FDA approval summary: fam-trastuzumab deruxtecan-nxki for unresectable or metastatic non-small cell lung cancer with activating HER2 mutations.

On August 11, 2022, FDA granted accelerated approval to fam-trastuzumab deruxtecan-nxki (DS-8201a, T-DXd, ENHERTU, Daiichi Sankyo) for adult patients with unresectable or metastatic non-small cell lung cancer (NSCLC) whose tumors have activating human epidermal growth factor receptor 2 (HER2) mutations, as detected by an FDA-approved test, and who have received a prior systemic therapy. The approval was based on a prespecified interim analysis of DESTINY-Lung02 (Study U206), a multi-center, randomized, dose-optimization trial in patients with NSCLC harboring activating HER2-mutations. At the approved dose of 5.4 mg/kg given intravenously every 3 weeks, the overall response rate (ORR) was 58% (95% confidence interval [CI]: 43, 71). The median duration of response was 8.7 months (95% CI: 7.1, not estimable). These results were consistent with response rates observed at the 6.4 mg/kg dose level. The most common (≥ 20%) adverse reactions were nausea, constipation, decreased appetite, vomiting, fatigue, and alopecia. The rate of interstitial lung disease (ILD) or pneumonitis was 6% at the 5.4 mg/kg dose level and 14% at the 6.4 mg/kg dose level. In the setting of similar efficacy and reduced toxicity, approval was granted for the 5.4 mg/kg dose level. The applicant conducted a randomized, dose-optimization study with guidance from the FDA Oncology Center of Excellence's Project Optimus. This is the first approval of a targeted therapy for HER2-mutated NSCLC.

Survival outcomes in older men with non-metastatic castration-resistant prostate cancer treated with androgen receptor inhibitors: a US Food and Drug Administration pooled analysis of patient-level data from three randomised trials.

BACKGROUND: Little is known about the benefit-risk profile of second-generation androgen receptor inhibitors in older men with non-metastatic castration-resistant prostate cancer. We aimed to examine the efficacy and safety of second-generation androgen receptor inhibitors in men aged 80 years or older with non-metastatic castration-resistant prostate cancer. METHODS: We searched for all randomised controlled clinical trials evaluating second-generation androgen receptor inhibitors in patients with non-metastatic castration-resistant prostate cancer submitted to the US Food and Drug Administration before Aug 15, 2020, and pooled data from three trials that met the selection criteria. All three trials enrolled patients who were aged 18 years or older with an Eastern Cooperative Oncology Group performance status of 0-1, castration-resistant prostate cancer, prostate-specific antigen (PSA) 2·0 µg/L or greater, PSA doubling time of 10 months or less, and no evidence of distant metastatic disease on conventional imaging per the investigator's assessment at the time of screening. All patients had histologically or cytologically confirmed adenocarcinoma of the prostate without neuroendocrine differentiation or small-cell features. All patients who were randomly assigned to androgen receptor inhibitor or placebo groups in these trials were considered assessable and were included in this pooled analysis. We evaluated the effect of age on metastasis-free survival and overall survival across age groups (<80 years vs ≥80 years) in the intention-to-treat population. Safety analyses were done in patients who received at least one dose of study treatment. FINDINGS: Between Oct 14, 2013, and March 9, 2018, 4117 patients were assigned to androgen receptor inhibitor (apalutamide, enzalutamide, or daralutamide; n=2694) or placebo (n=1423) across three randomised trials. The median follow-up duration for metastasis-free survival was 18 months (IQR 11-26) and for overall survival was 44 months (32-55). In patients aged 80 years or older (n=1023), the estimated median metastasis-free survival was 40 months (95% CI 36-41) in the androgen receptor inhibitor groups and 22 months (18-29) in the placebo groups (adjusted hazard ratio [HR] 0·37 [95% CI 0·28-0·47]), and the median overall survival was 54 months (50-61) versus 49 months (43-58), respectively (adjusted HR 0·79 [0·64-0·98]). In patients younger than 80 years of age (n=3094), the estimated median metastasis-free survival was 41 months (95% CI 36-not estimable [NE]) in the androgen receptor inhibitor groups and 16 months (15-18) in the placebo groups (adjusted HR 0·31 [95% CI 0·27-0·35]), and the median overall survival was 74 months (74-NE) versus 61 months (56-NE), respectively (adjusted HR 0·69 [0·60-0·80]). In patients aged 80 years or older, grade 3 or worse adverse events were reported in 371 (55%) of 672 patients in the androgen receptor inhibitor groups and 140 (41%) of 344 patients in the placebo groups, compared with 878 (44%) of 2015 patients in the androgen receptor inhibitor groups and 321 (30%) of 1073 patients in the placebo groups among patients younger than 80 years. The most common grade 3-4 adverse events were hypertension (168 [8%] of 2015 patients aged <80 years and 51 [8%] of 672 patients aged ≥80 years in the androgen receptor inhibitor groups vs 53 [5%] of 1073 patients aged <80 years and 22 [6%] of 344 patients aged ≥80 years in the placebo groups) and fracture (61 [3%] and 36 [5%] in the androgen receptor inhibitor groups vs 15 [1%] and 11 [3%] in the placebo groups). INTERPRETATION: The findings of this pooled analysis support the use of androgen receptor inhibitors in older men with non-metastatic castration-resistant prostate cancer. Incorporating geriatric assessment tools in the care of older adults with non-metastatic castration-resistant prostate cancer might help clinicians to offer individualised treatment to each patient. FUNDING: None.

