Accelerating the development of genetically engineered cellular therapies: a framework for extrapolating data across related products.

BACKGROUND: Significant advancements have been made in the field of cellular therapy as anti-cancer treatments, with the approval of chimeric antigen receptor (CAR)-T cell therapies and the development of other genetically engineered cellular therapies. CAR-T cell therapies have demonstrated remarkable clinical outcomes in various hematological malignancies, establishing their potential to change the current cancer treatment paradigm. Due to the increasing importance of genetically engineered cellular therapies in the oncology treatment landscape, implementing strategies to expedite development and evidence generation for the next generation of cellular therapy products can have a positive impact on patients. METHODS: We outline a risk-based methodology and assessment aid for the data extrapolation approach across related genetically engineered cellular therapy products. This systematic data extrapolation approach has applicability beyond CAR-T cells and can influence clinical development strategies for a variety of immune therapies such as T cell receptor (TCR) or genetically engineered and other cell-based therapies (e.g., tumor infiltrating lymphocytes, natural killer cells and macrophages). RESULTS: By analyzing commonalities in manufacturing processes, clinical trial designs, and regulatory considerations, key learnings were identified. These insights support optimization of the development and regulatory approval of novel cellular therapies. CONCLUSIONS: The field of cellular therapy holds immense promise in safely and effectively treating cancer. The ability to extrapolate data across related products presents opportunities to streamline the development process and accelerate the delivery of novel therapies to patients.

An Analysis of Dosing-Related Postmarketing Requirements for Novel Oncology Drugs Approved by the U.S. Food and Drug Administration, 2012-2022.

The FDA's Oncology Center of Excellence's (OCE) launch of Project Optimus signals increased focus on dose optimization approaches in oncology drug development, particularly toward optimization in the premarket setting. Although sponsors continue to adapt premarket study designs and approaches to align with FDA's expectations for dose optimization, including consideration of the optimal dosage(s), there are still instances where questions remain at the time of approval about whether the approved doses or schedules are optimal. In these cases, FDA can exercise regulatory flexibility by issuing postmarketing requirements (PMR) and avoid delaying patient access to promising therapies. This landscape analysis demonstrates that over the past decade (2012-2022), FDA frequently used PMRs to answer additional questions about dosing for novel oncology approvals. We found more than half of drugs (78/132, 59.1%) had a dosing PMR and observed a recent increase in PMRs intended to evaluate whether a lower dose could be more optimal. These results suggest there are opportunities to adapt premarket dose optimization strategies and leverage innovative development tools to ensure timely identification of the optimal dose.

An Evaluation of Novel Oncology Approvals with a PMR/C for Assessing Data in Racial and Ethnic Populations Underrepresented in Premarket Clinical Trials.

Clinical trials supporting oncology drug approvals frequently underrepresent diverse racial and ethnic populations. Recent policies have focused on ensuring premarket clinical trials are more inclusive and representative of racial and ethnic diversity in the general U.S. population or intended patient population; however, recent U.S. Food and Drug Administration (FDA) guidance on postmarketing approaches to collecting data in underrepresented populations demonstrates that, in certain circumstances, postmarketing requirements and/or commitments (PMR/Cs) may be issued to conduct more representative studies if there are remaining questions about safety or efficacy. This analysis demonstrates that prior to 2020, no drugs had PMR/Cs to further characterize use in a more representative population, and in the last 3 years, more than half of novel oncology approvals have had such a PMR/C (21/40, 53%). In addition, this analysis helps to identify characteristics, such as single-arm pivotal trial design, U.S. enrollment, and results of safety subgroup analyses based on race and ethnicity, that may contribute to decisions to issue a PMR/C to conduct a study that is more representative of the racial and ethnic diversity of the U.S. or intended patient population. These results can inform efforts to improve premarket clinical trials to ensure they are representative and able to characterize use in any patient who may need the drug.

Advancing Evidence Generation for Circulating Tumor DNA: Lessons Learned from A Multi-Assay Study of Baseline Circulating Tumor DNA Levels across Cancer Types and Stages.

Circulating tumor DNA (ctDNA) holds promise as a biomarker for predicting clinical responses to therapy in solid tumors, and multiple ctDNA assays are in development. However, the heterogeneity in ctDNA levels prior to treatment (baseline) across different cancer types and stages and across ctDNA assays has not been widely studied. Friends of Cancer Research formed a collaboration across multiple commercial ctDNA assay developers to assess baseline ctDNA levels across five cancer types in early- and late-stage disease. This retrospective study included eight commercial ctDNA assay developers providing summary-level de-identified data for patients with non-small cell lung cancer (NSCLC), bladder, breast, prostate, and head and neck squamous cell carcinoma following a common analysis protocol. Baseline ctDNA levels across late-stage cancer types were similarly detected, highlighting the potential use of ctDNA as a biomarker in these cancer types. Variability was observed in ctDNA levels across assays in early-stage NSCLC, indicative of the contribution of assay analytical performance and methodology on variability. We identified key data elements, including assay characteristics and clinicopathological metadata, that need to be standardized for future meta-analyses across multiple assays. This work facilitates evidence generation opportunities to support the use of ctDNA as a biomarker for clinical response.

Evaluation of Real-World Tumor Response Derived From Electronic Health Record Data Sources: A Feasibility Analysis in Patients With Metastatic Non-Small Cell Lung Cancer Treated With Chemotherapy.

PURPOSE: Real-world data (RWD) holds promise for ascribing a real-world (rw) outcome to a drug intervention; however, ascertaining rw-response to treatment from RWD can be challenging. Friends of Cancer Research formed a collaboration to assess available data attributes related to rw-response across RWD sources to inform methods for capturing, defining, and evaluating rw-response. MATERIALS AND METHODS: This retrospective noninterventional (observational) study included seven electronic health record data companies (data providers) providing summary-level deidentified data from 200 patients diagnosed with metastatic non-small cell lung cancer (mNSCLC) and treated with first-line platinum doublet chemotherapy following a common protocol. Data providers reviewed the availability and frequency of data components to assess rw-response (ie, images, radiology imaging reports, and clinician response assessments). A common protocol was used to assess and report rw-response end points, including rw-response rate (rwRR), rw-duration of response (rwDOR), and the association of rw-response with rw-overall survival (rwOS), rw-time to treatment discontinuation (rwTTD), and rw-time to next treatment (rwTTNT). RESULTS: The availability and timing of clinician assessments was relatively consistent across data sets in contrast to images and image reports. Real-world response was analyzed using clinician response assessments (median proportion of patients evaluable, 77.5%), which had the highest consistency in the timing of assessments. Relative consistency was observed across data sets for rwRR (median 46.5%), as well as the median and directionality of rwOS, rwTTD, and rwTTNT. There was variability in rwDOR across data sets. CONCLUSION: This collaborative effort demonstrated the feasibility of aligning disparate data sources to evaluate rw-response end points using clinician-documented responses in patients with mNSCLC. Heterogeneity exists in the availability of data components to assess response and related rw-end points, and further work is needed to inform drug effectiveness evaluation within RWD sources.