the efficacy of a monotherapy or supplement existing control data collected in a clinical trial. High priority research areas relating to external controls include exploration of design (e.g., sample size calculations, borrowing from external data if applicable, operational characteristics) and methodology considerations (balancing arms, endpoints and analysis).

35. Develop, define and test real world oncology endpoints from 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. OCE would like to understand the sensitivity of endpoints of interest in various real-world scenarios that may induce potential biases (e.g. immortal time bias), as well as methods to mitigate the concerns of confounding or bias in the analyses of these endpoints. OCE is particularly interested in research in this area that focuses on demonstrating consistent and robust effect estimation from RWD or methods to advance bias quantification.

36. Explore and define RWD quality. RWD sources are generally collected for purposes other than clinical or regulatory research and analyses. For this reason, determining data quality requires consideration of various factors, including the reasons for collecting specific variables (or not collecting variables), missingness or completeness of key variables, specificity, sensitivity,data validation, harmonization, data provenance, data linkage, and the potential capability to make accurate inferences from the available data.

37. An area that is of particular interest for the application of oncology RWD is exploring patient populations that are not represented or under-represented in clinical trials (e.g., racial minorities, older adults, adolescents, children, rare cancers etc.). Specifically, how can RWD effectively supplement clinical trial data in these patient populations to enhance current evidence? What types of statistical methods can be used to incorporate external or historical data in the estimation of treatment effect in under-represented groups?

VII. Pediatric oncology

The development of drugs for children 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; however, these drugs are less effective in pediatric cancers because of diminished neoantigen expression due to low mutational burdens. The lack of pre-clinical testing in pediatric tumors is also a major obstacle to advancing the field and is critical to identify promising molecular targets for pediatric cancers.

Example OCE research interests in this scientific priority area include:

38. Development of preclinical models (e.g., patient-derived xenograft models, orthotopic mouse models, organoids) of pediatric tumors, most of which are embryonal in origin to facilitate decision-making regarding the evaluation of emerging novel agents potentially applicable to tumors which predominantly occur in the pediatric population.

39. Investigations to elucidate the relevance of specific molecular targets to the growth and/or progression of pediatric tumors to understand and assess target actionability using text mining and artificial intelligence to analyze, assess and interpret the scientific literature and other public databases of genomic and transcriptomic analyses of pediatric cancers.

40. Translational research to design and develop rational combination regimens for pediatric patients that may include ICIs and other treatments (e.g., chemotherapy, vaccines, radiation) based on a strong scientific rationale that addresses the current data suggesting lack of activity of single agent ICIs in pediatric tumors.

41. Investigations to explore opportunities to develop acceptable external control arms from RWD to aid in accelerating new drug approvals for childhood cancer.

42. Development of immune based therapies (engineered immune effector cells or bifunctional activators) that recognize tumor specific altered glycan epitopes (glycolipids or glycoproteins) that NK and T-cells do not generally recognize.

43. Investigations to solicit children’s self-report of treatment related adverse events to accommodate the child’s voice in assessing patient tolerability of new drugs.

44. In collaboration with statistical experts, evaluate novel study designs for small populations including Bayesian approaches to borrowing from adult data and relaxed type 1 error considerations to facilitate randomized trials whenever possible.

VIII. 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:

45. Develop algorithms that predict an individual patient’s genotype and/or response (in terms of efficacy and/or safety) to cancer therapy using different types of medical images including radiology images (e.g., CT, PET) and/or histopathology images combined with novel analysis approaches such as high-throughput quantitative image feature extraction (i.e., radiomics) and machine learning. Explore conducting these analyses in combination with other types of data (for example, demographics, genetics, and laboratory test results) to advance precision medicine.

46. Identify biomarkers (including liquid biopsy biomarkers) to gain information related to oncology diagnosis, monitoring, response, or resistance.

47. Conduct studies to compare the performance of local and centralized molecular tests used for patient enrollment on cancer clinical trials. Investigate approaches that can improve the performance of local tests. Research that includes comparisons of tests commonly used in the US and/or comparisons of tests used in the US with those performed at international sites is particularly encouraged.

48. Conduct studies to understand why tumors located at different organ sites with molecular alterations in the same target respond differently to therapies directed at that target (e.g., the development of tumor-specific resistance mechanisms, differences in pathway activation) to inform future potential tumor agnostic drug development.

49. Develop methodologies to inform 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).

50. 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.

IX. 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. Telemedicine is also an area of interest for OCE, as it has been a successful tool for clinical trials and patient care in other disease areas (e.g., stroke, Parkinson’s disease), but has not been widely implemented in oncology.

OCE is interested in supporting research to assist drug development for rare cancers, defined by the Orphan Drug Act as a disease or condition that affects fewer than 200,000 people in the U.S. and includes several molecularly-defined subsets (e.g., RET-positive lung cancers) and all pediatric cancers such as:

51. Studies 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.

52. Studies to develop and characterize symptom function measures for rare cancers to complement information obtained from traditional clinical trial endpoints used in regulatory submissions. OCE is particularly interested in studies that focus on establishing clinical benefit and potential practical use in clinical trial settings.

53. 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. Consider whether new or additional tumor assessment techniques may provide a more informative assessment of a drug’s effect on a tumor compared with traditional RECIST criteria.

54. Studies in rare cancers to implement a clinical trial protocol incorporating use of telemedicine and/or decentralized approaches (e.g., collecting laboratory and/or imaging data from local facilities) for patient assessments. OCE is particularly interested in studies that focus on evaluating feasibility and implementation, including an analysis of the risks and benefits of different technologies, impact on clinical trial participation and the quality of data collected.

Cross Cutting Area:

Oncology Real World Data Utilization

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 studies which expand upon the need to evaluate innovative study designs (e.g. pragmatic, hybrid), RWD quality, statistical approaches, and real world endpoints specifically through scientific research studies, metric or framework development, or standardized definitions, are encouraged.

Specific topics of interest for use of Oncology RWD and RWE can be found in sections: 7, 8, 9, 11, 17, 27, 28, 29, 30, 33, 34, 35, 36, 37, 41, 49, 51