Why nurses stay: Analysis of the registered nurse workforce and the relationship to work environments.

AIM: To examine how factors such as a sense of belonging to a nursing work group, work environmental characteristics, and workplace violence effects the duration of employment in professional settings in a southwest region of the United States. DESIGN: The descriptive correlational survey study conducted in 2014. METHODS: A random sample of 700 licensed registered nurses (RN) from a Board of Nursing's list of currently licensed RNs' (approximate n = 2300). Participants completed and returned four survey tools to the principal investigator. The return rate was 36.8% (258/700). RESULTS/FINDINGS: Analysis indicated that a sense of belonging, as well as supportive workplace characteristics, played a role in why nurses stay. The three survey tools provided strong correlations in the survey data and further authenticated the tools' reliability. A healthy work environment supports nurse retention. CONCLUSION: The three survey tools used in this study showed substantial and significant correlations. Although not all sub-scales correlated, those that did had strong Cronbach alpha scores. The weakest correlations were with the belongingness scale. Rapid turnover rates of nursing staff continue to plague healthcare organizations. A variety of reasons including difficult practice settings and stressful work environments contribute to the outflow of nurses. IMPACT: Health care administration and management leaders can improve retention via their efforts to continue to create and sustain healthy work environments that address affiliation, belongingness, and the characteristics that attract and retain nurses.

Sample size determination for multilevel hierarchical designs using generalized linear mixed models.

A unified statistical methodology of sample size determination is developed for hierarchical designs that are frequently used in many areas, particularly in medical and health research studies. The solid foundation of the proposed methodology opens a new horizon for power analysis in presence of various conditions. Important features such as joint significance testing, unequal allocations of clusters across intervention groups, and differential attrition rates over follow up time points are integrated to address some useful questions that investigators often encounter while conducting such studies. Proposed methodology is shown to perform well in terms of maintaining type I error rates and achieving the target power under various conditions. Proposed method is also shown to be robust with respect to violation of distributional assumptions of random-effects.

Efferent-induced alterations in distortion and reflection otoacoustic emissions in children.

The medial olivocochlear efferent fibers control outer hair cell responses and inhibit the cochlear-amplifier gain. Measuring efferent function is both theoretically and clinically relevant. In humans, medial efferent inhibition can be assayed via otoacoustic emissions (OAEs). OAEs arise by two fundamentally different mechanisms-nonlinear distortion and coherent reflection. Distortion and reflection emissions are typically applied in isolation for studying the efferent inhibition. Such an approach inadvertently assumes that efferent-induced shifts in distortion and reflection emissions provide redundant information. In this study, efferent-induced shifts in distortion and reflection emissions (click-evoked and stimulus frequency OAEs) were measured in the same subjects-5- to 10-yr-old children. Consistent with the OAE generation theory, efferent-induced shifts in distortion and reflection emissions did not correlate, whereas the two reflection emission shifts correlated. This suggests that using either OAE types provides fragmented information on efferent inhibition and highlights the need to use both distortion and reflection emissions for describing efferent effects.

Assessing treatment efficacy in the presence of diagnostic errors.

This paper investigates estimating and testing treatment effects in randomized control trials where imperfect diagnostic device is used to assign subjects to treatment and control group(s). The paper focuses on pre-post design and proposes two new methods for estimating and testing treatment effects. Furthermore, methods for computing sample sizes for such design accounting for misclassification of the subjects are devised. The methods are compared with each other and with a traditional method that ignores the imperfection of the diagnostic device. In particular, the likelihood-based approach shows a significant advantage in terms of power, coverage probability and, consequently, in reduction of the required sample size. The application of the results are illustrated with data from an aging trial for dementia and data from electroencephalogram (EEG) recordings of alcoholic and non-alcoholic subjects. Copyright © 2016 John Wiley & Sons, Ltd.

Concurrent generation of multivariate mixed data with variables of dissimilar types.

Data sets originating from wide range of research studies are composed of multiple variables that are correlated and of dissimilar types, primarily of count, binary/ordinal and continuous attributes. The present paper builds on the previous works on multivariate data generation and develops a framework for generating multivariate mixed data with a pre-specified correlation matrix. The generated data consist of components that are marginally count, binary, ordinal and continuous, where the count and continuous variables follow the generalized Poisson and normal distributions, respectively. The use of the generalized Poisson distribution provides a flexible mechanism which allows under- and over-dispersed count variables generally encountered in practice. A step-by-step algorithm is provided and its performance is evaluated using simulated and real-data scenarios.

First trimester initiation of prenatal care in the US-Mexico border region.

OBJECTIVES: To systematically examine prevalence of first trimester prenatal care (FTPNC) in the 44 US counties and 80 Mexican municipios of the binational border region; and to describe disparities between border and nonborder areas within states, border states, and countries. METHODS: We combined 2009 records of singleton live births from the 10 US-Mexico border states (N=1,370,206) into a single file. We included FTPNC; county/municipio, state, and country of maternal residence; and demographic variables common to all records. We computed prevalence of FTPNC for border and nonborder residents by state and country. Using multivariable regression, we computed adjusted prevalence ratios (aPR) for FTPNC in border relative to nonborder residents, states relative to one another, and the US relative to Mexico. RESULTS: In 2009, 68.8% of US-Mexico border mothers and 72.9% of nonborder mothers received FTPNC. After adjustment, nonborder residents had higher prevalence of FTPNC than border residents in Sonora, New Mexico, Arizona, Coahuila, and Chihuahua (aPR=1.09-124). In US states, prevalence was 13%-36% higher in New Mexico, Arizona, and California than Texas. In Mexico, when compared with Coahuila, adjusted prevalence was 12%-20% higher in neighboring states. Between countries, FTPNC prevalence in border counties/municipios was higher in Mexico among women with low parity/low education and in the United States among women with high parity/high education. CONCLUSIONS: In the US and Mexico, women in border counties/municipios receive less timely prenatal care than their nonborder counterparts, but the magnitude of the disparity varies by state. Lack of a consistent, binational approach to birth data collection requires cautious interpretation of findings.

Likelihood-Based Random-Effect Meta-Analysis of Binary Events.

Meta-analysis has been used extensively for evaluation of efficacy and safety of medical interventions. Its advantages and utilities are well known. However, recent studies have raised questions about the accuracy of the commonly used moment-based meta-analytic methods in general and for rare binary outcomes in particular. The issue is further complicated for studies with heterogeneous effect sizes. Likelihood-based mixed-effects modeling provides an alternative to moment-based methods such as inverse-variance weighted fixed- and random-effects estimators. In this article, we compare and contrast different mixed-effect modeling strategies in the context of meta-analysis. Their performance in estimation and testing of overall effect and heterogeneity are evaluated when combining results from studies with a binary outcome. Models that allow heterogeneity in both baseline rate and treatment effect across studies have low type I and type II error rates, and their estimates are the least biased among the models considered.

Breast cancer prevention knowledge, beliefs, and information sources between non-Hispanic and Hispanic college women for risk reduction focus.

Although growing research focuses on breast cancer screenings, little is known about breast cancer prevention with risk reduction awareness for ethnic differences among college-age women. This study examined breast cancer prevention knowledge, beliefs, and information sources between non-Hispanic and Hispanic college women. Using a cross-sectional study, women at a university in the Southwest completed a 51-item survey about breast cancer risk factors, beliefs, and media and interpersonal information sources. The study was guided by McGuire's Input Output Persuasion Model. Of the 546 participants, non-Hispanic college women (n = 277) and Hispanic college women (n = 269) reported similar basic knowledge levels of modifiable breast cancer risk factors for alcohol consumption (52 %), obesity (72 %), childbearing after age 35 (63 %), and menopausal hormone therapy (68 %) using bivariate analyses. Most common information sources were Internet (75 %), magazines (69 %), provider (76 %) and friends (61 %). Least common sources were radio (44 %), newspapers (34 %), and mothers (36 %). Non-Hispanic college women with breast cancer family history were more likely to receive information from providers, friends, and mothers. Hispanic college women with a breast cancer family history were more likely to receive information from their mothers. Breast cancer prevention education for college women is needed to include risk reduction for modifiable health behavior changes as a new focus. Health professionals may target college women with more information sources including the Internet or apps.

Differences among college women for breast cancer prevention acquired information-seeking, desired apps and texts, and daughter-initiated information to mothers.

The purpose of this study was to examine among college women acquired breast cancer prevention information-seeking, desired apps and texts, and information given to mothers. Using a cross-sectional study, a survey was administered to college women at a southwestern university. College women (n = 546) used the Internet (44 %) for active breast cancer prevention information-seeking and used the Internet (74 %), magazines (69 %), and television (59 %) for passive information receipt. Over half of the participants desired breast cancer prevention apps (54 %) and texts (51 %). Logistic regression analyses revealed predictors for interest to receive apps were ethnicity (Hispanic), lower self-efficacy, actively seeking online information, and older age and predictors for interest to receive texts were lower self-efficacy and higher university level. Eighteen percent of college women (n = 99) reported giving information to mothers and reported in an open-ended item the types of information given to mothers. Predictors for giving information to mothers were actively and passively seeking online information, breast self-exam practice, and higher university level. Screenings were the most frequent types of information given to mothers. Breast cancer prevention information using apps, texts, or Internet and daughter-initiated information for mothers should be considered in health promotion targeting college students or young women in communities. Future research is needed to examine the quality of apps, texts, and online information and cultural differences for breast cancer prevention sources.

FDA Approval Summary: Durvalumab and Pembrolizumab, Immune Checkpoint Inhibitors for the Treatment of Biliary Tract Cancer.

On September 2, 2022, the Food and Drug Administration (FDA) approved durvalumab in combination with cisplatin and gemcitabine, for the treatment of patients with unresectable or metastatic biliary tract cancers (BTC). On October 31, 2023, the FDA approved pembrolizumab in combination with cisplatin and gemcitabine for the same indication. Approvals were based on two randomized, multiregional, placebo-controlled trials that randomly allocated patients to receive durvalumab (TOPAZ-1) or pembrolizumab (KEYNOTE-966) in combination with chemotherapy or placebo in combination with chemotherapy. Overall survival (OS) was the primary endpoint in both studies. In both studies, a statistically significant and clinically meaningful improvement in OS was demonstrated. In the TOPAZ-1 trial, the median OS of patients receiving durvalumab was 12.8 months [95% confidence interval (CI), 11.1-14.0] and 11.5 months (95% CI, 10.1-12.5) in patients receiving placebo [hazard ratio (HR), 0.80 (95% CI, 0.66-0.97)]. In the KEYNOTE-966 trial, the median OS of patients receiving pembrolizumab was 12.7 months (95% CI, 11.5-13.6) and 10.9 months (95% CI, 9.9-11.6) in patients receiving placebo [HR, 0.83 (95% CI, 0.72-0.95)]. The addition of checkpoint inhibitors to standard of care chemotherapy for this indication did not reveal any new adverse event signals, and the safety profile was generally consistent with the known clinical experience with durvalumab, pembrolizumab, and the backbone chemotherapy regimen. The approvals of durvalumab and pembrolizumab in combination with standard of care cisplatin and gemcitabine for the treatment of unresectable or metastatic BTC add two new therapeutic options for these patients.

FDA Approval Summary: Dabrafenib in Combination with Trametinib for BRAFV600E Mutation-Positive Low-Grade Glioma.

On March 16, 2023, the FDA approved dabrafenib in combination with trametinib (Tafinlar, Mekinist; Novartis Pharmaceuticals Corporation) for the treatment of pediatric patients with low-grade glioma (LGG) with a BRAFV600E mutation who require systemic therapy. FDA also approved oral formulations of both drugs suitable for patients who cannot swallow pills. This approval was based on the LGG cohort from study CDRB436G2201 (NCT02684058), a multicenter, open-label trial in which pediatric patients with LGG with a BRAFV600E mutation were randomly assigned 2:1 to dabrafenib plus trametinib (D+T) or carboplatin plus vincristine (C+V). The overall response rate (ORR) by independent review based on Response Assessment in Neuro-oncology LGG (2017) criteria was assessed in 110 patients randomly assigned to D+T (n = 73) or C+V (n = 37). ORR was 47% [95% confidence interval (CI), 35-59] in the D+T arm and 11% (95% CI, 3.0-25) in the C+V arm. Duration of response (DOR) was 23.7 months (95% CI, 14.5-NE) in the D+T arm and not estimable (95% CI, 6.6- NE) in the C+V arm. Progression-free survival (PFS) was 20.1 months (95% CI: 12.8, NE) and 7.4 months (95% CI, 3.6- 11.8) [HR, 0.31 (95% CI, 0.17-0.55); P < 0.001] in the D+T and C+V arms, respectively. The most common (>20%) adverse reactions were pyrexia, rash, headache, vomiting, musculoskeletal pain, fatigue, diarrhea, dry skin, nausea, hemorrhage, abdominal pain, and dermatitis acneiform. This represents the first FDA approval of a systemic therapy for the first-line treatment of pediatric patients with LGG with a BRAFV600E mutation.

Improving Collection and Analysis of Overall Survival Data.

Advances in anticancer therapies have provided crucial benefits for millions of patients who are living long and fulfilling lives. Although these successes should be celebrated, there is certainly room to continue improving cancer care. Increased long-term survival presents additional challenges for determining whether new therapies further extend patients' lives through clinical trials, commonly known as the gold standard endpoint of overall survival (OS). As a result, an increasing reliance is observed on earlier efficacy endpoints, which may or may not correlate with OS, to continue the timely pace of translating innovation into novel therapies available for patients. Even when not powered as an efficacy endpoint, OS remains a critical indication of safety for regulatory decisions and is a key aspect of the FDA's Project Endpoint. Unfortunately, in the pursuit of earlier endpoints, many registrational clinical trials lack adequate planning, collection, and analysis of OS data, which complicates interpretation of a net clinical benefit or harm. This article shares best practices, proposes novel statistical methodologies, and provides detailed recommendations to improve the rigor of using OS data to inform benefit-risk assessments, including incorporating the following in clinical trials intending to demonstrate the safety and effectiveness of cancer therapy: prospective collection of OS data, establishment of fit-for-purpose definitions of OS detriment, and prespecification of analysis plans for using OS data to evaluate for potential harm. These improvements hold promise to help regulators, patients, and providers better understand the benefits and risks of novel therapies.

FDA Approval Summary: Repotrectinib for Locally Advanced or Metastatic ROS1-Positive Non-Small Cell Lung Cancer.

On November 15, 2023, the U.S. Food and Drug Administration (FDA) granted traditional approval to repotrectinib (Augtyro, Bristol Myers Squibb Corporation) for the treatment of adult patients with locally advanced or metastatic receptor tyrosine kinase encoded by the ROS1 gene (ROS1)-positive non-small cell lung cancer (NSCLC). The approval was based on TRIDENT-1, a single-arm trial with multiple cohorts of patients with ROS1 fusion-positive (hereafter "ROS1-positive") NSCLC (NCT03093116), who were either treatment naïve or had received prior ROS1 tyrosine kinase inhibitor (TKI) and/or platinum-based chemotherapy. The primary efficacy outcome measure is objective response rate (ORR) assessed by blinded independent central review (BICR) using response evaluation criteria in solid tumors version 1.1. ORR was assessed in 71 patients who were ROS1 TKI naïve and 56 patients who had received a prior ROS1 TKI. Among the 71 patients who were ROS1 TKI naïve, the ORR was 79% (95% CI, 68-88), median duration of response was 34.1 months (95% CI, 26-NE). In patients who had received a prior ROS1 TKI and no prior chemotherapy, the ORR was 38% (95% CI, 25-52). The median duration of response was 14.8 months (95% CI, 7.6-NE); BICR-assessed responses were observed in CNS metastases in patients in both cohorts and in patients who developed resistance mutations following prior TKI therapy. The most common (>20%) adverse reactions were dizziness, dysgeusia, peripheral neuropathy, constipation, dyspnea, ataxia, fatigue, cognitive disorders, and muscular weakness. A unique feature of this ROS1 TKI approval is the inclusion of robust evidence of efficacy in patients with ROS1-positive NSCLC who had progressed on prior ROS1 TKIs.

Methodology for Good Machine Learning with Multi-Omics Data.

In 2020, Novartis Pharmaceuticals Corporation and the U.S. Food and Drug Administration (FDA) started a 4-year scientific collaboration to approach complex new data modalities and advanced analytics. The scientific question was to find novel radio-genomics-based prognostic and predictive factors for HR+/HER- metastatic breast cancer under a Research Collaboration Agreement. This collaboration has been providing valuable insights to help successfully implement future scientific projects, particularly using artificial intelligence and machine learning. This tutorial aims to provide tangible guidelines for a multi-omics project that includes multidisciplinary expert teams, spanning across different institutions. We cover key ideas, such as "maintaining effective communication" and "following good data science practices," followed by the four steps of exploratory projects, namely (1) plan, (2) design, (3) develop, and (4) disseminate. We break each step into smaller concepts with strategies for implementation and provide illustrations from our collaboration to further give the readers actionable guidance.

Sample size determination for clustered count data.

We consider the problem of sample size determination for count data. Such data arise naturally in the context of multicenter (or cluster) randomized clinical trials, where patients are nested within research centers. We consider cluster-specific and population-averaged estimators (maximum likelihood based on generalized mixed-effect regression and generalized estimating equations, respectively) for subject-level and cluster-level randomized designs, respectively. We provide simple expressions for calculating the number of clusters when comparing event rates of two groups in cross-sectional studies. The expressions we derive have closed-form solutions and are based on either between-cluster variation or intercluster correlation for cross-sectional studies. We provide both theoretical and numerical comparisons of our methods with other existing methods. We specifically show that the performance of the proposed method is better for subject-level randomized designs, whereas the comparative performance depends on the rate ratio for the cluster-level randomized designs. We also provide a versatile method for longitudinal studies. Three real data examples illustrate the results.

Breast cancer prevention knowledge, attitudes, and behaviors among college women and mother-daughter communication.

Although breast cancer prevention targets mostly women ages 40 and older, little is known about breast cancer prevention for young women and mother's advice. The purpose of this study was to examine breast cancer prevention knowledge, attitudes, and behaviors among college women and mother-daughter communication. Hispanic and non-Hispanic students at a southwestern university completed a breast cancer prevention survey with items for mother's advice, breast self-awareness and risk reduction knowledge, self-efficacy, susceptibility, family history, provider breast self-exam (BSE) recommendation, peer norms, BSE practice, and demographics. An openended item was also used to elicit types of mother's advice. Logistic regression was used to assess predictors for receiving mother's advice for breast cancer prevention and BSE practice. Self-reported data using a survey were obtained from 546 college women with a mean age of 23.3 (SD = 7.75). Nearly 36 % received mothers' advice and 55 % conducted BSE. Predictors for receiving mother's advice were age, self-efficacy, and family history of breast cancer. Predictors for BSE practice were mother's advice, age, self-efficacy, and provider BSE recommendation. Family history of breast cancer and knowledge were not significant predictors for BSE practice. Findings support the need for clinicians, community health educators, and mothers to provide breast cancer prevention education targeting college women.

Bayesian Methods in Human Drug and Biological Products Development in CDER and CBER.

The Center for Drug Evaluation and Research (CDER) and the Center for Biologics Evaluation and Research (CBER) of the U.S. Food and Drug Administration (FDA) have been leaders in protecting and promoting the U.S. public health by helping to ensure that safe and effective drugs and biological products are available in the United States for those who need them. The null hypothesis significance testing approach, along with other considerations, is typically used to demonstrate the effectiveness of a drug or biological product. The Bayesian framework presents an alternative approach to demonstrate the effectiveness of a treatment. This article discusses the Bayesian framework for drug and biological product development, highlights key settings in which Bayesian approaches may be appropriate, and provides recent examples of the use of Bayesian approaches within CDER and CBER.